Cooperative Backscatter Communications With Reconfigurable Intelligent Surfaces: An APSK Approach
Year: 2024
Type: article
Abstract: In this paper, a novel amplitude phase shift keying (APSK) modulation scheme for cooperative backscatter communications aided by a reconfigurable intelligent surface (RIS-CBC) is presented, according to which a passive or an active RIS is configured to modulate backscatter information onto unmodulated or PSK-modulated signals impinging on its panel via APSK. In passive RIS-CBC-APSK, the backscatter information is conveyed through the number of RIS reflecting elements being in the ON state and their phase shift values, whereas, in active RIS-CBC-APSK, this information is embedded through the number of RIS elements being in the active mode as well as the phase shift values of all elements. By using the optimal APSK constellation to ensure that reflected signals from the RIS undergo APSK modulation, a bit-mapping mechanism is developed. Assuming maximum-likelihood detection, we also present closed-form upper bounds for the symbol error rate (SER) performance for both proposed passive and active RIS-CBC-APSK schemes over Rician fading channels. In addition, we devise a low-complexity detector that can achieve flexible trade-offs between performance and complexity. Finally, we extend RIS-CBC-APSK to multiple-input single-output scenarios and present an alternating optimization approach for the joint design of transmit beamforming and RIS reflection. Our extensive simulation results on the SER performance of the proposed RIS-CBC-APSK framework corroborate our conducted performance analysis and showcase the superiority of both designed modulation schemes over the state-of-the-art RIS-CBC benchmarks.
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
Awards: G1542731143, ECCS-EPSRC: NeuroComm: Brain-Inspired Wireless Communications -- From Theoretical Foundations to Implementation for 6G and Beyond, G2184382865, G2236638392, Collaborative Research: SWIFT: Nonlinear and Inseparable Radar And Data (NIRAD) Transmission Framework for Pareto Efficient Spectrum Access in Future Wireless Networks, G4136366276, α-强衰减稀疏信号重构理论研究与算法设计, G7191294184, G7264393904
OpenAlex ID: W4401536832
