Workshops and Tutorials

6th IEEE WCNC International Workshop on Smart Spectrum (IWSS 2020)

Session HWS10-Opening

Opening Session

Conference
2:00 PM — 2:10 PM KST
Local
May 24 Sun, 10:00 PM — 10:10 PM PDT

Session Chair

Kenta Umebayashi (Tokyo University of Agriculture and Technology, Japan)

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Session HWS10-Keynote

Keynote

Conference
2:10 PM — 2:50 PM KST
Local
May 24 Sun, 10:10 PM — 10:50 PM PDT

Computing & Communication Tradeoff in 5G and Beyond

Seong-Lyun Kim (Yonsei University, Korea)

1
This talk does not have an abstract.

Session Chair

Kenta Umebayashi (Tokyo University of Agriculture and Technology, Japan)

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Session HWS10-S1

Smart Spectrum 1

Conference
2:50 PM — 3:30 PM KST
Local
May 24 Sun, 10:50 PM — 11:30 PM PDT

Direct Beamformer Estimation for Hybrid Architecture in mmWave Dynamic TDD System

Prashant Kumar Shah, Krishna Joshi, Satya Krishna Joshi and Antti Tölli (University of Oulu, Finland); Kenta Umebayashi (Tokyo University of Agriculture and Technology, Japan)

2
The problem of weighted sum-rate maximization for hybrid architecture in millimeter wave communications with dynamic time division duplexing is considered. Assumption of perfect channel state information is idealistic, and it is rarely available in practise. We propose an over the air pilot-aided direct beamforming estimation technique for the considered problem, by exploiting the channel reciprocity. Proper selection of analog precoder/combiner not only suppress large part of interference, but also ensure that less coordination is required for digital precoder/combiner design. We design analog precoders/combiners for each data stream in such a way that its signal strength is maximized; this strategy also minimizes large part of inter-stream interference that may arise due to the main-lobe of analog beamformers. Then we design digital beamformers such that inter-stream interference is further mitigated, maximizing the overall weighted sum-rate of the network.

Sample Size Analysis of Energy Detection under Fading Channels

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
The performance of energy detection under fading channels has been evaluated in terms of the average probability of detection as a function of the average Signal-to-Noise Ratio (SNR) and the channel fading parameters, assuming that the decision threshold is set to achieve a constant false alarm rate. However, the signal sample size, which is an important design parameter in the configuration of an energy detector and has a significant impact on its performance, has received no attention in the context of fading channels. The mathematical expressions available in the literature to calculate the sample size required to achieve desired target performance are valid for Additive White Gaussian Noise (AWGN) channels only, and the impact of fading on the required sample size remains unknown. In this context, this work fills the existing gap by providing analytical results that establish a direct relation between the channel fading parameters and the required sample size. The results are provided for a broad variety of fading models (Rayleigh, Nakagami-m, Nakagami-q/Hoyt, Nakagami-n/Rice, eta-mu and kappa-mu) in terms of elementary functions, which enables highly efficient numerical evaluations.

Session Chair

Kenta Umebayashi (Tokyo University of Agriculture and Technology, Japan)

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Session HWS10-S2

Smart Spectrum 2

Conference
3:45 PM — 5:15 PM KST
Local
May 24 Sun, 11:45 PM — 1:15 AM PDT

A Study on High-Efficiency Energy Detection-Based Spectrum Measurements

Hiroki Iwata, Kenta Umebayashi and Ahmed Al-Tahmeesschi (Tokyo University of Agriculture and Technology, Japan); Satya Krishna Joshi (University of Oulu, Finland); Miguel López-Benítez (University of Liverpool, United Kingdom (Great Britain)); Janne Lehtomäki (University of Oulu, Finland)

0
Statistical information in terms of spectrum occupancy is useful for the efficient and smart dynamic spectrum sharing, and it can be obtained by long-term, broadband, and wide-area spectrum measurements. In this paper, we investigate an energy detection-based spectrum measurements, in which the noise floor (NF) estimation is a key functionality for the appropriate detection threshold setting. Typically, the NF has the slowly time-varying property and frequency-dependency, and several NF estimation algorithms including forward consecutive mean excision (FCME) algorithm-based method have been proposed. However, these methods did not deeply consider the slowly time-varying property of the NF and are computationally inefficient. Accordingly, we propose a computational complexity reduction algorithm based on NF level change detection. This algorithm is computationally efficient since it skips the NF estimation process when the NF does not change. In numerical evaluations, we show the efficiency and the validity of the proposed algorithm.

LTE/Wi-Fi Coexistence in Unlicensed Bands Based on Dynamic Transmission Opportunity

Moawiah Alhulayil and Miguel López-Benítez (University of Liverpool, United Kingdom (Great Britain))

0
With the rapid proliferation of smart devices, the demand for more licensed spectrum bands arises. Due to the scarcity of the licensed spectrum, the 3rd Generation Partnership (3GPP) has recently deployed Long Term Evolution (LTE) networks using the Licensed Assisted Access (LAA) scheme over unlicensed bands. On the other hand, the Wi-Fi technology is the main technology that operates over these unlicensed bands. Thus,the major concern is to attain a fair coexistence mechanism between these coexisting technologies (i.e., LTE and Wi-Fi). In this paper, we focus on the downlink scenario under different traffic loads to study the effect of the maximum Transmission Opportunity (TxOP) period for LTE-LAA in the performance of LTE-LAA/Wi-Fi coexistence. A dynamic TxOP period method is proposed to provide better fairness and higher total aggregated throughputs for the coexisting networks based on the Hybrid Automatic Repeat Request (HARQ) reports. The novelty of this work is that the existing HARQ reports are exploited to update the TxOP period for LAA in a dynamic manner. We show that the TxOP period plays a key role in the coexistence between LTE-LAA and Wi-Fi networks over unlicensed bands. The simulation results show that the proposed dynamic TxOP method improves the fairness and achieves higher total aggregated throughputs for both coexisting networks as compared to the static TxOP period used by the standard Category 4 LBT (Cat 4 LBT) method defined by 3GPP.

USRP-based platform for 26/28 GHz mmWave Experimentation

Martin Danneberg and Roberto Bomfin (Technische Universität Dresden, Germany); Ahmad Nimr (Dresden University of Technology, Germany); Zhongju Li and Gerhard P. Fettweis (Technische Universität Dresden, Germany)

0
This paper presents an platform for 26/28GHz millimeter wave (mmWave) experimentation. We introduce an analog mmWave multi-beam antenna array, developed at TU-Dresden, that can be interfaced with regular software-defined radio (SDR) platforms. The motivation of this setup is to enable mmWave experimentation with a relatively simple system setup. As a demonstration example, we combine the mmWave frontends with the GFDM transceiver to provide a communication link at 26GHz. Moreover, considering mobility, we implement a real-time beam tracking algorithm that switches the beam according to the user's location. The performance is evaluated in terms through-put, where we demonstrate transmissions up to 3.1Mbits/s.

Radio Environment Map Updating Procedure considering Change of Surrounding Environment

Keita Katagiri (The University of Electro-Communication & Advanced Wireless and Communication Research Center (AWCC), Japan); Takeo Fujii (The University of Electro-Communications, Japan)

0
In this paper, we propose a method to update a radio environment map (REM) considering change of surrounding environment. The REM provides statistical radio information of primary users (PUs) to secondary users (SUs). SUs can utilize the information to design communication parameters for improving communication efficiency. However, if surrounding environment changes, the newly observed datasets are significantly different from the initially observed datasets. The database server requires to detect change of surrounding environment and to update the REM based on the detected results. In this paper, we propose a method to update the REM based on hypothesis testing. In the proposed method, sensor nodes observe a received signal strength indicator (RSSI) in each location and report that to the database server. Then, the database server updates the REM using tested results. The simulation results show that the proposed method can detect change of surrounding environment and accurately predict the average RSSI in each location while significantly reducing the number of the REM updates.

Mathematical Models for the Accuracy of the Estimated Distribution of Primary Activity Times in DSA

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)

0
Dynamic Spectrum Access (DSA) / Cognitive Radio (CR) systems can greatly benefit from the knowledge of the activity statistics of the primary channel. Such statistics can be estimated by the DSA/CR system based on the on/off decisions provided by the employed spectrum sensing algorithm, which can be processed to estimate the duration of the individual idle/busy periods of the primary channel and subsequently a broad range of activity statistics. Previous work has investigated analytically this estimation approach and provided closed-form expressions for the estimated distribution as well as its associated estimation error. However, existing analytical results are provided in an implicit form that requires some form of numerical evaluation and is not always well-suited for analytical manipulations. In this context, this work extends the existing results by providing mathematical models in an explicit form that can be evaluated directly and are applicable to several estimation strategies. The obtained mathematical expressions are validated with simulation results, showing a remarkable high level of accuracy.

Session Chair

Miguel López-Benítez (University of Liverpool, United Kingdom)

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