Achievable Rate Maximization for Underlay Spectrum Sharing MIMO System With Intelligent Reflecting Surface

Kumar, Vaibhav; Flanagan, Mark F.; Zhang, Rui; Tran, Le-Nam

doi:10.1109/lwc.2022.3180988

Cited by 16 publications

(11 citation statements)

References 17 publications

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“…This phase shift design is denoted as "Long-term" in the figures. ) The short-term phase shift design optimizes the instantaneous SNR as formulated in (10). This phase shift design is denoted as "Short-term" in the figures. )…”

Section: Numerical Resultsmentioning

confidence: 99%

See 1 more Smart Citation

Controlling Smart Propagation Environments: Long-Term Versus Short-Term Phase Shift Optimization

Chien

Thanh

Tran

et al. 2022

ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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Reconfigurable intelligent surface (RIS) has recently gained significant interest as an emerging technology for future wireless networks thanks to its potential for improving the coverage probability in challenging propagation environments. This paper studies an RIS-assisted propagation environment, where a source transmits data to a destination in the presence of a weak direct link. We analyze and compare RIS designs based on long-term and short-term channel statistics in terms of coverage probability and ergodic rate. For the considered optimization designs, we derive closed-form expressions for the coverage probability and ergodic rate, which explicitly unveil the impact of both the propagation environment and the RIS on the system performance. Besides the optimization of the RIS phase profile, we formulate an RIS placement optimization problem with the aim of maximizing the coverage probability by relying only on partial channel state information. An efficient algorithm is proposed based on the gradient ascent method. Simulation results are illustrated in order to corroborate the analytical framework and findings. The proposed RIS phase profile is shown to outperform several heuristic benchmarks in terms of outage probability and ergodic rate. In addition, the proposed RIS placement strategy provides an extra degree of freedom that remarkably improves system performance.

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Section: Numerical Resultsmentioning

confidence: 99%

“…The initial location of the RIS (0) r , (0) r , (0) r is selected as in Figs. 1-3, ( r,min , r,min , r,min ) = (20,10,5) [m], ( r,max , r,max , r,max ) = (30,40,35) [m], and the step size is = 0.9. We observe a remarkable enhancement of the coverage probability by appropriately deploying the RIS.…”

Section: Numerical Resultsmentioning

confidence: 99%

Controlling Smart Propagation Environments: Long-Term Versus Short-Term Phase Shift Optimization

Chien

Thanh

Tran

et al. 2022

ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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show abstract

“…A similar assumption regarding the perfect CSI availability in different IRS-assisted systems was considered in[8]-[16]. The results in this letter serve as theoretical performance bounds for the IRS-MU-MIMO system with imperfect CSI.…”

mentioning

confidence: 89%

A Novel SCA-Based Method for Beamforming Optimization in IRS/RIS-Assisted MU-MISO Downlink

Kumar

Zhang

Renzo

et al. 2023

IEEE Wireless Commun. Lett.

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In this letter, we consider the fundamental problem of jointly designing the transmit beamformers and the phaseshifts of the intelligent reflecting surface (IRS) / reconfigurable intelligent surface (RIS) to minimize the transmit power, subject to quality-of-service constraints at individual users in an IRSassisted multiuser multiple-input single-output downlink communication system. In particular, we propose a new successive convex approximation based second-order cone programming approach in which all the optimization variables are simultaneously updated in each iteration. Our proposed scheme achieves superior performance compared to state-of-the-art benchmark solutions. In addition, the complexity of the proposed scheme is O(N 3.5 s ), while that of state-of-the-art benchmark schemes is O(N 7 s ), where Ns denotes the number of reflecting elements at the IRS.

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“…In the downlink of RIS-assisted mmWave communication systems, most optimization problems involve joint optimization of RIS phase shift and baseband precoding to meet various optimization objectives [13][14][15][16]. In [14], the trade-off between energy efficiency and spectrum efficiency in the RIS-assisted multi-user uplink was investigated.…”

Section: Introductionmentioning

confidence: 99%

Low-Complexity Passive Beamforming for Reconfigurable Intelligent Surface Aided mmWave communication Systems

Qi,

Li,

Zhang

et al. 2024

Preprint

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Millimeter wave (mmWave) communication technology has received wide attention in recent years due to its abundant frequency resources. However, severe propagation loss and the ease of being blocked by obstacles are not conducive to wide area coverage. Reconfigurable intelligent surface (RIS) is expected to solve the coverage problem of mmWave communication systems by reforming the wireless channel to some extent. In this work, we propose a low complexity scheme for the optimization of RIS phase shifts in the downlink of mmWave communication systems. Unlike previous works that usually jointly design the RIS phase shifts and precoding matrix with nonnegligible computational and implementation complexity, we propose to solely optimize the RIS phase shifts to maximize the overall throughput of the wireless channel and devise two low complexity RIS phase shift design schemes, i.e., TM UB-RPO and TM SCA-RPO. For TM UB-RPO, the suboptimal phase shifts are derived in closed form through theoretical analysis, while for TM SCA-RPO, the phase shifts are optimized using the successive convex approximation method, and the solution in each iteration is given in closed form. The proposed schemes can work with any conventional precoding scheme, such as zero-forcing precoding (ZF), thus can be easily deployed in existing schemes. Numerical results show that the proposed schemes outperform existing methods in terms of achievable rates while significantly reducing computational complexity.

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Achievable Rate Maximization for Underlay Spectrum Sharing MIMO System With Intelligent Reflecting Surface

Cited by 16 publications

References 17 publications

Controlling Smart Propagation Environments: Long-Term Versus Short-Term Phase Shift Optimization

Controlling Smart Propagation Environments: Long-Term Versus Short-Term Phase Shift Optimization

A Novel SCA-Based Method for Beamforming Optimization in IRS/RIS-Assisted MU-MISO Downlink

Low-Complexity Passive Beamforming for Reconfigurable Intelligent Surface Aided mmWave communication Systems

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