Energy Efficiency and Spectral Efficiency Tradeoff in RIS-Aided Multiuser MIMO Uplink Systems

Xiong, Jiayuan; You, Li; Ng, Derrick Wing Kwan; Yuen, Chau; Wang, Wenjin; Gao, Xiqi

doi:10.1109/globecom42002.2020.9348208

Cited by 10 publications

(8 citation statements)

References 16 publications

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“…In this section, we will provide some simulation results to evaluate the performance of the framework for the trade-off of the EE and SE. During the simulation, we use the 3GPP spatial channel model under the suburban macro-cell propagation scenario [33,34]. The adopted parameters during the simulation are shown in the Table 1 below for clarity [35].…”

Section: Numerical Resultsmentioning

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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Section: Numerical Resultsmentioning

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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“…To facilitate the derivation of the overall proposed incentive mechanism and resource allocation algorithm's computation complexity, as presented in Algorithm 1, the following algorithmic complexities are considered alone. First, the asymptotic complexity of a convex optimization problem is polynomial in the number of the optimization variables [43], [46], which applies for the optimization problems in Eq. ( 33), Eq.…”

Section: Computation Complexitymentioning

confidence: 99%

Incentive Mechanism and Resource Allocation for Edge-Fog Networks Driven by Multi-Dimensional Contract and Game Theories

Diamanti

Charatsaris

Tsiropoulou

et al. 2022

IEEE Open J. Commun. Soc.

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The edge computing paradigm has become extremely popular over the past years, as a means of offloading computationally intensive tasks by users of resource and battery-constrained devices. Nevertheless, the edge networks' overexploitation by the ever-increasing number of task-offloading users, gradually leads to their performance degradation. In this paper, we leverage on the different levels of available computing capabilities across the network, and we design an incentive mechanism that aims to shift the selfish users' preference from the edge to the upper fog computing layer, accounting for their level of delay tolerance. To deal with the users' heterogeneity in terms of their applications' multidimensional distinctive features (including their delay tolerance/sensitivity), a multi-dimensional contract theory modeling is adopted, according to which the edge server determines the bundles of the users' provided efforts and corresponding offered rewards. In this respect, each user's effort represents the amount of its initially offloaded task at the edge that is allowed to be further forwarded and processed at the fog. Considering that the users-to-edge server offloading is performed under Non-Orthogonal Multiple Access (NOMA), the problem of joint computation task offloading and uplink transmission power allocation is subsequently addressed via a Stackelberg game, where the edge server and the users are treated as leader and followers, respectively. The aim of the game is to minimize the end-to-end network's energy consumption and increase its resource utilization efficiency. The incentive mechanism and resource allocation framework is evaluated via modeling and simulation regarding its operation and efficiency under different scenarios.

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“…To enhance the spectrum and energy efficiency of a 6G-enabled cognitive IoT network, two SWIPT cooperative spectrum sharing techniques are suggested in Lu et al 46 In Lu et al, 47 an architectural design for smart cities has been studied through the use of information transfer protocols and collaborative energy. In previous studies, [48][49][50] Reconfigurable intelligent surface (RIS)enabled networks were studied for energy optimization. In Diamanti et al, 51 RIS is used in an unmanned aerial vehicle (UAV)-assisted integrated access and backhaul (IAB) technology to achieve energy efficiency in NOMA-based wireless communication systems.…”

Section: Introductionmentioning

confidence: 99%

Energy‐efficient multiple cooperative moving relay selection for heterogeneous nonorthogonal‐multiple access systems

Khan

Chauhan²,

Singh³

2022

Int J Communication

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In a high-speed vehicular scenario, due to vehicle penetration loss (VPL) and fast signal fluctuations, frequent handovers occur, which results in more battery consumption. So power saving is a critical concern in high-speed wireless networks. In the past, moving relay (MR)-based heterogeneous network (HetNet) models were proposed and studied to overcome the effect of VPL, but the issue of power saving has not been studied till now for vehicular HetNet.

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Energy Efficiency and Spectral Efficiency Tradeoff in RIS-Aided Multiuser MIMO Uplink Systems

Cited by 10 publications

References 16 publications

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

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

Incentive Mechanism and Resource Allocation for Edge-Fog Networks Driven by Multi-Dimensional Contract and Game Theories

Energy‐efficient multiple cooperative moving relay selection for heterogeneous nonorthogonal‐multiple access systems

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