Main Conference
Track 1 – Phy & Fundamentals
Session T1-S11
Millimeter-Wave Systems 2
Conference
11:00 AM
—
12:30 PM KST
Local
May 26 Tue, 10:00 PM
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11:30 PM EDT
Hybrid Multi-User Precoding for mmWave Massive MIMO in Frequency-Selective Channels
Shijian Gao (Colorado State University, USA); Xiang Cheng (Peking University, China); Liuqing Yang (Colorado State University, USA)
2
This paper investigates the transceiver design for downlink hybrid mmWave multi-user multi-carrier massive MIMO systems. In order to balance the processing complexity and the design flexibility, we adopt a prevalent hybrid precoding technique named hybrid block diagonalization (HBD) for downlink multi-user transmission. Aimed at maximizing the end-to- end mutual information (EEMI), a novel virtual EEMI assisted two-stage HBD scheme is judiciously devised. Apart from a low implementing complexity, the developed scheme is a more generic HBD solution, as it not only takes the frequency selectivity into account, but also removes the reliance on the high-resolution analog network. Simulations show that, even when applied with an inferior hardware configuration, the proposed HBD could still remarkably outperform its counterparts in terms of the EEMI performance at different levels of channel sparsity.
Secrecy Rate Analysis of mmWave MISO Ad Hoc Networks with Null Space Precoding
Ahmed F Darwesh and Abraham O Fapojuwo (University of Calgary, Canada)
0
Secure communication in the millimeter wave (mmWave) network is an important issue in the next-generation wireless network due to the massive improvement in the eavesdroppers' ability. This paper studies the secrecy rate performance of a mmWave multi-input single-output (MISO) ad hoc network in the presence of colluding eavesdroppers. Firstly, to enhance the average achievable secrecy rate, an artificial noise (AN) transmission with null space linear precoder (Tx-AN/LP) is applied, taking into consideration the effect of blockage and Nakagami fading. Consequently, the tools of stochastic geometry are used to derive the mathematical expression of the average achievable secrecy rate for mmWave MISO ad hoc network with Tx-AN/LP technique. Numerical and simulation results show that, using the Tx-AN/LP technique achieves more than three-fold improvement in the average secrecy rate over that without in the high power transmit regime (> 15 dBm). Moreover, the effect of increasing the colluding eavesdroppers' intensity without using the Tx-AN/LP technique is studied which provides a high deterioration in the average secrecy rate. Conversely, when the Tx-AN/LP technique is applied, increasing the colluding eavesdroppers' intensity has no negative impact on the secrecy rate. Furthermore, the proper power allocation between the message and AN signals which maximizes the average secrecy rate is computed. The results therefore show that the Tx-AN/LP technique is a useful technique to enhance the secrecy performance of mmWave MISO ad hoc network in the presence of colluding eavesdroppers.
SINR Coverage Analysis of Dense HetNets Over Fox's H-Fading Channels
Imene Trigui (University of Toronto, Canada); Sofiene Affes (INRS-EMT, Canada); Marco Di Renzo (Paris-Saclay University / CNRS, France); Dushantha Nalin K. Jayakody (National Research Tomsk Polytechnic University & Sri Lanka Technological Campus, Russia)
0
This paper embodies the Fox's H-transform theory into a unifying modeling and analysis of HetNets. The proposed framework has the potential, due to the Fox's H-functions versatility, of significantly simplifying the cumbersome analysis and representation of cellular coverage, while subsuming those previously derived for all known simple and composite fading models. The paper reveals important insights into the practice of densification in conjunction with signal-to-noise plus interference (SINR) thresholds and path-loss models.
Coverage Analysis of Relay Assisted Millimeter Wave Cellular Networks with Spatial Correlation
Simin Xu (Australian National University, Australia); Nan Yang (The Australian National University, Australia); Biao He (MediaTek USA Inc., USA); Hamid Jafarkhani (University of California, Irvine, USA)
0
We propose a novel analytical framework for evaluating the coverage performance of a millimeter wave (mmWave) cellular network where idle user equipments (UEs) act as relays. In this network, the base station (BS) adopts either the direct mode to transmit to the destination UE, or the relay mode if the direct mode fails, where the BS transmits to the relay UE and then the relay UE transmits to the destination UE. To address the drastic rotational movements of destination UEs in practice, we propose to adopt selection combining at destination UEs. New expression is derived for the signal-to-interference-plus- noise ratio (SINR) coverage probability of the network. Using numerical results, we first demonstrate the accuracy of our new expression. Then we show that ignoring spatial correlation, which has been commonly adopted in the literature, leads to severe overestimation of the SINR coverage probability. Furthermore, we show that introducing relays into a mmWave cellular network vastly improves the coverage performance. In addition, we show that the optimal BS density maximizing the SINR coverage probability can be determined by using our analysis.
Performance Analysis of Opportunistic Millimeter Wave Cloud-RAN with Nakagami-Blockage Channels
Behrouz Maham (Nazarbayev University, Kazakhstan)
1
In this paper, we consider an uplink Cloud Radio Access Network (RAN) transmission from a user served by multiple remote radio heads (RRHs) which are connected to each other via base band unit (BBU) pool which form a centralized processing. We assume opportunistic detection in which the best RRH is selected at a time to transfer the received message to BBU pool. In this case, we can achieve the diversity gain by choosing the proper RRH and reduce fronthaul traffic by occupying a single link. As another enabling technology for 5G and Beyond, we consider mmWave communications. Since LOS/NLOS components are essential in modeling mmWave bands, we use Nakagami-m channels. In addition, for blockage effect of mmWave bands, we assume random blockage model. For performance analysis, closed form expressions for outage probability and ergodic capacity are derived. Furthermore the analytical results are confirmed by comparing them with simulation results. It is shown that opportunistic scheme outperforms maximum ratio beamforming in which all RRHs are contributing in detection of the mobile user signal.
Session Chair
Jiho Song (University of Ulsan, Korea (South))
Session T1-S12
Multi-Antenna System
Conference
11:00 AM
—
12:30 PM KST
Local
May 26 Tue, 10:00 PM
—
11:30 PM EDT
Time Switching Protocol for Multi-Antenna SWIPT Systems
Seowoo Kang (Korea University, Korea (South)); Hoon Lee (Pukyong National University, Korea (South)); Sangwon Hwang and Inkyu Lee (Korea University, Korea (South))
0
In this paper, we investigate simultaneous wireless information and power transfer (SWIPT) where a multi-antenna transmitter conveys information and energy simultaneously to a multi-antenna receiver equipped with time switching (TS) circuits for an energy harvesting (EH) mode and an information decoding (ID) mode. In contrast with conventional uniform TS (UTS) structure where all the receive antennas at the receiver apply a single TS circuit, to improve the SWIPT performance, we suggest a general dynamic TS (DTS) receiver architecture which consists of an individual TS circuit for each antenna. We aim to analyze the achievable rate-energy (R-E) tradeoff of the DTS system by jointly optimizing the covariance matrices at the transmitter and the time durations for the EH and the ID modes of the receive antennas. To determine the boundary points of the R-E region, we suggest the globally optimal algorithm for the rate maximization problem via convex optimization techniques. Numerical examples verify the efficacy of the proposed DTS over conventional UTS methods.
Adaptive Antenna Array with weight and antenna space control
Kenta Umebayashi and Yoshimasa Kimoto (Tokyo University of Agriculture and Technology, Japan); Antti Tölli (University of Oulu, Finland)
2
A typical adaptive antenna array based on weight control (AAA-W) with M antennas can suppress M — 1 interference signals. In this paper, we propose AAA based on not only weight but also antenna spacing control (AAA-WS) and investigate the basic performance of AAA-WS under the line-of- sight. At first, we show that AAA-WS with two antennas (M =3D 2) can sufficiently suppress more than two interference signals while the desired signal is enhanced. The inherent interference suppression capability of AAA-WS can be determined by the maximum antenna spacing and this fact is exhibited by analysis and Monte Carlo simulations. In addition, we will show that AAA-WS with two antennas can outperform AAA-W with more than two antennas. It is notable that the additional gain in AAA-WS compared to AAA-W can be around 18 dB.
Channel Correlation Cancelation-Based Hybrid Beamforming for Massive Multiuser MIMO Systems
Xinbo Wang, Li Guo, Chao Dong and Xidong Mu (Beijing University of Posts and Telecommunications, China)
3
In millimeter-wave (mmWave) communication systems, hybrid beamforming is regarded as an effective way to increase the spectral efficiency of the massive multiple-input multiple-output (MIMO) system. Assuming perfect channel state information (CSI) is known at the transmitter, we focus on a downlink massive multi-user MIMO system which supports multi-stream per user. In the above scenario, we investigate the hybrid beamforming problem with strong correlation between users’ channels, where the existing schemes have performance loss. To tackle this problem, this paper proposes the channel correlation cancelation-based hybrid beamforming (CCCHB) algorithm which considers the correlation between channels and decomposes the optimization of overall spectrum efficiency of the users to a series of sub-rate optimization problems. And the block diagonalization (BD) technique is used in the equivalent channel to eliminate inter-user interference. Simulation results illustrate that the performance of the proposed scheme outperforms the existing algorithm, especially significant when there exists high correlation between users’ channels.
IRS-Enhanced Wideband MU-MISO-OFDM Communication Systems
Hongyu Li, Rang Liu, Ming Li, Qian Liu and Xuanheng Li (Dalian University of Technology, China)
1
Intelligent reflecting surface (IRS) is considered as an enabling technology for future wireless communication systems since it can intelligently change the wireless environment to improve the communication performance. In this paper, an IRS-enhanced wideband multiuser multi-input single-output orthogonal frequency division multiplexing (MU-MISO-OFDM) system is investigated. We aim to jointly design the transmit beamformer and the reflection of IRS to maximize the average sum-rate over all subcarriers. With the aid of the relationship between sum-rate maximization and mean square error (MSE) minimization, an efficient joint beamformer and IRS design algorithm is developed. Simulation results illustrate that the proposed algorithm can offer significant average sum-rate enhancement, which confirms the effectiveness of the use of the IRS for wideband wireless communication systems.
MF-based Dimension Reduction Signal Compression for Fronthaul-Constrained Distributed MIMO C-RAN
Fred Wiffen and Angela Doufexi (University of Bristol, United Kingdom (Great Britain)); Mohammud Z Bocus (Toshiba Research Europe Ltd, United Kingdom (Great Britain)); Woon Hau Chin (Toshiba Research Europe Limited, United Kingdom (Great Britain))
0
In this work we propose a fronthaul compression scheme for distributed MIMO systems with multi-antenna receivers, in which, prior to signal quantisation, dimension reduction is performed at each receiver by matched filtering the received signal with a subset of the local user channel vectors. By choosing these matched filter vectors based on global channel information, a high proportion of the potential capacity may be captured by a small number of signal components, which can then be compressed efficiently using local signal compression. We outline a greedy algorithm for selecting the matched filtering vectors for each receiver, and a local transform coding approach for quantising them, giving expressions for the resulting system sum and user capacities. We then show that the scheme is easily modified to account for imperfect CSI at the receivers. Numerical results show that with a low signal dimension the scheme is able to operate very close to the cut-set bound in the fronthaul-limited regime, and demonstrates significant improvements in rate-capacity trade-off versus local compression at all operating points, particularly at high SNR.
Session Chair
Daeyoung Park (Inha University, Korea (South))
Session T1-S13
Information Theory and Capacity
Conference
11:00 AM
—
12:30 PM KST
Local
May 26 Tue, 10:00 PM
—
11:30 PM EDT
How Does Channel Coding Affect the Design of Uplink SCMA Multidimensional Constellations?
Monirosharieh Vameghestahbanati, Ian D. Marsland, Ramy Gohary and Halim Yanikomeroglu (Carleton University, Canada); Javad Abdoli (Huawei Technologies Canada Co., Ltd., Canada)
0
Sparse code multiple access (SCMA) is a potential non-orthogonal multiple access candidate for future wireless systems. The key performance indicators (KPIs) of uplink SCMA multidimensional constellations (MdCs) that should be considered in their design process have recently been identified in conjunction with the LTE turbo code for different channel scenarios. However, it is questionable whether the same KPIs are applicable to designing MdCs when a different error correcting code is employed. In this paper, we investigate the effect of the high-rate and low-rate 5G low density parity check (LDPC) codes on determining KPIs in designing MdCs for uplink SCMA systems under various channel scenarios. Through simulations, we show that similar results to the LTE turbo coded case occur in the presence of 5G LDPC code, with one notable exception over one specific scenario. The exception is in the performance of one MdC, which has a low number of distinct points; its performance is significantly worse than predicted by the KPIs when the low- rate 5G LDPC code is employed. This phenomenon happens due to the inherent structure of the 5G LDPC code, in which we propose a pseudorandom interleaver to rectify the problem.
Capacity Analysis of Time-Indexed Media-based Modulation
Bharath Shamasundar (Indian Institute of Science, India); Lakshmi Narasimhan Theagarajan (Indian Institute of Technology, Palakkad, India); A. Chockalingam (Indian Institute of Science, India)
0
Time-indexed media-based modulation (TI-MBM) is an index modulation scheme where time slots in a transmission frame are indexed to convey additional information bits in media-based modulation (MBM). It was shown in the literature that, in frequency selective fading channels with inter-symbol interference, TI-MBM with cyclic-prefixed single-carrier (CPSC) scheme can achieve better transmission rates, bit error performance, and multipath diversity gain compared to conventional MBM. In this paper, we analyze the capacity of TI-MBM with CPSC, which has not been reported before. We show that, for a given channel matrix, selecting the index of the activated time slots and RF mirrors according to uniform distribution is suboptimal. We derive the probabilities with which time slots and RF mirrors in TI-MBM can be activated such that the achievable transmission rate is maximized. Further, we prove that the transmit symbols from a Gaussian mixture distribution, whose mixture weights are chosen to be the product of these probabilities, can achieve capacity.
Average Secrecy Capacity of SIMO κ-µ Shadowed Fading Channels with Multiple Eavesdroppers
Jiangfeng Sun and Hongxia Bie (Beijing University of Posts and Telecommunications, China); Xingwang Li (Henan Polytechnic University, China); Khaled M. Rabie and Rupak Kharel (Manchester Metropolitan University, United Kingdom (Great Britain))
0
In this paper, we analyze the security capability of single-input multiple-output wireless transmission systems over κ-µ shadowed fading channels in the presence of multiple eavesdroppers. Our security analysis relies on an important standard, i.e., average secrecy capacity which is more difficult and suitable for analyzing active eavesdropping scenario than secure outage probability and probability of strictly positive secrecy capacity. The novel expression of average secrecy capacity over κ-µ shadowed fading channels with multiple eavesdroppers is deduced. The results of Monte Carlo simulation fully prove the correctness of our theoretical derivation. Through the obtained results, we observe that large antenna quantity in the highest signal-to-noise ratio regime, small number of the eavesdroppers, and small signal-to-noise-ratio of eavesdropping link will enhance confidentiality of the system under consideration.
LDPC-Staircase Codes for Soft Decision Decoding
Viduranga Wijekoon, Emanuele Viterbo and Yi Hong (Monash University, Australia)
1
Staircase codes, a class of product-like codes, have been demonstrated to perform exceptionally well in optical transmission systems. Although they are predominantly used with BCH component codes and hard decision decoding, soft decision decoding has also been recently attempted, with BCH and polar code based staircase codes. We consider using LDPC codes as the component code of soft decoded staircase codes. Results demonstrate that these codes offer very good performance, with gains in the range of 0.5-1dB over soft decoded BCH-staircase codes, at a BER of 10-8 . These can be further improved through the novel bit-flipping scheme we propose.
On the Construction of \(G_N\)-coset Codes for Parallel Decoding
Xianbin Wang, Huazi Zhang, Rong Li and Jiajie Tong (Huawei Technologies, Co. Ltd., China); Yiqun Ge (Huawei Technologies Canada Inc., Canada); Jun Wang (Huawei Technologies Co. Ltd, China)
0
In this work, we propose a type of GN -coset codes for parallel decoding. The parallel decoder exploits two equivalent decoding graphs of GN -coset codes. For each decoding graph, the inner code part is composed of independent component codes to be decoded in parallel. The extrinsic information of the code bits is obtained and iteratively exchanged between the two graphs until convergence. Accordingly, we explore a heuristic and flexible code construction method (information set selection) for various information lengths and coding rates. Compared to the previous successive cancellation algorithm, the parallel decoder avoids the serial outer code processing and enjoys a higher degree of parallelism. Furthermore, a flexible trade-off between performance and decoding latency can be achieved with three types of component decoders. Simulation results demonstrate that the proposed encoder-decoder framework achieves comparable error correction performance to polar codes with a much lower decoding latency.
Session Chair
Sang-Woon Jeon (Hanyang University, Korea (South))
Session T1-S14
Signal Processing for Millimeter-Wave and THz Communications
Conference
2:00 PM
—
3:30 PM KST
Local
May 27 Wed, 1:00 AM
—
2:30 AM EDT
Measurement of 2x2 LoS Terahertz MIMO Channel
Suresh Singh, Thanh Le and Ha Tran (Portland State University, USA)
1
This paper examines the performance of a 2x2 Line of Sight (LoS) Multiple Input Multiple Output (MIMO) channel at three terahertz frequencies - 340 GHz, 410 Ghz, and 460 GHz. While theoretical models predict very high channel capacities, we observe lower capacity which is explained by asymmetric transmit-to-receive signal strengths as well as due to signal attenuation over longer distances. Overall, however, we note that at 460 Ghz, channel capacity of higher than 12 bps/hz is possible even at sub-optimal inter-antenna spacings (for different distances). An important observation is also that we need to maintain appropriate receive signal levels at receive antennas in order to improve capacity.
Precoding with the Assistance of Attitude Information in Millimeter Wave MIMO System
Shiyu Zhou (University of Science and Technology of China, China); Chen Li (University of Science And Technology of China, China); Weidong Wang (University of Science and Technology of China, China)
1
Digital beamforming (DBF) is considered as an efficient method to overcome the high propagation loss of millimeter wave (mmWave) communication, but the acquisition of channel state information (CSI) brings huge training overhead, especially in high mobility scenarios. To tackle this challenge, we consider using attitude information from motion sensors to reduce the training overhead of DBF in this paper. We first analyze the characteristics of mmWave uplink channel when the attitude of user equipment (UE) rotates, and it shows that only the precoder needs to be redesigned after the rotation. Therefore, we develop a novel attitude information aided precoding algorithm, which approaches the performance of conventional singular value decomposition (SVD) algorithm. The proposed algorithm reduces the channel estimation and feedback overhead significantly compared to the conventional one. Finally, the simulation results show that the proposed algorithms allow mmWave systems to approach their performance limits.
A Novel 3D Space-Time-Frequency Non-Stationary Channel Model for 6G THz Indoor Communication Systems
Jun Wang (Southeast University, China); Cheng-Xiang Wang (Southeast University & Heriot-Watt University, China); Jie Huang and Haiming Wang (Southeast University, China)
0
Terahertz (THz) communication is now being considered as one of possible technologies for the sixth generation (6G) communication systems. In this paper, a novel three-dimensional (3D) space-time-frequency non-stationary massive multiple-input multiple-output (MIMO) channel model for 6G THz indoor communication systems is proposed. In this geometry-based stochastic model (GBSM), the initialization and evolution of parameters in time, space, and frequency domains are developed to generate the complete channel transfer function (CTF). Based on the proposed model, the correlation functions including time auto-correlation function (ACF), spatial cross-correlation function (CCF), and frequency correlation function (FCF) are investigated. The results show that the statistical properties of the simulation model match well with those of the theoretical model. The stationary intervals at different frequencies are simulated. The non-stationarity in time, space, and frequency domains is verified by theoretical derivations and simulations.
Measurement-based Characterization of 73GHz Propagation Channels in Scatterer-rich Environments
Zeyu Huang, José Rodríguez-Piñeiro, Xuefeng Yin and Yejian Lv (Tongji University, China); Haowen Wang (Shanghai Research Center for Wireless Communications, China)
0
The use of millimeter-wave bands is undoubtedly one of the key technologies considered by the Fifth Generation Communication Systems (5G). However, the performance of millimeter-wave communication systems can be severely affected by the propagation environment. In this paper, the propagation channel characteristics in scatterer-rich environments for the 73 GHz millimeter-wave band is studied based on measurements. The channel characteristics under study include the propagation loss and its variation depending on the elements around the receiver, the channel dispersion in delay represented by the Root- Mean-Square (RMS) channel delay spread and the multipath behavior in the form of multi-path component (MPC) clusters. The proposed models for the mentioned channel characteristics are of great value as reference for millimeter-wave 5G deployments.
Frequency-Selective Analog Beam Probing for Millimeter Wave Communication Systems
Christoph Jans (Technische Universität Dresden, Germany); Xiaohang Song (Technical University of Dresden, Germany); Wolfgang Rave (Dresden University of Technology, Germany); Gerhard P. Fettweis (Technische Universität Dresden, Germany)
3
This work focuses on the initial beam acquisition/alignment of millimeter wave (mmWave) communication systems. To detect the angle of arrival (AoA) and/or angle of departure (AoD), we propose a training protocol which probes all beamformers from a given codebook simultaneously by exploiting the sparse nature of mmWave channels. By applying a frequency- selective beam probing network, we can map each beamformer from the codebook to different frequencies and a spectral analysis at the receiver allows us to deduce favorable beamformers or AoDs. For practical reasons, we elaborate this idea of steering direction to frequency mapping for an orthogonal frequency division multiplexing (OFDM) communication system, i.e., we map each beamformer to specific pilot subcarriers. Under two different hardware designs, we investigate the feasibility of building such beamformer to frequency mappings for one additional radio frequency (RF) chain next to an existing OFDM communication system. We show that parallel beam training is able to achieve better effective transmission rates than exhaustive search in fasttime varying environments due to high temporal efficiency. This is crucial for mmWave communication systems which have access to large beamforming codebooks but suffer from short coherence times due to mobility and high spatial resolution.
Session Chair
Namyoon Lee (POSTECH, Korea (South))
Session T1-S15
Networking Application
Conference
2:00 PM
—
3:30 PM KST
Local
May 27 Wed, 1:00 AM
—
2:30 AM EDT
Practical Framework for Beam Feature-based Physical Layer Identification in 802.11 ad/ay Networks
Shreya Gupta (University at Buffalo, USA); Zhi Sun (State University of New York at Buffalo, USA); Pu Wang (University of North Carolina at Charlotte, USA); Arupjyoti (Arup) Bhuyan (INL, USA)
0
The millimeter wave (mmWave) technologies can significantly increase the throughput and user capacity in the future wireless networks. In term of device authentication, due to the usage of highly directional communication link, new physical layer identification (PLI) mechanism based on the spatial-temporal beam features becomes available. However, it is not known how to implement the new PLI mechanism using commodity devices in multiple client scenario in wireless networks. To this end, this paper presents a practical operational framework for the new beam feature-based PLI that is compatible with 802.11ad/ay standards. The low cost of these commodity devices leads to much wider beams, multiple main lobes, and high side lobes which in turn results in frequent sector level sweep (SLS) even for a minimal level of the transmitter-receiver misalignment. The high mobility sensitivity also triggers SLS. The key idea is to utilize the mobility of the mmWave device to collect enough measurements, the beam pattern feature values, from different observation angles where the beam features are extracted. This mobility effect takes advantage of the rich spatial-temporal information of the feature to prevent the system from spoofing. We also propose a novel feature database refinement algorithm to strengthen the database against false accept/reject rates and increase the identification accuracy. The algorithm filters the noisy data collected in the presence of multiple-clients. The proposed operational framework is implemented in commodity 802.11ad/ay devices. We show that the proposed scheme can reach near 100% accuracy even with a minimal feature vector database in real-time scenarios. 1
Caching and Pricing based on Blockchain in a Cache-delivery Market
Yuanzhuo Lin (Beijing University of Posts and Telecommunications, China); Hui Tian (Beijng university of posts and telecommunications, China); Jiazhi Ren and Shaoshuai Fan (Beijing University of Posts and Telecommunications, China)
0
The cache-delivery market is generally composed of Content Provider (CP), users, and Mobile Network Operator (MNO) equipped with Base Stations (BSs). In order to deal with the dishonest problems of different parties, we build a caching- chain network based on blockchain. This network is a pure peer-to-peer system, which allows file acquisition transactions without going through a centralized issuer or controller, but attains a reliable and tamper-proof value transfer. The utilization of smart contracts protects the interests of all parties in the untrusted caching market. By reasonably distributing the reward of generating new blocks, we can motivate the MNO to allocate more resources for offloading the traffic of the CP. In addition, we use the linear regression model to predict user mobility and design the cache placement policy accordingly. Furthermore, we compare the performance of three caching algorithms through simulation. And the simulation results show that an appropriate choice of parameters can raise the CP's profit.
Network Formation Model of Bio-nanomachines Based on Directed Migration and Adhesion
Kazuki Yonekura, Tadashi Nakano, Yutaka Okaie, Takahiro Hara and Kaname Harumoto (Osaka University, Japan)
0
A bio-nanomachine network is useful in diverse applications of molecular communication. In this paper, we develop a network formation model of bio-nanomachines based on how vascular endothelial cells form a blood vessel-like structure. In our model, bio-nanomachines migrate toward each other using attractant molecules. When two bio-nanomachines move close to each other, they adhere to form a physical connection or a link between them. In this way, a group of bio-nanomachines forms a network collectively. We perform computer simulations using the model to identify critical parameter values at which a large- scale bio-nanomachine network emerges. The model developed in this paper helps us design synthetic communication networks of bio-nanomachines.
Optimizing Caching Policy and Bandwidth Allocation Towards User Fairness
Pengyu Cong and Chengjian Sun (Beihang University, China); Dong Liu (University of Southampton, United Kingdom (Great Britain)); Chenyang Yang (Beihang University, China)
0
User fairness is an important metric for cellular systems. It has been widely considered for wireless transmission when optimizing radio resource allocation but rarely considered for femto-caching. In this paper, we optimize caching and bandwidth allocation policies to improve long-term user fairness during content placement and content delivery by harnessing heterogeneous user preference. To this end, we maximize the minimal average data rate, where the average is taken over large-and small-scale channel gains as well as individual user requests. This gives rise to a complicated two-timescale optimization problem involving functional optimization. The objective function of the problem does not have closed-form expression due to unknown user preference and channel distributions, and the "variables" to be optimized include a function. To solve such a challenging problem, we first optimize bandwidth allocation policy given arbitrary caching policy, user locations and user requests, whose structure can be found. We next optimize the caching policy given the optimized bandwidth allocation policy. To handle the difficulty of unknown distributions, we resort to stochastic optimization. Simulation results show that optimizing caching policy exploiting user preference can support much higher minimal average rate than optimizing caching policy based on content popularity when user preferences are less similar. Besides, better user fairness can be achieved by optimizing caching policy than by optimizing bandwidth allocation.
Clustering-based Scenario-Aware LTE Grant Prediction
Peter Brand, Muhammad Sabih and Joachim Falk (Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany); Jonathan Ah Sue (Intel Deutschland Gmbh, Germany); Jürgen Teich (Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany)
1
Reducing the energy consumption of mobile phones is a crucial design goal for cellular modem solutions for LTE and 5G standards. Recent approaches for dynamic power management incorporate traffic prediction to power down components of the modem as often as possible. These predictive approaches have been shown to still provide substantial energy savings, even if trained purely on-line. However, a higher prediction accuracy could be achieved when performing predictor training off-line. Additionally, having pre-trained predictors opens up the ability to successfully employ predictive techniques also in less favorable situations such as short intervals of stable traffic patterns. For this purpose, we introduce a notion of similarity, based on which a clustering is performed to identify similar traffic patterns. For each resulting cluster, i.e., an identified traffic scenario, one predictor is designed and trained off-line. At run time, the system selects the pre-trained predictor with the lowest average shortterm false negative rate allowing for energy-efficient and highly accurate on-line prediction. Through experiments, it is shown that the presented mixed static/dynamic approach is able to improve the prediction accuracy and energy savings compared to a state-of-the-art approach by factors of up to 2 and up to 1.9, respectively.
Session Chair
Yunquan Dong (Nanjing University of Information Science and Technology, China)
Session T1-S16
Resource Management and Optimization
Conference
2:00 PM
—
3:30 PM KST
Local
May 27 Wed, 1:00 AM
—
2:30 AM EDT
Joint Subcarrier and Power Allocation in D2D Communications Underlaying Cellular Networks
Caihong Kai, Yan Wu, Xinyue HU and Wei Huang (Hefei University of Technology, China)
1
For the high density of users and accompanying network service requirements in the cellular system, Device- to-Device (D2D) communication is a promising technology to cope with the increasing wireless traffic demands by reusing spectrum resources. In practice, the wireless signal is easy to be eavesdropped in D2D communications underlaying cellular networks, hence, ensuring a secure communication for cellular user equipments (CUEs) is an urgent and meaningful problem. In this paper, we propose a joint subcarrier and power allocation scheme for maximizing the sum data rate of D2D pairs, meanwhile protecting the CUEs against eavesdropping. Specifically, in the proposed scheme, we first quantify the security performance with the secrecy data rate, and obtain the closed- form expression for the optimal power allocation of CUEs and D2D pairs by tightening the quality of service (QoS) and secrecy rate requirement constraints of CUEs. Based on the obtained power allocation solution, by searching the optimal mapping relationship between CUEs and D2D pairs, we develop a subcarrier assignment strategy with the Hungarian algorithm to solve it, which can further enhance the sum data rate of D2D pairs. Simulation results demonstrate that the proposed scheme can significantly yield better performance than other schemes.
Cache Allocations for Consecutive Requests of Categorized Contents: Service Provider's Perspective
Minseok Choi (Jeju National University, USA); Andreas Molisch (University of Southern California, USA); Dong-Jun Han (KAIST, Korea (South)); Joongheon Kim (Korea University, Korea (South)); Jaekyun Moon (KAIST, Korea (South))
0
In wireless caching networks, a user generally has a concrete purpose of consuming contents in a certain preferred category, and requests more than one content in sequence. While most existing research on wireless content caching and delivery has focused only on one-shot requests, the popularity distribution of contents requested consecutively is definitely different from the one-shot request and has been not considered. Also, especially from the perspective of the service provider, it is advantageous for users to consume as many contents as possible. Thus, this paper proposes two cache allocation policies for categorized contents and consecutive user demands, which maximize 1) the cache hit rate and 2) the number of consecutive content consumption, respectively. Numerical results show how categorized contents and consecutive content requests have impacts on the cache allocation rule.
Multi-BS association and Pilot Allocation via Pursuit Learning
Naufan Raharya (University of Sydney, Australia); Wibowo Hardjawana (The University of Sydney, Australia); Obada Al-Khatib (University of Wollongong in Dubai, United Arab Emirates); Branka Vucetic (University of Sydney, Australia)
3
Pilot contamination (PC) interference causes an inaccurate user equipment's (UE) channel estimations and significant signal-to-interference ratio (SINR) degradations. To combat the PC effect and to maximize network spectral efficiency, pilot allocation can be combined with multi-Base Station (BS) association and then solved by using learning algorithm efficiently. However, current methods separate the pilot allocation and multi-BS association in the network. This results in suboptimal network spectral efficiency performance and can cause an outage where some UEs are not allocated pilots due to the limited availability of pilots at each BS. In this paper, we propose a multi-BS association and pilot allocation optimization via pursuit learning. Here, we design a parallel pursuit learning algorithm that decomposes the optimization function into smaller entities called learning automata. Each learning automaton computes the joint pilot allocation and BS association solution in parallel, by using the reward from the environment. Simulation results show that our scheme outperforms the existing schemes and does not cause an outage.
Group-based Multi-User Tracking in Mobile Millimeter-Wave Networks
Peng-Yu Lai (Novatek, Taiwan); Kuang-Hao (Stanley) Liu (National Cheng Kung University, Taiwan)
0
This work tackles the problem of user tracking in the multi-user scenario. User tracking is one of the key functional elements in millimeter wave (mmWave) communications that heavily rely on directional beamforming to overcome significant path loss. A naive strategy is to track users one by one but this not only introduces great overhead but also reduces the tracking update frequency when the number of users or antennas is large. In addition, user tracking based the angular information, namely angle of arrival (AoA)/angle of departure (AoD) often requires a good initial estimate and an iterative procedure to ensure the accuracy. Aiming to improve the tracking efficiency for multiple users, we propose to track multiple users simultaneously by partitioning users into groups based on the beamspace multi- input and multi-output (MIMO) channel representation. We formulate the joint user grouping and precoding as a mixed-integer nonlinear programming (MINP) problem and propose a low- complexity grouping algorithm. Simulation results demonstrate the significant improvement of the proposed multi-user tracking scheme over two existing approaches in terms of the spectral efficiency.
Spectrum Trading in Hybrid RF/FSO Communications: A Stackelberg Game Approach
Shenjie Huang (the Uinviersity of Edinburgh, United Kingdom (Great Britain)); Majid Safari (University of Edinburgh, United Kingdom (Great Britain))
3
In this work, a hybrid RF/FSO system employing a game theoretic spectrum trading process is investigated. Different from the hybrid systems in the literature, in the proposed system no RF spectrum is preallocated to the FSO link. Only under infrequent adverse weather conditions where the availability of the FSO link is severely impaired, the source borrows a portion of the licensed RF spectrum from the surrounding RF nodes. The competition among RF nodes is considered and the Stackelberg game is employed to model the spectrum trading game between the source of FSO link and the RF nodes. Using the leased spectrum, the source can establish a hybrid link containing not only the original FSO link but also an RF link to improve its throughout to the destination. Our performance analysis demonstrates that the proposed scheme improves the average capacity of the system in adverse weather conditions remarkably, thereby enhancing the availability of FSO communications.
Session Chair
Yo-Seb Jeon (POSTECH, Korea (South))
Session T1-S17
5G Wireless Communications
Conference
4:00 PM
—
5:30 PM KST
Local
May 27 Wed, 3:00 AM
—
4:30 AM EDT
Popularity Prediction with Federated Learning for Proactive Caching at Wireless Edge
Kaiqiang Qi and Chenyang Yang (Beihang University, China)
1
File popularity prediction plays an important role in proactive edge caching. The widely-used methods for popularity prediction are based on centralized learning, which needs to collect the request information and even more personal information from users, incurring the privacy-disclosure risk. In this paper, we propose a method of predicting file popularity with federated learning to address the privacy issue, where the request data of each user for each file is only employed for local training at each user. To facilitate the popularity prediction at the base station (BS) without information disclosure as well as the supervised training of a neural network at each user, we let each user upload a weighted sum of its own preference and file popularity to the BS. The neural network is employed to predict the weighted sum at each user by training with the user's historical request records for each file. The local models and uploaded results of the users are aggregated at the BS. We show the convergence of the proposed popularity prediction method with a synthetic dataset. We use simulation results with a real dataset to show that the proposed method performs closely to the centralized learning based method in terms of caching performance.
Ambient backscatters-friendly 5G networks: creating hot spots for tags and good spots for readers
Romain Fara (Orange Labs, France); Dinh-Thuy Phan-Huy (Orange-France Telecom, France); Marco Di Renzo (Paris-Saclay University / CNRS, France)
0
In this paper, we present an ambient backscatters- friendly 5G network that creates locations with large power (hot spots) for tags and good reception locations (quiet spots or coherent spots) for readers. Tags are devices that communicate information to readers by backscattering ambient radio- frequency signals. The massive multiple input multiple output (M-MIMO) antenna and beamforming capability of the 5G network is used as follows. In a first step, a training device (separate from tags and readers) is used to send pilots and train the 5G network to perform focusing and/or nulling onto marked locations. In a second step, tags and readers are positioned onto the marked locations. The robustness of M-MIMO beamforming to slight changes in the environment is exploited. Our initial simulation results, in a multipath propagation channel environment, show that creating a hot spot on a tag improves the tag-reader range however with a low probability of detection. Creating a hot spot on a tag and a good reception spot on a reader at the same time, improves the tag-reader range with 99% probability of detection. The study also shows that beamforming does not degrade the performance of a legacy 5G communication.
A Simple Cell-Specific Beamforming Technique for Multi-Antenna Wireless Communications
Maksym A. Girnyk (Ericsson Research, Sweden); Sven O. Petersson (Ericsson AB, Sweden)
1
Next-generation wireless communication systems will rely on multiple-antenna deployments enabling the beamforming functionality. In contrast to data transmission that benefits from user-specific beamforming (i.e., focusing the radiation at a particular user terminal), broadcasting of control information over a public channel requires cell-specific beamforming (i.e., cell-wide coverage). This paper presents a simple beamforming technique for cell-specific signaling for a four-port linear antenna array, based on exploiting two orthogonal polarizations and a maximum-ratio combining receiver. For instance, it is shown that by carefully tuning the excitation weights it is possible to design radiation patterns with any half-power beamwidth in the range from that of a narrow DFT beam to that of a single antenna element, while preserving the constant-modulus property of the excitation weights, thereby assuring excellent power utilization. The paper, furthermore, shows a direct connection between the underlying beamforming technique and the well-known concept of Alamouti space-time coding.
Wireless Fingerprint Aided Spectrum Sensing in Cellular Cognitive Radio Networks
Xin Wang and Siji Chen (Chongqing University of Posts and Telecommunications, China); Bin Shen (Chongqing University of Posts and Telecommunications (CQUPT), China); Taiping Cui (Chongqing University of Posts and Telecommunications, China)
1
Apart from the received signal energy, geo-location information plays an important role in ameliorating spectrum sensing performance. In this paper, a novel wireless fingerprint (WFP) aided spectrum sensing scheme is proposed. Assisted by the wireless fingerprint database (WFPD), secondary user equipments (SUEs) first identify their locations in the cellular cognitive radio network (CCRN) and then ascertain the white licensed spectrum for opportunistic access. The SUEs can pinpoint their geographical locations via time of arrival (TOA) estimate over the signals received from their surrounding base-stations (BSs). In view of the fact that locations of the primary user (PU) transmitters are either readily known or practically unavailable, the SUEs can search the WFPD or perform support vector machine (SVM) algorithm to determine the availability of the licensed spectrum, according to the locations of themselves and the PU transmitters (PUTs). In addition, to alleviate the deficiency of single SU based sensing, a joint prediction mechanism is proposed on the basis of cooperations of multiple SUs that are geographically nearby. Simulations verify that the proposed scheme achieves higher detection probability and demands less energy consumption than conventional spectrum sensing algorithms.
Session Chair
Jiho Song (University of Ulsan, Korea (South))
Session T1-S18
Signal Detection and Estimation
Conference
4:00 PM
—
5:30 PM KST
Local
May 27 Wed, 3:00 AM
—
4:30 AM EDT
Reconstruction Algorithm for Primary Channel Statistics Estimation Under Imperfect Spectrum Sensing
Ogeen Toma and Miguel López-Benítez (University of Liverpool, United Kingdom (Great Britain)); Dhaval Karshanbhai Patel (School of Engineering and Applied Science-Ahmedabad University, India); Kenta Umebayashi (Tokyo University of Agriculture and Technology, Japan)
0
Statistical information of primary channels has received considerable research interest in the recent years. This is due to the important role that these statistics play in improving the performance of Dynamic Spectrum Access (DSA)/Cognitive Radio (CR) systems. Although a DSA/CR system has no initial knowledge about the statistical information of the primary channels, these statistics can be estimated from the observations of spectrum sensing. However, spectrum sensing is not perfect in the real world and sensing errors are likely to occur during DSA/CR operation, which in turn leads to incorrect estimation of primary channel statistics as well. As a result, several attempts have arisen to reconstruct the estimated periods of the primary channel occupancy patterns which are affected by the sensing errors, in order to provide more accurate estimation for the statistical information. However, all the reconstruction methods available in the literature assume the perfect knowledge of the primary users' minimum occupancy time. In this context, this work proposes the first reconstruction method that does not require any prior knowledge about the primary channel activity and inactivity patterns while achieving almost the same performance achieved by the latest reconstruction methods available in the literature, making it significantly attractive and feasible in practical implementation scenarios.
Methods for Fast Estimation of Primary Activity Statistics in Cognitive Radio Systems
Miguel López-Benítez and Ogeen Toma (University of Liverpool, United Kingdom (Great Britain)); Dhaval Karshanbhai Patel (School of Engineering and Applied Science-Ahmedabad University, India); Kenta Umebayashi (Tokyo University of Agriculture and Technology, Japan)
0
Cognitive Radio (CR) is aimed at increasing the efficiency of spectrum utilisation by allowing unlicensed users to opportunistically access licensed spectrum bands during the inactivity periods of the licensed users. CR systems can benefit from an accurate knowledge of the spectrum occupancy patterns and their statistical properties. This statistical information can be obtained by periodically monitoring (sensing) the idle/busy state of the licensed channels. However, a reliable estimation of the primary activity statistics may require long observations times. This work proposes efficient methods to reduce the observation time required to produce a reliable estimation of the primary activity statistics. Furthermore, a method enabling CR users to quantify the accuracy of the estimated statistics is also proposed. Compared to other existing approaches, the proposed methods can provide accurate estimations of the primary activity statistics in significantly shorter observation times, thus allowing CR users to quickly adapt to new unknown operating channels.
Applying Deep Neural Networks for Duty Cycle Estimation
Ahmed Al-Tahmeesschi, Kenta Umebayashi and Hiroki Iwata (Tokyo University of Agriculture and Technology, Japan); Miguel López-Benítez (University of Liverpool, United Kingdom (Great Britain)); Janne Lehtomäki (University of Oulu, Finland)
0
A pro-active spectrum usage prediction is a key technique in decision making and spectrum selection for dynamic spectrum access systems. This work focuses on the estimation of the duty cycle (DC) metric to reflect spectrum usage. The prediction is formulated as a time-series regression problem. Deep neural networks (DNNs) is selected to obtain accurate predictions of channel usage. Namely, Multilayer perceptron (MLP), Long short term memory (LSTM) and a hybrid model based on convolutional neural network followed by an LSTM (CNN-LSTM) layer are selected. The hyper-parameters selection has been optimised utilising both grid search and multi-stage grid search. Moreover, in many cases, the spectrum usage is measured on a smaller time scale from the actual required one. Hence, down-sampling and averaging is required. Averaging operation results in flattening the data and losing essential features to assist DNN to predict the channel usage. We show what is the minimum required time resolution to have a pro-active prediction system. Then, we propose utilising feature engineering to improve prediction accuracy. All the proposed DNNs approaches are trained on real-life measurements. The experimental evaluation demonstrated a high potential of DNNs to learn from previous spectrum usage and accurately predict the spectrum usage. Moreover, adding input features significantly assists the system to achieve accurate predictions in a pro-active manner.
Channel Estimation for Intelligent Reflecting Surface Assisted Multiuser Communications
Zhaorui Wang (The Hong Kong polytechnic University); Liang Liu (The Hong Kong Polytechnic University, China); Shuguang Cui (The Chinese University of Hong Kong, Shenzhen & Shenzhen Research Institute of Big Data, China)
0
In the intelligent reflecting surface (IRS) assisted communication systems, the acquisition of channel state information (CSI) is a crucial impediment for achieving the passive beamforming gain of IRS because of the considerable overhead required for channel estimation. Specifically, under the current beamforming design for IRS-assisted communications, KMN + KM channel coefficients should be estimated if the passive IRS cannot estimate its channels with the base station (BS) and users due to its lack of radio frequency (RF) chains, where K, N and M denote the numbers of users, reflecting elements of the IRS, and antennas at the BS, respectively. These numbers can be extremely large in practice considering the current trend of massive MIMO (multiple-input multiple-output), i.e., a large M, and massive connectivity, i.e., a large K. To accurately estimate such a large number of channel coefficients within a short time interval, we devote our endeavour in this paper to investigating the efficient pilot-based channel estimation method in IRS-assisted uplink communications. Building upon the observation that each IRS element reflects the signals from all the users to the BS via the same channel, we analytically verify that a time duration consisting of $K+N+\mathrm{max}(K+1,\lceil\frac{(K-1)N}{M}\rceil)$ pilot symbols is sufficient for the BS to perfectly recover all the KMN + KM channel coefficients for the case without receiver noise. In contrast to the conventional uplink communications without IRS in which the minimum pilot sequence length is independent with the number of receive antennas, our study reveals the significant role of massive MIMO in reducing the channel training time for IRS-assisted communications.
Dynamic Model Based Malicious Collaborator Detection in Cooperative Tracking
Wang Pi and Pengtao Yang (Peking University, China); Dongliang Duan (University of Wyoming, USA); Chen Chen and Xiang Cheng (Peking University, China); Liuqing Yang (Colorado State University, USA)
0
The mobility status of vehicles play a crucial role in most tasks of Autonomous Vehicles (AVs) and Intelligent Transportation System (ITS). To operate securely, a precise, stable and robust mobility tracking system is essential. Compared with self-tracking that relies only on mobility observations from on-board sensors (e.g. Global Positioning System (GPS), Inertial Measurement Unit (IMU) and camera), cooperative tracking increases the precision and reliability of mobility data greatly by integrating observations from road side units and nearby vehicles through V2X communications. Nevertheless, cooperative tracking can be quite vulnerable if there are malicious collaborators sending bogus observations in the network. In this paper, we present a dynamic sequential detection algorithm, dynamic model based mean state detection (DMMSD), to exclude bogus mobility data. Simulations validate the effectiveness and robustness of the proposed algorithm as compared with existing approaches.
Session Chair
Wonjun Kim (Seoul National University, Korea (South))
Session T1-S19
Energy Efficient Communications
Conference
4:00 PM
—
5:30 PM KST
Local
May 27 Wed, 3:00 AM
—
4:30 AM EDT
Minimization of Sum Inverse Energy Efficiency for Multiple Base Station Systems
Zijian Wang (Université Catholique de Louvain, Belgium); Luc Vandendorpe (Université catholique de Louvain, Belgium); Mateen Ashraf (University Catholique de Louvain, Louvain-la-Neuve, Belgium); Yuting Mou and Nafiseh Janatian (Université Catholique de Louvain, Belgium)
0
A sum inverse energy efficiency (SIEE) minimization problem is solved. Compared with conventional sum energy efficiency (EE) maximization problems, minimizing SIEE achieves a better fairness. The paper begins by proposing a framework for solving sum-fraction minimization (SFMin) problems, then uses a novel transform to solve the SIEE minimization problem in a multiple base station (BS) system. After the reformulation into a multi-convex problem, the alternating direction method of multipliers (ADMM) is used to further simplify the problem. Numerical results confirm the efficiency of the transform and the fairness improvement of the SIEE minimization. Simulation results show that the algorithm convergences fast and the ADMM method is efficient.
Joint Optimization for PS-based SWIPT Multiuser Systems with Non-linear Energy Harvesting
Thang X. Vu, Symeon Chatzinotas, Sumit Gautam and Eva Lagunas (University of Luxembourg, Luxembourg); Björn Ottersten (University of Luxembourg, Luxembourg)
0
In this paper, we investigate the performance of simultaneous wireless information and power transfer (SWIPT) multiuser systems, in which a base station serves a set of users with both information and energy simultaneously via a power splitting (PS) mechanism. To capture realistic scenarios, a nonlinear energy harvesting (EH) model is considered. In particular, we jointly design the PS factors and the beamforming vectors in order to maximize the total harvested energy, subjected to rate requirements and a total transmit power budget. To deal with the inherent non-convexity of the formulated problem, an iterative optimization algorithm is proposed based on the inner approximation method and semidefinite relaxation (SDR), whose convergence is theoretically guaranteed. Numerical results show that the proposed scheme significantly outperforms the baseline max-min based SWIPT multicast and fixed-power PS designs.
A Novel Low-Complexity Power-Allocation Algorithm for Multi-Tone Signals for Wireless Power Transfer
Boules Mouris (KTH Royal Institute of Technology, Sweden); Henrik Forssell (KTH, Sweden); Ragnar Thobaben (KTH Royal Institute of Technology, Sweden)
0
Recent studies proved that optimized multi-tone signals can significantly enhance the performance of wireless power transfer (WPT) systems. However, optimizing the power allocation for multi-tone signals in order to maximize the efficiency of WPT is a computationally complex task. In this paper, a novel low-complexity algorithm, the truncated maximum-ratio transmission (TMRT) algorithm, for allocating power to multitone signals for WPT is proposed. The algorithm exploits the fact that optimal algorithms tend to allocate power to tones having the strongest channels and no power to weaker channels, and therefore, performs maximum ratio transmission power allocation on the subset of the m strongest channels. In this way, the power allocation problem is reduced to finding the optimal m that maximizes the efficiency. Simulation results confirm that the proposed TMRT algorithm achieves a performance very close to the optimal power allocation, despite its very low complexity, and significantly outperforms other low-complexity solutions.
Towards Power-Efficient Aerial Communications via Dynamic Multi-UAV Cooperation
Lin Xiang, Lei Lei and Symeon Chatzinotas (University of Luxembourg, Luxembourg); Björn Ottersten (University of Luxembourg, Luxembourg); Robert Schober (Friedrich-Alexander University Erlangen-Nuremberg, Germany)
0
Aerial base stations (BSs) attached to unmanned aerial vehicles (UAVs) constitute a new paradigm for next- generation cellular communications. However, the flight range and communication capacity of aerial BSs are usually limited due to the UAVs' size, weight, and power (SWAP) constraints. To address this challenge, in this paper, we consider dynamic cooperative transmission among multiple aerial BSs for power- efficient aerial communications. Thereby, a central controller intelligently selects the aerial BSs navigating in the air for cooperation. Consequently, the large virtual array of moving antennas formed by the cooperating aerial BSs can be exploited for low-power information transmission and navigation, taking into account the channel conditions, energy availability, and user demands. Considering both the fronthauling and the data transmission links, we jointly optimize the trajectories, cooperation decisions, and transmit beamformers of the aerial BSs for minimization of the weighted sum of the power consumptions required by all BSs. Since obtaining the global optimal solution of the formulated problem is difficult, we propose a low-complexity iterative algorithm that can efficiently find a Karush-Kuhn-Tucker (KKT) solution to the problem. Simulation results show that, compared with several baseline schemes, dynamic multi-UAV cooperation can significantly reduce the communication and navigation powers of the UAVs to overcome the SWAP limitations, while requiring only a small increase of the transmit power over the fronthauling links.
Energy Efficiency Optimization for Secure Transmission in a MIMO-NOMA System
Miao Zhang and Kanapathippillai Cumanan (University of York, United Kingdom (Great Britain)); Wei Wang (Nantong University, China); Alister G. Burr (University of York, United Kingdom (Great Britain)); Zhiguo Ding (University of Manchester, United Kingdom (Great Britain)); Sangarapillai Lambotharan (Loughborough University, United Kingdom (Great Britain)); Octavia A. Dobre (Memorial University, Canada)
0
This paper investigates a secrecy energy efficiency (SEE) optimization problem for a multiple-input multiple-output non-orthogonal multiple access network. In particular, a multi-antenna transmitter intends to send two integrated service messages: a confidential message for the stronger user and a broadcast message for both stronger and weaker users. It is assumed that both users are equipped with multi-antennas. In this secure wireless network, we consider the transmit covariance matrices design of confidential and broadcast message, under broadcast energy efficiency (BEE) constraint. In addition, it is assumed that the weaker user might turn out to be a potential eavesdropper due to the broadcast nature of wireless transmission. We formulate this transmit covariance matrices design as an SEE maximization problem which is non-convex in its original form due the non-linear fractional objective function and constraints. To realize the solution for this problem, we utilize non-linear fractional programming and difference of concave (DC) functions approach which facilitate to reformulate it into a tractable form. Based on the Dinkelbach's algorithm and DC approximation method, we propose iterative algorithms to determine a solution to the original SEE maximization problem. Numerical results are provided to demonstrate the performance of the proposed transmit covariance matrices design to maximize the SEE.
Session Chair
Seok-Ho Chang (Konkuk University, Korea (South))