- Electrical and Electronic Engineering - Research Publications
Electrical and Electronic Engineering - Research Publications
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ItemNo Preview AvailableFlex-Net: A Graph Neural Network Approach to Resource Management in Flexible Duplex NetworksPerera, T ; Atapattu, S ; Fang, Y ; Dharmawansa, P ; Evans, J (IEEE, 2023)
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ItemNo Preview AvailableFrequency Permutations for Joint Radar and CommunicationsSenanayake, R ; Smith, PJ ; Han, T ; Evans, J ; Moran, W ; Evans, R (IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2022-11-01)
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ItemNo Preview AvailableDesign and Analysis of Hardware-Limited Non-Uniform Task-Based QuantizersBernardo, NI ; Zhu, J ; Eldar, YC ; Evans, J (IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2023)
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ItemNo Preview AvailableCapacity Bounds for One-Bit MIMO Gaussian Channels With Analog CombiningBernardo, NI ; Zhu, J ; Eldar, YC ; Evans, J (IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2022-11-01)
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ItemNo Preview AvailableOn the Capacity-Achieving Input of Channels With Phase QuantizationBernardo, NI ; Zhu, J ; Evans, J (IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2022-09-01)
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ItemNo Preview AvailableOptimum Reconfigurable Intelligent Surface Selection for Wireless NetworksFang, Y ; Atapattu, S ; Inaltekin, H ; Evans, J (IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2022-09)
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ItemNo Preview AvailableOn the Capacity-Achieving Input of the Gaussian Channel With Polar QuantizationBernardo, NI ; Zhu, J ; Evans, J (IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2022-09-01)
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ItemNo Preview AvailableCombined Radar and Communications With Phase-Modulated Frequency PermutationsHan, T ; Senanayake, R ; Smith, P ; Evans, J ; Moran, W ; Evans, R (IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2023)
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ItemNo Preview AvailablePhysical-Layer Security in Full-Duplex Multi-Hop Multi-User Wireless Network With Relay SelectionAtapattu, S ; Ross, N ; Jing, Y ; He, Y ; Evans, JS (IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2019-02-01)This paper investigates the relay selection (RS) problem for multi-hop full-duplex relay networks where multiple source-destination (SD) pairs compete for the same pool of relays, under the attack of multiple eavesdroppers. To enhance the physical-layer security, within a given coherence time, our objective is to jointly assign the available relays at each hop to different SD pairs to maximize the minimum secrecy rate among all pairs. Two RS schemes, optimal RS and suboptimal RS (SRS), are proposed for two-hop networks based on global channel state information (CSI) and only SD pairs CSI, respectively. Since all users can communicate within the same coherence time, our joint RS schemes are important for the user-fairness and ultra-reliable low-latency communications. To evaluate the performance, the exact secrecy outage probability of the SRS scheme is derived under two residual self-interference models. The asymptotic analysis shows that the SRS scheme achieves full diversity. A relay-based jamming scheme is also proposed by using unassigned relays for user communications. Finally, the two-hop RS schemes and the analysis are extended to the general multi-hop network with multiple eavesdroppers. The numerical results reveal interesting fundamental trends where the proposed schemes can significantly enhance the secrecy performance.
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ItemMaximizing Sum-Rate via Relay Selection and Power Control in Dual-Hop NetworksDayarathna, S ; Senanayake, R ; Evans, J (IEEE, 2022-01-01)In this paper, we focus on the sum-rate optimization problem in a general dual-hop relay network by considering the joint relay selection and power control in the presence of interference. First, we propose a new relay selection algorithm which has better sum-rate performance than the existing relay selection techniques. Then we combine relay selection and power control to propose a novel iterative algorithm based on the tight lower bound approximation which maximizes the achievable sum-rate. We also prove that for the special case of two-user networks, binary power allocation is optimum for at least two transmitting nodes. Extensive numerical examples are used to compare the performance of the proposed algorithm and to illustrate the accuracy of the analysis.