Main Conference
Track 1 – Phy & Fundamentals
Session T1-S1
Millimeter-Wave Systems 1
Conference
11:00 AM
—
12:30 PM KST
Local
May 25 Mon, 7:00 PM
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8:30 PM PDT
An Analytical Model for Efficient Indoor THz Access Point Deployment
Rohit Singh and Doug Sicker (Carnegie Mellon University, USA)
3
Ultra-densification of user equipment (UE) and access points (APs) are anticipated to take a toll on the future spectrum needs. Higher frequency bands, such as mmWave (30-300GHz) and THz spectrum (0.3-10THz), can be used to cater to the high-throughput needs of ultra-dense networks. These high-frequency bands have a tremendous amount of green-filed contiguous spectrum, ranging in hundreds of GHz. However, these bands, especially the THz bands, face numerous challenges, such as high spreading, absorption, and penetration losses. To combat these challenges, the THz-APs need to be either equipped with high transmit power, high antenna gains (i.e., narrow antenna beams), or limit the communication to short-ranges. All of these factors are bounded due to technical or economic challenges, which will result in a "distance-power dilemma" while deciding on the deployment strategy of THz-APs. In this paper, we present an analytical model to deploy THz-APs in an indoor setting efficiently. We further show through extensive numerical analysis, the optimal number of APs and optimal room length for different blocks of the THz spectrum. Furthermore, these THz-APs need to be efficiently packed to avoid outages due to handoffs, which can add more complexity to the dilemma. To mitigate the packing problem, we propose two solutions over the optimal solution: (a) Radius Increase, and (b) Repeater Assistance, and present an analytical model for each.
Opportunistic Hybrid Beamforming based on Adaptive Perturbation for mmWave Multi-User MIMO Systems
Thuan Van Le and Kyungchun Lee (Seoul National University of Science and Technology, Korea (South))
2
In this paper, we propose an adaptive perturbation- aided opportunistic hybrid beamforming (AP-OHBF) scheme for temporally correlated millimeter wave (mmWave) channels. The basic idea is that the proposed scheme perturbs the channel parameters to track the channels of the scheduled mobile stations (MSs), whose channels are in favorable conditions, based on only the signal-to-interference-plus-noise ratio (SINR) information of MSs. The BS utilizes these parameters to generate the precoders and adopts the successful perturbation for data transmission, which achieves performance improvements. By contrast, if a perturbation results in performance degradation, it is discarded, whereas the precoders corresponding to the best-known parameters in the memory are instead used.
Maximum Sub-array Diversity for mmWave Network under RF Power Leakage and Distortion Noises
Leila Tlebaldiyeva and Behrouz Maham (Nazarbayev University, Kazakhstan); Olav Tirkkonen (Aalto University, Finland)
2
This paper investigates millimeter wave (mmWave) networks operating on a hybrid beamforming (HB) system where a base station with massive MIMO antennas communicates with user equipment (UE) nodes equipped with a single antenna. Space division multiple access allows simultaneous data transmission,however, it causes RF power leakage between UE nodes that originates from side/back lobe gains of antenna arrays. A maximum sub-array transmission diversity technique implemented on HB is proposed to improve the system performance under RF power leakage and residual distortion noise. In this work, we emphasize how RF power leakage and residual distortion noise constraints degrade the quality of communication performance in terms of outage probability (OP) and ergodic capacity. The closed-form expressions for the OP and ergodic capacity are corroborated through Monte-Carlo simulations. Simulation results demonstrate that the effect of distortion noise is more severe at high signal power due to the proportionality of distortion noise to signal power.
Enabling Massive Connections Using Hybrid Beamforming in Terahertz Micro-Scale Networks
Hang Yuan (Beijing Institute of Technology, China); Nan Yang (The Australian National University, Australia); Kai Yang (Beijing Institute of Technology, China); Chong Han (Shanghai Jiao Tong University, China); Jianping An (Beijing Institute of Technology, China)
2
We propose a novel hybrid beamforming (BF) scheme with distance-aware multi-carrier (DAMC) modulation and beam division multiple access (BDMA) to enable massive connections in terahertz (THz) micro-scale networks. This scheme breaks a fundamental limitation in hybrid BF, i.e., the number of users that are simultaneously supported cannot exceed the number of RF chains. Some unique properties of THz channels, such as high distance-and-frequency dependence, high sparsity, and small angular spread, are exploited in this scheme. First, we propose a user grouping scheme with rough beam pre-scanning and a DAMC spectrum allocation scheme to eliminate intra- group interference. Then, we propose a wideband hybrid BF designing algorithm using the principles of BDMA to control inter-group interference. Furthermore, we propose an iterative power allocation strategy to maximize the achievable sum-rate of the network. Simulation results are presented to show that our proposed hybrid BF DAMC-BDMA scheme achieves higher sumrate than the fully digital BF scheme in the high transmit power regime, due to the high sparsity of THz channels. Simulation results also demonstrate that our iterative power allocation strategy has strong robustness against uncertain interferences.
Particle Swarm Optimization Inspired Low-complexity Beamforming for MmWave Massive MIMO Systems
Lina Hou (Inner Mongolia University, China); Yang Liu (Institute of Electronic Information Engineering, Inner Mongolia University, China); Xuehui Ma and Yuting Li (Inner Mongolia University, China); Shun Na (Institute of Electronic Information Engineering, Inner Mongolia University, China); Minglu Jin (Dalian University of Technology, China)
4
The codebook-based techniques are extensively utilized in analog beamforming and combining to overcome high path-loss in millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) communications. However, to find the best analog precoder and combiner, a complex search based on predefined codebook is required in conventional schemes, which leads to large time cost. For the purpose of reducing complexity, we propose a new integer coded quantified angles- based particle swarm optimization (IC-PSO) beamforming algorithm. We firstly propose a joint search scheme based on integer coded (IC) quantified angles which transforms the search space into the integer field to simplify the search space. To converge to the optimal solution quickly, an improved particle swarm optimization (PSO) algorithm is further proposed. In this way, the best precoder and combiner can be found with lower complexity. Furthermore, we optimize the inertia weight and acceleration coefficients and process the out-of-bounds particles, which can improve the search ability of the PSO. Theoretical analysis indicates that the proposed IC-PSO beamforming has the lower complexity than some existing methods. Simulation results show that the algorithm has a satisfactory achievable rate which can achieve almost 98% performance of the full-search beamforming.
Session Chair
Seungnyun Kim (Seoul National University, Korea (South))
Session T1-S2
Deep Learning for Wireless Communications 1
Conference
11:00 AM
—
12:30 PM KST
Local
May 25 Mon, 7:00 PM
—
8:30 PM PDT
Adversarial Jamming Attacks on Deep Reinforcement Learning Based Dynamic Multichannel Access
Chen Zhong, Feng Wang, M. Cenk Gursoy and Senem Velipasalar (Syracuse University, USA)
2
Adversarial attack strategies have been widely studied in machine learning applications, and now are increasingly attracting interest in wireless communications as the application of machine learning methods to wireless systems grows along with security concerns. In this paper, we propose two adversarial policies, one based on feed-forward neural networks (FNNs) and the other based on deep reinforcement learning (DRL) policies. Both attack strategies aim at minimizing the accuracy of a DRL-based dynamic channel access agent. We first present the two frameworks and the dynamic attack procedures of the two adversarial policies. Then we demonstrate and compare their performances. Finally, the advantages and disadvantages of the two frameworks are identified.
Multi-Agent Deep Reinforcement Learning for Secure UAV Communications
Yu Zhang (Tsinghua University, China); Zirui Zhuang (Beijing University of Posts and Telecommunications, China); Feifei Gao (Tsinghua University, China); Jingyu Wang (Beijing University of Posts and Telecommunications, China); Zhu Han (University of Houston, USA)
3
In this paper, we investigate a multi-unmanned aerial vehicle (UAV) cooperation mechanism for secure communications, where the UAV transmitter moves around to serve the multiple ground users (GUs) while the UAV jammers send the 3D jamming signals to the ground eavesdroppers (GEs) to protect the UAV transmitter from being wiretapped. The 3D jamming guarantees the GEs not being interfered by the jamming signals. It is challenging to make a joint trajectory design and power control for a UAV team without central control. To this end, we propose a multi-agent deep reinforcement learning approach to achieve the maximum sum secure rate by designing the dynamic trajectory of each UAV. The proposed multi-agent deep deterministic policy gradient (MADDPG) technique is centralized training at high altitude platforms (HAPs) and distributed execution at each UAV, which enables the fully distributed cooperation among UAVs. Finally, the simulation results show the proposed method can efficiently solve the multi-UAV cooperation trajectory design problem in secure communication scenarios.
Autoencoder based Friendly Jamming
Bui Minh Tuan (University of Engineering and Technology, Vietnam); Duc-Tuyen Ta (LRI, Université Paris Saclay, France & University of Engineering and Technology, VNU-HN, Vietnam); Nguyen Linh Trung (Vietnam National University, Hanoi, Vietnam); Nguyen Viet Ha (VNU Ha Noi, Vietnam)
1
Physical layer security (PLS) provides lightweight security solutions in which security is achieved based on the inherent random characteristics of the wireless medium. In this paper, we consider the PLS approach called friendly jamming (FJ), which is more practical thanks to its low computational complexity. State-of-the-art methods require that legitimate users have full channel state information (CSI) of their channel. Thanks to the recent promising application of the autoencoder (AE) in communication, we propose a new FJ method for PLS using AE without prior knowledge of the CSI. The proposed AE-based FJ method can provide good secrecy performance while avoiding explicit CSI estimation. We also apply the recently proposed tool for mutual information neural estimation (MINE) to evaluate the secrecy capacity. Moreover, we leverage MINE to avoid end-to- end learning in AE-based FJ.
Exploiting a low-cost CNN with skip connection for robust automatic modulation classification
Thien Huynh-The (Kumoh National Institute of Technology, Korea (South)); Cam-Hao Hua (Kyung Hee University, Korea (South)); Jae Woo Kim, Seung-Hwan Kim and Dong Seong Kim (Kumoh National Institute of Technology, Korea (South))
4
Recently, deep learning (DL) is an innovative machine learning (ML) technique that has gained the outstanding achievements in computer vision and natural language processing. This work takes advantage of DL for effectively handling automatic modulation classification (AMC), which is the fundamental function of numerous cognitive radio-based and spectrum sensing-based applications in many modern communication systems. Concretely, a novel deep convolutional neural network (DCNN) is proposed for learning a classification model from a massive amount of modulated signals, in which the network architecture has several convolutional blocks specialized to simultaneously capture the temporal intra-signal correlations and the spatial inter-signal relations. To this end, each block comprises various convolutional layers of asymmetric convolution kernels, whose outputs are gathered via a concatenation layer. For the enrichment of multi-scale deep feature and the prevention of gradient vanishing problem, these blocks are associated by skip connections to take into account the useful residual information. In experiments, the proposed CNN-based AMC method achieves the overall 24-modulation classification rate of 88.22% at 10dB SNR on the well-known DeepSig dataset.
A Linear Bayesian Learning Receiver Scheme for Massive MIMO Systems
Alva Kosasih, Wibowo Hardjawana and Branka Vucetic (The University of Sydney, Australia); Chao-Kai Wen (National Sun Yat-sen University, Taiwan)
3
Much stringent reliability and processing latency requirements in ultra-reliable-low-latency-communication (URLLC) traffic make the design of linear massive multipleinput-multiple-output (M-MIMO) receivers becomes very challenging. Recently, Bayesian concept has been used to increase the detection reliability in minimum-mean-square-error (MMSE) linear receivers. However, the latency processing time is a major concern due to the exponential complexity of matrix inversion operations in MMSE schemes. This paper proposes an iterative M-MIMO receiver that is developed by using a Bayesian concept and a parallel interference cancellation (PIC) scheme, referred to as a linear Bayesian learning (LBL) receiver. PIC has a linear complexity as it uses a combination of maximum ratio combining (MRC) and decision statistic combining (DSC) schemes to avoid matrix inversion operations. Simulation results show that the bit-error-rate (BER) and latency processing performances of the proposed receiver outperform the ones of MMSE and best Bayesian-based receivers by minimum 2 dB and 19 times for various M-MIMO system configurations.
Session Chair
Wonjae Shin (Pusan National University, Korea (South))
Session T1-S3
Energy Efficiency in 5G and HetNets
Conference
11:00 AM
—
12:30 PM KST
Local
May 25 Mon, 7:00 PM
—
8:30 PM PDT
Energy Harvesting-Enabled Full-Duplex DF Relay Systems with Improper Gaussian Signaling
Jhe-Yi Lin and Ronald Y. Chang (Academia Sinica, Taiwan); Hen-Wai Tsao and Hsuan-Jung Su (National Taiwan University, Taiwan)
0
Loop interference (LI) is the main performance- limiting factor in full-duplex (FD) relaying systems. In this paper, we propose using improper Gaussian signaling (IGS) in joint source and relay transmission to achieve a better LI resistance and, as a result, a better end-to-end system throughput in energy harvesting (EH) enabled FD relaying systems. An alternating optimization (AO) algorithm is proposed to solve the challenging design problem of finding the optimal transmission with IGS at both the source and relay, as well as the optimal power-splitting (PS) factor at the EH-enabled relay. The relationship between the PS factor and the optimal pseudo-variances is derived in closed form. Numerical results demonstrate the superior throughput performance yielded by IGS at the same LI level, and suggest the possibility of employing IGS as a replacement of a sophisticated LI canceller in practical FD relaying systems.
Low-Complexity Hybrid Precoding and Combining Scheme Based on Array Response Vectors
Eduard Bahingayi and Kyungchun Lee (Seoul National University of Science and Technology, Korea (South))
3
The hybrid precoding and combining algorithms for mmWave massive multiple-input multiple-output (MIMO) systems must consider the trade-off between the complexity and performance of the system. Unfortunately, because of the unit-norm constraint imposed by the use of phase shifters, the optimization of the radio frequency (RF) precoder and combiner becomes a non-convex problem. As a consequence, the algorithm for hybrid precoding and combining design often incurs high complexity. This paper proposes a low-complexity algorithm for hybrid precoding and combining design based on array response vectors. The proposed algorithm considers a decoupled optimization scheme between the RF and baseband domains for the spectral efficiency-maximization problem. In the RF domain, we propose an incremental successive selection method to find a subset of array response vectors from a dictionary, which forms the RF precoding/combining matrices. For the digital domain, we employ singular-value decomposition (SVD) of the low-dimensional effective channel matrix to generate the digital baseband precoder and combiner. Through numerical simulation, we show that the proposed algorithm achieves near- optimal performance with 89.9% — 99.4% complexity reduction compared to the conventional state-of-the-art hybrid precoding and combining algorithm.
Energy Efficiency Optimization for Beamspace Massive MIMO Systems with Low-Resolution ADCs
Hualian Sheng and Xihan Chen (Zhejiang University, China); Kaiming Shen (University of Toronto, Canada); Xiongfei Zhai (Guangdong University of Technology, China); An Liu and Minjian Zhao (Zhejiang University, China)
1
In this article, we propose a sparse hybrid combining (SHC) scheme for the uplink transmission of beamspace massive multiple-input multiple-output (MIMO) system with low- resolution analog to digital converters (LADCs), to alleviate the performance bottleneck caused by the multi-user interference and quantization noise, with reduced hardware cost and power consumption. To this end, we formulate the optimization of the proposed SHC scheme as a system energy efficiency maximization problem under some practical constraints. The resulting problem contains the highly coupled nonconvex objective function, as well as the discrete binary constraints. By exploiting some fractional programming (FP) techniques and introducing auxiliary variables, we first recast the original challenging problem into a more tractable yet equivalent form. We then develop an efficient double-loop iterative algorithm based on the penalty dual decomposition (PDD) method to find its local stationary solutions. Finally, simulation results verify the effectiveness of the proposed SHC scheme by numerical examples in terms of the achieved system energy efficiency.
Energy-Efficient Design for Massive Access in B5G Cellular Internet of Things
Feiyan Tian and Xiaoming Chen (Zhejiang University, China)
0
In this paper, we investigate an energy-efficient grant-free random access protocol for beyond fifth-generation (B5G) cellular internet of things (IoT) with sporadic traffic. A design framework, including device activity information (DAI) and channel state information (CSI) acquisition and uplink data transmission, is first provided to support massive access over limited radio spectrum. Then, considering the low-power requirement of IoT devices, we propose a robust massive access scheme by jointly optimizing pilot transmit power, data transmit power and receive vector at the base station (BS) for maximizing the energy efficiency in the presence of channel uncertainty. Finally, extensive simulation results validate the effectiveness and robustness of the proposed scheme.
Energy Efficient Ultra-Dense Network Using Long Short-Term Memory
Junwon Son, Seungnyun Kim and Byonghyo Shim (Seoul National University, Korea (South))
0
The energy consumption of cellular systems is becoming a matter of grave concern in both economic and environmental perspectives. Recently, in order to reduce the energy consumption of base stations (BSs), which takes the largest portion, turning off under-loaded BSs has been suggested. However, determining the on/off mode of BSs is a non-convex optimization problem. Also, the problem must be solved in accordance with the time-varying environment since the transition overhead in the future may outrun the power saving at the moment. In this paper, we propose Long Short-Term Memory (LSTM) based framework to make far-sighted control decisions maximizing energy efficiency from a long-term perspective. The LSTM-based network can intelligently determine the on/off modes, utilizing the time-correlated property of the channel and approximating complex mapping between channel state and desired power control coefficient. Lastly, through the convex optimization technique, the optimal power allocation for the active BSs can be found. Simulation results show that the proposed technique outperforms the conventional techniques by a large margin.
Session Chair
Wan Choi (Seoul National University & KAIST, Korea (South))
Session T1-S4
NOMA (Non-Orthogonal Multiple Access)
Conference
2:00 PM
—
3:30 PM KST
Local
May 25 Mon, 10:00 PM
—
11:30 PM PDT
Covert Non-Orthogonal Multiple Access
Hien Ta and Sang Wu Kim (Iowa State University, USA)
4
We consider hiding a covert (private) message in non-orthogonal multiple access (NOMA) systems by superimposing (embedding) it under non-covert (public) messages. We determine the total detection error probability (sum of false alarm and missed detection probability), the adversary's optimum detection strategy that minimizes the total detection error probability, and the communicator's optimum message hiding strategy that maximizes the total detection error probability. Additionally, we explore exploiting the channel variations to further increase the total detection error probability. We show that the total detection error probability increases and converges to 1 as the number of users increases and that the total detection error probability can be increased by increasing the transmission power when the channel variation is exploited.
Finite-Alphabet Signature Design for Grant-Free NOMA using Quantized Deep Learning
Hanxiao Yu and Fei Zesong (Beijing Institute of Technology, China); Zhong Zheng (National Institute of Standards and Technology, USA); Neng Ye (Beijing Institute of Technology, China); Sen Wang (China Mobile Research Institute, China)
1
Grant-free Non-Orthogonal Multiple Access (NOMA) techniques are able to reduce the signaling overhead and the transmission latency in multi-user communications system. However, most of the existing code-domain grant-free NOMA schemes reuse the spreading signatures designed for the grant- based scenarios. Considering the sparsity and randomness nature of user activities in the uplink transmissions, we propose a deep learning-based signature design, where the non-equal user activation probabilities are exploited to optimize the code-domain NOMA signature. In addition, the conventional grant-free NOMA signatures are not specifically designed over finite Galois field, which hinders the implementation of the encoder/decoder using practical hardware. To address these challenges, we utilize the quantized deep learning framework for the NOMA signature training, which jointly optimizes the sequence generation and the quantization. The numerical results reveal that the obtained signatures outperform the conventional ones especially when the users has unequal activation probabilities.
Physical Layer Secrecy of NOMA-Based Hybrid Satellite-Terrestrial Relay Networks
Vinay Bankey, Vibhum Singh and Prabhat Kumar Upadhyay (Indian Institute of Technology Indore, India)
2
In this paper, we investigate the physical layer security of a non-orthogonal multiple access (NOMA) based downlink hybrid satellite-terrestrial relay network where the satellite communicates with terrestrial NOMA users in the presence of an eavesdropper via an amplify-and-forward relay. To analyze the secrecy performance of this network, we derive new closed- form expressions of secrecy outage probability (SOP) and the probability of positive secrecy capacity by adopting shadowed-Rician fading for the satellite link and Nakagami-m fading for terrestrial links. To get more insights, we further derive the closed- form expression for asymptotic SOP and illustrate the behavior of SOP at high signal-to-noise ratio regime. The analytical results are corroborated through Monte-Carlo simulations.
Performance Analysis of the Virtual Full-Duplex Non-Orthogonal Multiple Access Systems
Yafang Zhang and Suili Feng (South China University of Technology, China)
4
Full-duplex (FD) and non-orthogonal multiple access (NOMA) are the principal means to improve the spectral efficiency of the system. In this paper, a virtual full-duplex NOMA (VFD-NOMA) scheme is proposed, in which a pair of geographically distributed half-duplex remote radio units (RRU) are used to imitate the traditional FD-enabled BS and to serve the uplink and downlink users simultaneously with the centralized control of the baseband processing unit (BPU). We investigate the outage probability and ergodic sum rate of the proposed scheme and obtain their closed-form expressions with perfect and imperfect interference cancellation. Simulation results not only show the feasibility of the developed analysis, but also unveil the performance gains achieved by the proposed scheme over the conventional full-duplex NOMA scheme.
Compressive Sensing based User Activity Detection and Channel Estimation in Uplink NOMA Systems
Yuanchen Wang (University of Liverpool, United Kingdom (Great Britain)); Xu Zhu (University of Liverpool, United Kingdom (Great Britain) & Harbin Institute of Technology, Shenzhen, China); Eng Gee Lim (Xi'an Jiaotong-Liverpool University, China); Zhongxiang Wei (University College London & School of EE and CS, United Kingdom (Great Britain)); Yujie Liu (University of Liverpool, United Kingdom (Great Britain)); Yufei Jiang (Harbin Institute of Technology, Shenzhen, China)
3
Conventional request-grant based non-orthogonal multiple access (NOMA) incurs tremendous overhead and high latency. To enable grant-free access in NOMA systems, user activity detection (UAD) is essential. In this paper, we investigate compressive sensing (CS) aided UAD, by utilizing the property of quasi-time-invariant channel tap delays as the prior information. This does not require any prior knowledge of the number of active users like the previous approaches, and therefore is more practical. Two UAD algorithms are proposed, which are referred to as gradient based and time-invariant channel tap delays assisted CS (g-TIDCS) and mean value based and TIDCS (m-TIDCS), respectively. They achieve much higher UAD accuracy than the previous work at low signal-to-noise ratio (SNR). Based on the UAD results, we also propose a low-complexity CS based channel estimation scheme, which achieves higher accuracy than the previous channel estimation approaches.
Session Chair
Wonjae Shin (Pusan National University, Korea (South))
Session T1-S5
Next-Generation Communications
Conference
2:00 PM
—
3:30 PM KST
Local
May 25 Mon, 10:00 PM
—
11:30 PM PDT
Chemical Reactions-based Detection Mechanism for Molecular Communications
Trang N Cao (University of Melbourne, Australia); Vahid Jamali (Friedrich-Alexander-University Erlangen-N¨urnberg, Germany); Wayan Wicke (Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany); Phee Lep Yeoh (University of Sydney, Australia); Nikola Zlatanov (Monash University, Australia); Jamie S Evans (University of Melbourne, Australia); Robert Schober (Friedrich-Alexander University Erlangen-Nuremberg, Germany)
2
In molecular communications, the direct detection of signaling molecules may be challenging due to the lack of suitable sensors and interference from co-existing substances in the environment. Motivated by examples in nature, we investigate an indirect detection mechanism using chemical reactions between the signaling molecules and a molecular probe to produce an easy-to-measure product at the receiver. The underlying reaction-diffusion equations that describe the concentrations of the reactant and product molecules in the system are non-linear and coupled, and cannot be solved in closed-form. To analyze these molecule concentrations, we develop an efficient iterative algorithm by discretizing the time variable and solving for the space variables in each time step. We also derive insightful closed-form solutions for a special case. The accuracy of the proposed algorithm is verified by particle-based simulations. Our results show that the concentration of the product molecules has a similar characteristic over time as the concentration of the signaling molecules. We analyze the bit error rate (BER) for a threshold detector and highlight that significant improvements in the BER can be achieved by carefully choosing the molecular probe and optimizing the detection threshold.
Generalized Dimming Control Scheme with Optimal Dimming Control Pattern for VLC
Congcong Wang, Yang Yang, Caili Guo, Zhimin Zeng and Chunyan Feng (Beijing University of Posts and Telecommunications, China)
1
This paper proposes a simple dimming control scheme for multi-LED visible light communications (VLC), termed as generalized dimming control (GDC) scheme. The GDC performs dimming control by simultaneously adjusting the intensity of transmitted symbols and the number of active elements in a space-time matrix. The indices of active elements in each space-time matrix, as well as the modulated constellation symbols, are used to transmit information base on the space-time index modulation. Furthermore, the tradeoff between the intensity of transmitted symbols and the number of active elements in the space-time matrix is analyzed for enhancing the reliability of communication. To improve the communication reliability, a GDC with the minimum bit error rate (BER) criterion is first proposed to select the optimal dimming control pattern based on exhaustive search. Furthermore, to reduce the computational complexity, a low complexity GDC with the maximum free distance criterion is proposed. Simulation and numerical results show that the proposed scheme can outperform conventional dimming control schemes at both low and high dimming levels in terms of the BER performance.
Characterization for High-Speed Railway Channel enabling Smart Rail Mobility at 22.6 GHz
Lei Ma, Ke Guan, Dong Yan, Danping He and Bo Ai (Beijing Jiaotong University, China); Junhyeong Kim and Hee Sang Chung (ETRI, Korea (South))
1
The millimeter wave (mmWave) communication with large bandwidth is a key enabler for both the fifth- generation mobile communication system (5G) and smart rail mobility. Thus, in order to provide realistic channel fundamental, the wireless channel at 22.6 GHz is characterized for a typical high-speed railway (HSR) environment in this paper. After importing the three-dimensional environment model of a typical HSR scenario into a self-developed high-performance cloud- computing Ray-Tracing platform - CloudRT, extensive ray-tracing simulations are realized. Based on the results, the HSR channel characteristics are extracted and analyzed, considering the extra loss of various weather conditions. The results of this paper can help for the design and evaluation for the HSR communication systems enabling smart rail mobility.
Transmit laser selection for dual hop decode and forward UOWC cooperative communication
Anirban Bhowal and Rakhesh Singh Kshetrimayum (Indian Institute of Technology Guwahati, India)
1
Underwater optical wireless communication (UOWC) is an alternative to the existing acoustic and radio frequency (RF) underwater communication. In this paper, advanced schemes of UOWC like transmit laser selection (TLS) and TLS combined with optical spatial modulation (TLS-OSM) are proposed for weak oceanic turbulence based UOWC cooperative communication, which can enhance the performance of conventional UOWC communication. The performance is analyzed in terms of average symbol error probability (ASEP) and corroborated by Monte Carlo simulations. It is observed that TLS can achieve a signal to noise ratio (SNR) gain of at least 2 dB over the existing methods while TLS-OSM achieves a SNR gain of at least 3 dB over TLS scheme at any ASEP value of more than 10-2 , thereby validating the efficiency of our schemes.
Hybrid multiplexing in OFDM-based VLC systems
Cheng Chen (University of Edinburgh, United Kingdom (Great Britain)); Iman Tavakkolnia (University of Edinburgh & LiFi Research and Development Centre, United Kingdom (Great Britain)); Mohammad Dehghani Soltani and Majid Safari (University of Edinburgh, United Kingdom (Great Britain)); Harald Haas (The University of Edinburgh, United Kingdom (Great Britain))
3
In conventional visible light communication (VLC) systems with multiple light-emitting diodes (LEDs) and multiple photodiodes (PDs), high data rate transmission with limited modulation bandwidth can be achieved via spatial multiplexing (SMP) or wavelength division multiplexing (WDM). However, the number of multiplexing channels is limited by the strong spatial correlation in SMP and by the inter-colour crosstalk in WDM. In this paper, we propose a multiple-input multiple-output (MIMO) hybrid multiplexing (HMP) VLC system which avoids the disadvantages of SMP / WDM and explores the degrees-of- freedom (DoFs) in space and wavelength domains jointly. With appropriate system configuration, a MIMO channel matrix with a better channel condition in HMP can be obtained. Eventually, it is able to increase the number of multiplexing channels and support higher data rate transmission.
Session Chair
Yo-Seb Jeon (POSTECH, Korea (South))
Session T1-S6
Channel Modeling
Conference
2:00 PM
—
3:30 PM KST
Local
May 25 Mon, 10:00 PM
—
11:30 PM PDT
Joint Channel Equalization and Symbol Detection for IoT Devices in Severe Multipath Channels
Shusen Jing, Joseph Hall, Yahong Rosa Zheng and Chengshan Xiao (Lehigh University, USA); Zhiqun Deng (Pacific Northwest National Laboratory, USA)
0
Internet of Things (IoT) devices often transmit very short message blocks without strong error correction coding or pilots for channel equalization. When the transmitted signals encounter a severe multipath channel, the receiver is often unable to equalize the resulting inter-symbol interference (ISI) via traditional methods, leading to a high retransmission rate. This paper proposes a joint channel equalization and symbol detection scheme for this scenario by utilizing the preamble sequence as a training pilot for equalization and the relatively weak cyclic redundancy check (CRC) 8-Dallas code for error correction. By assuming a sparse channel impulse response, the proposed joint channel equalization and symbol detection scheme formulates an 11 norm constrained optimization problem and solves it by a saddle-point algorithm. The proposed algorithm is applied to a set of real-world underwater animal tracking IoT data, and the results show improvement of correct message detection rate from 21.5% (direct symbol decisions) to 41.6% (equalization and decoding).
A Novel Massive MIMO Beam Domain Channel Model
Fan Lai (Southeast University, China); Cheng-Xiang Wang (Southeast University & Heriot-Watt University, China); Jie Huang and Xiqi Gao (Southeast University, China); Fu-Chun Zheng (University of York, United Kingdom (Great Britain) & Southeast University, China)
1
A novel beam domain channel model (BDCM) for massive multiple-input multiple-output (MIMO) communication systems has been proposed in this paper. The near-field effect and spherical wavefront are firstly assumed in the proposed model, which is different from the conventional BDCM for MIMO based on the far-field effect and plane wavefront assumption. The proposed novel BDCM is the transformation of an existing geometry-based stochastic model (GBSM) from the antenna domain into beam domain. The space-time non-stationarity is also modeled in the novel BDCM. Moreover, the comparison of computational complexity for both models is studied. Based on the numerical analysis, comparison of cluster-level statistical properties between the proposed BDCM and existing GBSM has shown that there exists little difference in the space, time, and frequency correlation properties for two models. Also, based on the simulation, coherence bandwidths of the two models in different scenarios are almost the same. The computational complexity of the novel BDCM is much lower than the existing GBSM. It can be observed that the proposed novel BDCM has similar statistical properties to the existing GBSM at the cluster- level. The proposed BDCM has less complexity and is therefore more convenient for information theory and signal processing research than the conventional GBSMs.
Geometry based Stochastic Channel Modeling using Ambit Processes
Rakesh R. T. and Emanuele Viterbo (Monash University, Australia)
3
The simulation of vehicular wireless channels using geometry-based radio channel models is computationally intensive when the number of scatterers is significantly high. In this paper, we propose a new geometry-based stochastic channel model to simulate and analyze the aforementioned channels based on a framework developed from the theory of ambit processes. Under reasonable assumptions, the underlying mathematical structure of the proposed channel model enables the characterization of high mobility channels in terms of fading statistics, spatio-temporal channel correlation, and Doppler spectrum, besides ensuring tractable analysis. The developed algorithm facilitates fast simulation of high mobility channels and accounts for key features of vehicular channels including appearance and disappearance of multi-path components, spatial consistency, and captures the correlation between time-evolving delay and Doppler associated with multi-path components. Finally, we carry out simulations to obtain crucial insights about the characteristics of typical vehicle-to-infrastructure channels based on the proposed channel model.
A Practical Non-Stationary Channel Model for Vehicle-to-Vehicle MIMO Communications
Weidong Li and Qiuming Zhu (Nanjing University of Aeronautics and Astronautics, China); Cheng-Xiang Wang (Southeast University & Heriot-Watt University, China); Fei Bai, Xiao-min Chen and Xu Dazhuan (Nanjing University of Aeronautics and Astronautics, China)
0
In this paper, a practical model for non-stationary Vehicle-to-Vehicle (V2V) multiple-input multiple-output (MIMO) channels is proposed. The new model considers more accurate output phase of Doppler frequency and is simplified by the Taylor series expansions. It is also suitable for generating the V2V channel coefficient with arbitrary velocities and trajectories of the mobile transmitter (MT) and mobile receiver (MR). Meanwhile, the channel parameters of path delay and power are investigated and analyzed. The closed-form expressions of statistical properties, i.e., temporal autocorrelation function (TACF) and spatial cross-correlation function (SCCF) are also derived with the angle of arrival (AoA) and angle of departure (AoD) obeying the Von Mises (VM) distribution. In addition, the good agreements between the theoretical, simulated and measured results validate the correctness and usefulness of the proposed model.
Effects On Polarization Characteristics of Off-Body Channels with Dynamic Users
Kenan Turbic (INESC-ID / IST, University of Lisbon, Portugal); Luis M. Correia (IST/INESC-ID - University of Lisbon & INESC, Portugal)
0
This paper presents an analysis of the depolarization effect in off-body channels, based on a previously developed geometry-based channel model for polarized communications with dynamic users. The model considers Line-of-Sight propagation and components reflected from scatterers distributed on cylinders centered around the user. A mobility model for wearable antennas based on Fourier series is employed to take the effects of user's motion into account. The focus is on scattered signal components, where the impact of a scatter's position, its material properties, and the influence of user dynamics on signal depolarization are investigated. It is observed that the wearable antenna motion has a strong impact on the channel's polarization characteristics, particularly for dynamic on-body placements, such as arms and legs. If the antenna motion is neglected, the error in cross-polarization ratio is greater than 23 dB compared to a static approach. The antenna rotation during motion is found to be the dominant factor, while the corresponding displacement can be neglected, with the error not exceeding 1 dB. This result justifies the channel model simplification proposed in this paper.
Session Chair
Inkyu Bang (Hanbat National University, Korea (South))
Session T1-S7
Waveform and Modulation
Conference
2:00 PM
—
3:30 PM KST
Local
May 25 Mon, 10:00 PM
—
11:30 PM PDT
Cancellation Symbol Insertion for Spectrally Compact OFDM Pilot Waveform
Char-Dir Chung (National Taiwan University, Taiwan); Wei-Chang Chen (National Taipei University of Technology, Taiwan); Jia-Ling Jiang (MediaTek Inc., Taiwan)
0
Cancellation symbols (CSs) are inserted into guard subcarriers to suppress the sidelobe power of the OFDM pilot waveform for channel estimation. Different from the conventional schemes where CSs are designed to suppress the sidelobe power of composite OFDM waveforms conveying data and pilot symbols, the inserted CSs depend on pilot symbols only and are shown to make the spectrally compact pilot waveform at the cost of less cancellation symbol power. The composite OFDM waveforms conveying spectrally precoded data symbols, optimum pilot symbols, and pilot-dependent CSs are shown to exhibit highly compact spectrum, while maintaining the channel estimation optimality on the quasi-static multipath channel.
Low Complexity Iterative Rake Detector for Orthogonal Time Frequency Space Modulation
Tharaj Thaj and Emanuele Viterbo (Monash University, Australia)
3
This paper presents a linear complexity iterative rake detector for the recently proposed orthogonal time frequency space (OTFS) modulation scheme. The basic idea is to extract and combine the received multipath components of the transmitted symbols in the delay-Doppler grid using linear diversity combining schemes like maximal ratio combining (MRC), equal gain combining and selection combining to improve the SNR of the combined signal. We reformulate the OTFS input-output relation in the vector form by placing some null symbols in the delay-Doppler grid thereby exploiting the block circulant property of the channel matrix. Using the new input-output relation we propose a low complexity iterative detector based on the MRC scheme. The bit error rate (BER) performance of the proposed detector will be compared with the state of the art message passing detector and orthogonal frequency division multiplexing (OFDM) scheme employing a single tap minimum mean square error (MMSE) equalizer. We also show that the frame error rate (FER) performance of the MRC detector can be improved by employing error correcting codes operating in the form of a turbo decision feedback equalizer (DFE).
The Impact of CFO on OFDM based Physical-layer Network Coding with QPSK Modulation
Ling Fu Xie (Faculty of EECS, Ningbo University, China); Ivan Wang-Hei Ho and Zhenhui Situ (The Hong Kong Polytechnic University, Hong Kong); Peiya Li (Jinan University, China)
0
This paper studies Physical-layer Network Coding (PNC) in a two-way relay channel (TWRC) operated based on OFDM and QPSK modulation but with the presence of carrier frequency offset (CFO). CFO, induced by node motion and/or oscillator mismatch, causes inter-carrier interference (ICI) that impairs received signals in PNC. Our ultimate goal is to empower the relay in TWRC to decode network-coded information of the end users at a low bit error rate (BER) under CFO, as it is impossible to eliminate the CFO of both end users. For that, we first put forth two signal detection and channel decoding schemes at the relay in PNC. For signal detection, both schemes exploit the signal structure introduced by ICI, but they aim for different output, thus differing in the subsequent channel decoding. We then consider CFO compensation that adjusts the CFO values of the end nodes simultaneously and find that an optimal choice is to yield opposite CFO values in PNC. Particularly, we reveal that pilot insertion could play an important role against the CFO effect, indicating that we may trade more pilots for not just a better channel estimation but also a lower BER at the relay in PNC. With our proposed measures, we conduct simulation using repeat-accumulate (RA) codes and QPSK modulation to show that PNC can achieve a BER at the relay comparable to that of point-to-point transmissions for low to medium CFO levels.
A Novel Hybrid MSK Modulation Scheme for Additional Data Transmission
Zhengguang Xu (Huazhong University Of Science and Technology, China)
0
In the paper, a novel hybrid modulation scheme is proposed to embed a phase-modulated signal into the minimum shift keying (MSK) signal, where the additional signal could be used to transmit some additional important data. In order to achieve the imperceptibility of the additional signal to the MSK signal, the orthogonal condition between the additional signal and the MSK signal is investigated. The bit-error-rate (BER) performances of the hybrid modulation over addition white Gaussian noise (AWGN) channel are also investigated. The theoretical analysis and simulation results show that the additional signal with the orthogonal frequency makes little effect on the BER performance of the original MSK receiver, and the information in the additional signal is also robust.
Performance Analysis of Various Waveforms and Coding Schemes in V2X Communication Scenarios
Waqar Anwar (Technische Universität Dresden, Germany); Anton Krause (TU Dresden, Germany); Atul Kumar, Norman Franchi and Gerhard P. Fettweis (Technische Universität Dresden, Germany)
0
5G and beyond communications systems need to cope with a high degree of heterogeneity in terms of services and requirements. Specially, vehicle-to-everything (V2X) use cases require ultra-reliable and low latency communications (URLLC) under harsh channel conditions. To design an optimal waveform and coding scheme for such use cases is a key challenge. Therefore, new waveforms and coding techniques are need to be investigated. In this paper, we present a comparison of several waveform candidates (orthogonal frequency-division multiplexing (OFDM), discrete Fourier transform-spread-OFDM (DFT-s-OFDM), generalized frequency division multiplexing (GFDM) and orthogonal time frequency space (OTFS)) and coding schemes (convolution, turbo, low-density priority-check (LDPC) and polar) under a common framework. We consider two metrics, i.e. maximum data rates and packet error rate, to evaluate their performance under various fading conditions. The simulation results show that OTFS outperforms all other waveforms in both frequency selective and doubly selective channels. Regarding the coding schemes, turbo codes outperforms all other coding schemes, even though difference with LDPC codes is marginal.
Session Chair
Joon Ho Cho (Pohang University of Science and Technology (POSTECH), Korea (South))
Session T1-S10
Multiple Access and Interference Management
Conference
4:00 PM
—
5:30 PM KST
Local
May 26 Tue, 12:00 AM
—
1:30 AM PDT
Multiplexing More Data Streams in the MU-MISO Downlink by Interference Exploitation Precoding
Ang Li (Xi'an Jiaotong University, China); Christos Masouros (University College London, United Kingdom (Great Britain)); Xuewen Liao (Xi'an Jiaotong University, China); Yonghui Li and Branka Vucetic (University of Sydney, Australia)
1
In this paper, we focus on the constructive interference (CI) precoding for the scenario when the number of streams simultaneously transmitted by the base station (BS) is larger than that of transmit antennas at the BS, and derive the optimal precoding structure by employing the pseudo inverse. We show that the optimal pre-scaling vector in IE precoding is equal to a linear combination of the right singular vectors that correspond to zero singular values of the coefficient matrix. By formulating the dual problem, we further show that the optimal precoding matrix can be expressed as a function of the dual variables in a closed form, and an equivalent quadratic programming (QP) formulation is derived for computational complexity reduction. Numerical results validate our analysis and demonstrate significant performance improvements for interference exploitation precoding in the considered scenario.
Intelligent Reflecting Surface Assisted Non-Orthogonal Multiple Access
Gang Yang, Xinyue Xu and Ying-Chang Liang (University of Electronic Science and Technology of China, China)
3
Intelligent reflecting surface (IRS) is a new and disruptive technology to achieve spectrum-, energy, and cost- efficient wireless networks. In this paper, we consider an IRS-assisted non-orthogonal-multiple-access (NOMA) system in which a base station (BS) transmits superposed downlink signals to multiple users. A combined-channel-strength (CCS) based user ordering scheme is first proposed. In order to optimize the rate performance and ensure user fairness, we further maximize the minimum decoding signal- to-interference-plus-noise-ratio (i.e., equivalently the rate) of all users, by jointly optimizing the power allocation at the BS and the phase shifts at the IRS. However, the formulated problem is non-convex and difficult to be solved optimally. By leveraging the block coordinate descent and semidefinite relaxation techniques, an efficient algorithm is then proposed to obtain a suboptimal solution. Simulation results show that the IRS-assisted downlink NOMA system can enhance the rate performance significantly, compared to traditional NOMA without IRS and traditional orthogonal multiple access with/without IRS, and the rate degradation due to the IRS's finite phase resolution is slight.
Bit Error Probability for Asynchronous Channel Access with Interference Cancellation and FBMC
Maxim Penner and Sami Akın (Leibniz Universität Hannover, Germany); Martin Fuhrwerk (Baker Hughes, Germany); Jürgen Peissig (Leibniz Universität Hannover, Germany)
2
Future wireless communication standards will include technologies to provide access to an increasing number of users, for example Machine-Type Communication (MTC), which is expected to interconnect billions of devices. Managing such a large number of network participants in centrally coordinated systems suffers from large controlling overhead as each device needs to be assigned resources and maintain synchronization. In this paper, we investigate systems with asynchronous channel access, in which signals are transmitted without prior resource coordination. In such uncoordinated networks, signal collisions are inevitable and pose a major challenge for system design. We present a closed-form solution for the Bit Error Probability (BEP) of colliding signals modulated with Filter Bank Multicarrier (FBMC), a modern multicarrier scheme that allows a flexible signal design. We additionally derive a solution for the BEP when Successive Interference Cancellation (SIC) is applied, a scheme where successfully decoded signals are removed from a collision in order to improve decoding of other signals implicated in the collision. The results are valid for any numbers of colliding FBMC signals over a broad range of doubly-selective channel configurations. Furthermore, we provide an overview of when interference cancellation is beneficial depending on the power ratio between colliding signals and the selected channel models.
Full Duplex Based Digital Out-of-Band Interference Cancellation for Collocated Radios
Thomas Ranström (Swedish Defense Research Agency, Sweden); Erik Axell (Swedish Defence Research Agency, Sweden)
2
In this work, a novel out-of-band interference cancellation (OOBIC) method, based on a full duplex interference cancellation technique, is proposed. The aim of the OOBIC is to counteract the interference that may occur when collocated radios transmit and receive in closely located frequency bands. The main advantage of the method is that the cancellation can be performed directly on the data signal, with the desired signal present, without complex nonlinear modeling, and without additional synchronization between the collocated radios. The method is validated both analytically and through simulations, and is shown to successfully increase the signal quality in OOB interference situations where the signal otherwise would have been unrecoverable.
Adaptive Threshold Detection and ISI Mitigation in Mobile Molecular Communication
Amit Kumar Shrivastava and Debanjan Das (International Institute of Information Technology, Naya Raipur, India); Rajarshi Mahapatra (IIIT Naya Raipur, India)
2
Due to the dynamic nature of nanomachines and diffusion channel, detection is challenging in mobile molecular communication (MMC). In general, signal detection is performed on the number of received molecules with respect to a fixed threshold. However, in MMC number of received molecules varies in each bit interval, which makes detection very challenging if a fixed threshold is considered. In addition to this, the dynamic nature of nanomachines, communication channel impacted intersymbol interference (ISI), and makes it time-varying. In this work, we propose a detection technique with adaptive threshold for signal detection in MMC. The selection of adaptive threshold depends on the parameters such as the dynamic distance between nanomachines, diffusion coefficient etc. Detection using adaptive threshold improves the detection performance and also mitigates ISI manifold. In this paper, we use modified concentration shift keying (M-CSK) based modulation to release more amount of signaling molecules for bit-1 than bit-0. Received signal is reconstructed in each bit interval using the average distance variation in a bit interval and the reconstructed received signal is subtracted from the total received signal in subsequent bit duration. Detection threshold is calculated by applying maximum a posteriori (MAP) rule to reconstructed signals for the bit-1 and the bit-0 of previous bit interval. Performance of this detector is compared with an existing detection technique. Results reveal a better bit error rate (BER) performance in terms of parameters like coherence time of the channel (zero BER for coherence time of two bit durations), increasing diffusion coefficient and initial distance between nanomachines.
Session Chair
Sang-Woon Jeon (Hanyang University, Korea (South))
Session T1-S8
Low Latency Communications
Conference
4:00 PM
—
5:30 PM KST
Local
May 26 Tue, 12:00 AM
—
1:30 AM PDT
Cross-Link Interference Suppression By Orthogonal Projector For 5G Dynamic TDD URLLC Systems
Ali Esswie (Nokia Bell Labs, Denmark); Klaus Pedersen (Nokia - Bell Labs, Denmark)
1
Dynamic time division duplexing (TDD) is envisioned as a vital transmission technology of the 5G new radio, due to its reciprocal propagation characteristics. However, the potential cross-link interference (CLI) imposes a fundamental limitation against the feasibility of the ultra-reliable and low latency communications (URLLC) in dynamic-TDD systems. In this work, we propose a near-optimal and complexity-efficient CLI suppression scheme using orthogonal spatial projection, while the signaling overhead is limited to B-bit, over the back-haul links. Compared to the state-of-the-art dynamic-TDD studies, proposed solution offers a significant improvement of the URLLC outage latency, e.g., ~ —199% reduction, while boosting the achievable capacity per the URLLC packet by ~ +156%.
Robust Integration of Computation and Communication in B5G Cellular Internet of Things
Qiao Qi (ZheJiang University, China); Xiaoming Chen, Caijun Zhong and Zhaoyang Zhang (Zhejiang University, China)
0
In this paper, we investigate the issue of integrated computation and communication in beyond fifth-generation (B5G) cellular internet of things (IoT) networks with massive connectivity. By exploiting the open nature of wireless channels, a comprehensive deign framework integrating computation and communication over the same spectrum is first put forward for massive IoT. To achieve efficient integration of computation and communication under practical but adverse conditions, a robust algorithm is proposed by jointly optimizing transmit power and receive beamforming, with the goal of minimizing the computation error of computation signals while guaranteeing the requirement of communication signals. Finally, extensive simulations validate the robustness and effectiveness of the proposed algorithm for B5G cellular IoT.
Dynamic HARQ with Guaranteed Delay
Mahyar Shirvanimoghaddam (University of Sydney, Australia); Hossein Khayami (Sharif University of Technology, Iran); Yonghui Li and Branka Vucetic (University of Sydney, Australia)
1
In this paper, a dynamic-hybrid automatic repeat request (D-HARQ) scheme with guaranteed delay performance is proposed. As opposed to the conventional HARQ that the maximum number of re-transmissions, L, is fixed, in the proposed scheme packets can be re-transmitted more times given that the previous packet was received with less than L re-transmissions. The dynamic of the proposed scheme is analyzed using the Markov model. For delay sensitive applications, the proposed scheme shows a superior performance in terms of packet error rate compared with the conventional HARQ and Fixed retransmission schemes when the channel state information is not available at the transmitter. We further show that D-HARQ achieves a higher throughput compared with the conventional HARQ and fixed re-transmission schemes under the same reliability constraint.
On Error Rate Analysis for URLLC over Multiple Fading Channels
Jinho Choi (Deakin University, Australia)
0
In this paper, we study ultra-reliable and low-latency communication (URLLC) under fading using repetition diversity through multiple orthogonal radio resource blocks (e.g., multiple frequency or time bins). We investigate an approach to find an upper-bound on the packet error rate when a finite-length code is used. From simulation results, we find that the bound is reasonably tight for wide ranges of signal-to-noise ratio (SNR) and the number of multiple bins. Thus, the derived bound can be used to determine key parameters to guarantee the performance of URLLC in terms of the packet error rate.
Fast Cross Layer Authentication Scheme For Dynamic Wireless Network
ZhiYuan Zhang, Na Li, Shida Xia and Xiaofeng Tao (Beijing University of Posts and Telecommunications, China)
0
Current physical layer authentication (PLA) mechanisms are mostly designed for static communications, and the accuracy degrades significantly when used in dynamic scenarios, where the network environments and wireless channels change frequently. To improve the authentication performance, it is necessary to update the hypothesis test models and parameters in time, which however brings high computational complexity and authentication delay. In this paper, we propose a lightweight cross-layer authentication scheme for dynamic communication scenarios. We use multiple characteristics based PLA to guarantee the reliability and accuracy of authentication, and propose an upper layer assisted method to ensure the performance stability. Specifically, upper layer authentication (ULA) helps to update the PLA models and parameters. By properly choosing the period of triggering ULA, a balance between complexity and performance can be easily obtained. Simulation results show that our scheme can achieve pretty good authentication performance with reduced complexity.
Session Chair
Jemin Lee (Daegu Gyeongbuk Institute of Science and Technology (DGIST), Korea (South))
Session T1-S9
Deep Learning for Wireless Communications 2
Conference
4:00 PM
—
5:30 PM KST
Local
May 26 Tue, 12:00 AM
—
1:30 AM PDT
Deep Learning Based Fast Downlink Channel Reconstruction For FDD Massive MIMO Systems
Mengyuan Li and Yu Han (Southeast University, China); Chao-Kai Wen (National Sun Yat-sen University, Taiwan); Xiao Li and Shi Jin (Southeast University, China)
1
The spatial reciprocity enables the downlink channel reconstruction in frequency division duplex (FDD) massive multi-input multi-output (MIMO) systems by obtaining the frequency-independent parameters in the uplink. However, the algorithms to estimate these parameters are typically complex and time-consuming. In this paper, we regard the channel as an image and utilize you only look once (YOLO), an advanced deep learning- based object detection network, to locate the bright spots in the channel image, then the frequency-independent parameters can be estimated rapidly. Superior to the traditional algorithm that iteratively extracts the paths, YOLO can detect all the path simultaneously. Experimental results show that YOLO can greatly deplete the running time to obtain the frequency-independent parameters and reconstruct the FDD massive MIMO downlink channel with satisfactory accuracy.
Deep Learning based Low-Rank Channel Recovery for Hybrid Beamforming in Millimeter-Wave Massive MIMO
Nuan Song, Chenhui Ye and Xiaofeng Hu (Nokia Bell Labs China, China); Tao Yang (Nokia Shanghai Bell, China)
4
Massive Multiple Input Multiple Output (MIMO) at millimeter wave bands is able to boost the system throughput. A key challenge for the hybrid beam- forming design in massive MIMO systems is the acquisition of the full channel state information, since the number of radio frequency chains is much smaller than that of the antennas. Conventional methods require a longer measurement time, a large overhead, or costly signal processing efforts. Therefore, we propose an efficient and adaptable deep neural network based low-rank channel recovery scheme for a hybrid array based massive MIMO system. The proposed neural network architecture includes a common feature extraction module and the adaptable recovery module. The feature extraction, built on the convolutional neural network with residual learning functionality, can efficiently learn the essential features from the low-rank measurements. The adaptable key recovery module maps the essential features to the full channel information. The proposed architecture enables an efficient learning procedure and can be easily adapted to different cases. Simulation results are carried out and compared with existing solutions, showing the potential of applying deep learning concepts in millimeter wave massive MIMO systems.
IMNet: A Learning Based Detector for Index Modulation Aided MIMO-OFDM Systems
Jinxue Liu and Hancheng Lu (University of Science and Technology of China, China)
0
Index modulation (IM) brings the reduction of power consumption and complexity of transmitter to classical multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems. However, due to the introduction of IM, the complexity of the detector at receiver is greatly increased. Furthermore, the detector also requires the channel state information at receiver (CSIR), which leads to high system overhead. To tackle these challenges, in this paper, we introduce deep learning (DL) in designing a non-iterative detector. Specifically, based on the structural sparsity of the transmitted signal in IM aided MIMO-OFDM (IM-MIMO-OFDM) systems, we first formulate the detection process as a sparse reconstruction problem. Then, a DL based detector called IMNet, which combines two subnets with the traditional least square method, is designed to recover the transmitted signal. To the best of our knowledge, this is the first attempt that designs the DL based detector for IM-MIMO-OFDM systems. Finally, to verify the adaptability and robustness of IMNet, simulations are carried out with consideration of correlated MIMO channels and imperfect CSIR. The simulation results demonstrate that the proposed IMNet outperforms existing detectors in terms of bit error rate and computational complexity under various scenarios.
Blind Packet-Based Receiver Chain Optimization Using Machine Learning
Mohammed Radi (TU Dresden, Germany); Emil Matus and Gerhard P. Fettweis (Technische Universität Dresden, Germany)
3
The selection of the most appropriate equalization-detection-decoding algorithms in wireless receivers is a challenging task due to the diversity of application requirements, algorithm performance-complexity trade-offs, numerous transmission modes, and channel properties. Typically, the fixed receiver- chain is employed for specific application scenario that may support iterative processing for better adaptation to variable channel conditions. We propose a novel method for optimizing receiver efficiency in the sense of maximizing packet transmission reliability while minimizing receiver processing complexity. We achieve this by packet-wise dynamic selection of the least complex receiver that enables error-free packet reception out of set of available receivers. The scheme employs convolutional neural network (CNN) and supervised deep learning approach for packet classification and subsequent prediction of the optimum receiver using raw baseband signals. The proposed scheme aims to approach a packet error rate close to the rate of the most complex receiver architecture while using a combination of both low and high complexity architectures. This is achieved by employing the neural network based classifier to dynamically select packet-specific optimum architecture; i.e. instead of using the most complex receiver for all packets, the approach dynamically assigns the packet to the most appropriate receiver in terms of equalization-detection-decoding capability and the least possible complexity. We analyze the performance of the proposed scheme considering various channel scenarios. The system demonstrates excellent packet classification performance resulting in the significant performance increase and the reduction of the usage of the functional blocks that can go up to 96% of the time in different scenarios.
Neural Network MIMO Detection for Coded Wireless Communication with Impairments
Omer Sholev (Ben Gurion University, Israel); Haim H Permuter (Ben-Gurion University, Israel); Eilam Ben-Dror (Huawei Technologies ltd., Israel); Wenliang Liang (China)
0
In this paper, a neural network based MultipleInput-Multiple-Output (MIMO) algorithm is presented. The algorithm is specifically designed to be integrated in a coded MIMO-OFDM system, and is based upon projected gradient descent iterations. We combine our model as a part of a modern coded MIMO-OFDM system, and we compare its performance with common MIMO detectors on simulated data, as well as on field data. We also investigated our model's performance in the presence of several common communication impairments, and demonstrated empirically its robustness. We show empirically that a single trained model is suited for the detection of both coded and uncoded data, with or without impairments, and in the presence of a wide range of tested SNR levels.
Session Chair
Junil Choi (KAIST, Korea (South))