Wireless Communications
Mojtaba Hajiabadi; Naaser Neda; Amir Moradband Toroghi
Abstract
Background and Objectives: This research addresses the issue of channel estimation and beamforming in systems with Reconfigurable Intelligent Surface (RIS). RIS is able to significantly improve coverage by controlling the phase and amplitude of the reflected signals through nearly passive elements. This ...
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Background and Objectives: This research addresses the issue of channel estimation and beamforming in systems with Reconfigurable Intelligent Surface (RIS). RIS is able to significantly improve coverage by controlling the phase and amplitude of the reflected signals through nearly passive elements. This advantage is highly dependent on the availability of accurate channel state information (CSI), which is difficult to obtain, and even more so in realistic scenarios where the RIS phase variations are limited to a small number of discrete surfaces due to hardware limitations.Methods: To study this issue, we propose a new CSI estimation paradigm called recursive averaging, which extends the traditional least squares (LS) estimator but compensates for its weaknesses under low SNR and quantized phase regimes, known as (RALS). The new approach involves combining a recursive update scheme that sequentially improves the CSI estimates through recursive averaging and an adaptive feedback framework. This provides better robustness against noise and quantization-induced distortion, and allows for more precise RIS configuration under the hardware constraints of a non-ideal system. The aim is to reduce the channel estimation error and reduce the bit error rate (BER) by considering the practical implementation of the method. In addition, this study also investigates the effect of discrete phase.Results: We analyze the performance of RALS under idealized continuous-phase and discrete-phase scenarios, where the phase of each RIS element is quantized with a finite number of bits. Simulation results show that RALS outperforms traditional LS and other reference estimators measured in MSD and BER, especially in situations where the number of quantized bits is low or the SNR is poor.Conclusion: Simulation results show that the proposed method provides higher accuracy channel estimation with less estimation error. Integrating accurate channel estimation with efficient beamforming strategy, overall system performance is significantly enhanced. More specifically, it is shown through simulations that 4-bit resolution is sufficient for phase discretization considering real reflection phase constraints. Interestingly, the devised approach achieves such improved performance without engaging in huge computational complexity, thus being feasible to implement in real-time in RIS-based systems.
Wireless Communications
M.B. Noori Shirazi; M.R. Zahabi
Abstract
Background and Objectives: Non-orthogonal multiple access (NOMA) is a promising solution to meet a high data rate demand in the new generation of cellular networks. Moreover, simultaneous wireless information and power transfer (SWIPT) was introduced to enhance the performance in terms of energy efficiency. ...
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Background and Objectives: Non-orthogonal multiple access (NOMA) is a promising solution to meet a high data rate demand in the new generation of cellular networks. Moreover, simultaneous wireless information and power transfer (SWIPT) was introduced to enhance the performance in terms of energy efficiency. In this paper, a single-cell cooperative NOMA system with energy harvesting full-duplex (FD) relaying is proposed to improve the sum rate and energy efficiency. Methods: A downlink model consisting of a base station (BS), two cell-center users (nearly located users), and two cell-edge users (far located users) are considered. In each signalling interval, the BS transmits a superposition signal of cell-center and cell-edge users based on the power domain (PD) NOMA strategy. Employing a relay selection criterion, a cell-center user is paired with a cell-edge user and acts as an FD decode and forward (DF) relay to improve the cell-edge user performance. An energy harvesting (EH) model is considered where a power splitting (PS) protocol is adopted at the relay node. The other cell-center user saves the harvested energy from the BS to exploit in the subsequent signalling intervals. Two problems of power allocation for sum rate and energy efficiency maximization in constraints of the minimum required data rate for each user and maximum transmit power at the BS are formulated for the proposed scheme. Due to the non-convexity, the optimization problems are transformed and approximated to the convex optimization problems and solved by iterative algorithms. Difference of convex (DC) programming is employed for solving the sum rate maximization problem where an effective combination of DC programming, bisection method, and Dinkelbach algorithm is utilized for dealing with the energy efficiency maximization problem. Results: The sum rate and energy efficiency over maximum available power at the BS are presented. Also, the effects of the power splitting factor and the cell radius on the sum rate and energy efficiency are investigated. Moreover, a comparison with the OMA and NOMA schemes is studied for the different minimum required data rates. Conclusion: Simulation results validate that the proposed scheme outperforms the OMA and NOMA schemes in terms of sum rate in all SNR regimes. Moreover, the energy efficiency of the proposed scheme achieves considerably better performance than OMA for all SNR values and obtains remarkable better performance than NOMA in most SNR values.
