Reconfigurable Intelligent Surfaces Assisted MIMO-MAC with Partial CSI

Xiong, Jiayuan; You, Li; Huang, Yufei; Ng, Derrick Wing Kwan; Wang, Wenjin; Gao, Xiqi

doi:10.1109/icc40277.2020.9149355

Cited by 7 publications

(7 citation statements)

References 13 publications

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“…Hence, the developed approach for optimizing Φ also converges and will not decrease the system GEE value at each iteration in Algorithm 4. Based on the above facts, both solutions of Q and Φ will not decrease the objective value in P Q,Φ , i.e., GEE 1) , where t is the iteration index of AO. Hence, the convergence of the overall methodology for alternatingly optimizing Q and Φ in the AO-based GEE maximization in Algorithm 4 is guaranteed.…”

Section: Convergence and Complexity Analysismentioning

confidence: 98%

“…In ( 5), ξ k = ρ −1 k with ρ k denoting the transmit power amplifier efficiency at UT k, tr {Q k } denotes the average transmit power consumed by UT k, and P c,k represents the static circuit power dissipation at UT k. In addition, P BS and N R P s incorporate the static hardware-dissipated power at the BS and the RIS, respectively. 1 It is worth emphasizing that there is no transmit power consumed by the RIS because the reflectors of the RIS are passive elements which do not change the magnitude of the reflected signals. In fact, the potential amplification gain offered by the RIS is realized via appropriately adjusting the phase shifts of the reflectors so that the impinging signals are coherently combined at the desired receiver.…”

Section: B Energy Consumption Modelmentioning

confidence: 99%

“…Solve problem P Φ in (23) via solving the equivalent problem P MSE using the BCDbased Algorithm 5 and set the intermediate solution as Φ (t+1) . 9: 1) , Φ (t−1) ≤ ε Output: Transmit covariance matrices Q (t) and the RIS phase shift matrix Φ (t) .…”

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confidence: 99%

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Reconfigurable Intelligent Surfaces-Assisted Multiuser MIMO Uplink Transmission with Partial CSI

You,

Xiong,

Huang

et al. 2020

Preprint

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This paper considers the application of reconfigurable intelligent surfaces (RISs) (a.k.a. intelligent reflecting surfaces (IRSs)) to assist multiuser multiple-input multiple-output (MIMO) uplink transmission from several multi-antenna user terminals (UTs) to a multi-antenna base station (BS). For reducing the signaling overhead, only partial channel state information (CSI), including the instantaneous CSI between the RIS and the BS as well as the slowly varying statistical CSI between the UTs and the RIS, is exploited in our investigation. In particular, an optimization framework is proposed for jointly designing the transmit covariance matrices of the UTs and the RIS phase shift matrix to maximize the system global energy efficiency (GEE) with partial CSI. We first obtain closed-form solutions for the eigenvectors of the optimal transmit covariance matrices of the UTs. Then, to facilitate the design of the transmit power allocation matrices and the RIS phase shifts, we derive an asymptotically deterministic equivalent of the objective function with the aid of random matrix theory. We further propose a suboptimal algorithm to tackle the GEE maximization problem with guaranteed convergence, capitalizing on the approaches of alternating optimization, fractional programming, and sequential optimization. Numerical results substantiate the effectiveness of the proposed approach as well as the considerable GEE gains provided by the RIS-assisted transmission scheme over the traditional baselines.

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Section: Convergence and Complexity Analysismentioning

confidence: 98%

Section: B Energy Consumption Modelmentioning

confidence: 99%

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Reconfigurable Intelligent Surfaces-Assisted Multiuser MIMO Uplink Transmission with Partial CSI

You,

Xiong,

Huang

et al. 2020

Preprint

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“…Since CSI plays a major role in obtaining the properties of the communication channel in MIMO, achieving perfect CSI is still challenging due to limited signal processing. The authors in [121] - [124] considered RIS-aided MIMO system by assuming imperfect CSI. The authors in [122] studied the worst-case robust beamforming design for the proposed system.…”

Section: ) State-of-the-artmentioning

confidence: 99%

Reconfigurable Intelligent Surface Aided Multi-User Communications: State-of-the-Art Techniques and Open Issues

Munochiveyi

Pogaku

Do³

et al. 2021

IEEE Access

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Reconfigurable intelligent surface (RIS)-aided communication is considered as an exciting research topic in academic and industrial communities since it provides an emerging affordable solution to achieve high quality and secure next-generation wireless systems. Especially, the deployment of RIS in multi-user wireless networks promises to reduce system hardware costs, signal processing complexity, as well as energy consumption due to small size, lightweight and ability to actively shape the wireless propagation environment. Further, by realizing a cost-effective radio environment, RIS-aided communication can be implemented to be an appealing technology for future integration with other emerging wireless applications and communication systems. Despite the positive appeal, RISs face new challenges that hinder integrating efficiently into wireless networks, such as network secrecy performance and system sum-rates, as well as achieving efficient deployment design in highly dynamic and time-varying wireless environments. To this end, we overview recent state-of-the-art techniques to address the above issues faced in the integration of RISs with various emerging multi-user communication techniques, such as Unmanned Aerial Vehicles (UAVs), Non-Orthogonal Multiple Access (NOMA), Millimeter Wave (mmWave) and Terahertz (THz) communications, Physical Layer Security (PLS), massive antennas, and Simultaneous Wireless Information and Power Transfer (SWIPT). Finally, we highlight promising future research directions of RIS-aided communication in Cell-Free Massive Multiple-Input-Multiple-Output (MIMO) systems, Rate-Splitting Multiple Access (RSMA), Light Fidelity (LiFi), and Cognitive Radio (CR) systems.

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“…In the resource allocation design of RIS-aided communication, large amounts of work focus on optimizing the spectral efficiency (SE) of the system [18]. Furthermore, we treat energy efficiency (EE), which is another important topic in the research on RIS [19,20], as one of the optimization objectives. However, most of the existing work has focused on the optimization of either SE or EE.…”

Section: Introductionmentioning

confidence: 99%

On the Trade-Off between Energy Efficiency and Spectral Efficiency in RIS-Aided Multi-User MISO Downlink

et al. 2021

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As reconfigurable intelligent surfaces (RISs) have been gradually brought to reality, a large amount of research has been conducted to investigate the immense benefits of RISs. That is because RISs enable us to artificially direct the radio wave propagating through the environment at a relatively low cost. This paper investigates the trade-off between spectral efficiency (SE) and energy efficiency (EE) in the RIS-aided multi-user multiple-input single-output downlink. We develop an optimization framework for designing the transmitting precoding at the base station and the phase shift values at the RIS to balance the EE-SE trade-off. The proposed iterative optimization framework for the design includes quadratic transform, alternating optimization, and weighted minimization mean-square error conversion. Simulation results illustrate our optimization framework algorithm exhibits effectiveness and a fast convergence rate.

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Reconfigurable Intelligent Surfaces Assisted MIMO-MAC with Partial CSI

Cited by 7 publications

References 13 publications

Reconfigurable Intelligent Surfaces-Assisted Multiuser MIMO Uplink Transmission with Partial CSI

Reconfigurable Intelligent Surfaces-Assisted Multiuser MIMO Uplink Transmission with Partial CSI

Reconfigurable Intelligent Surface Aided Multi-User Communications: State-of-the-Art Techniques and Open Issues

On the Trade-Off between Energy Efficiency and Spectral Efficiency in RIS-Aided Multi-User MISO Downlink

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