Robust Max-Min Energy Efficiency for RIS-Aided HetNets With Distortion Noises

Xu, Yongjun; Xie, Hao; Wu, Qingqing; Huang, Chongwen; Yuen, Chau

doi:10.1109/tcomm.2022.3141798

Cited by 93 publications

(21 citation statements)

References 54 publications

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“…Third, the safety issue of the VEC systems needs to be further explored [40]. In addition, the digital twin [41], unmanned aerial vehicle (UAV) [42] and reconfigurable intelligent surfaces (RISs) [43] can be integrated into the VEC system. Other solution methods to the MINP problems, such as the dandelion algorithm (DA) [44] and Bat algorithm [45], can also be adopted to solve the formulated problem.…”

Section: Discussionmentioning

confidence: 99%

Computational Resources Allocation and Vehicular Application Offloading in VEC Networks

Gu¹,

Yang²,

et al. 2022

Electronics

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With the advances in wireless communications and the Internet of Things (IoT), various vehicular applications such as image-aided navigation and autonomous driving are emerging. These vehicular applications require a significant number of computation resources and a lower processing delay. However, these resource-limited and power-constrained vehicles may not meet the requirements of processing these vehicular applications. By offloading these vehicular applications to the edge cloud, vehicular edge computing (VEC) is deemed a novel paradigm for improving vehicular performance. However, how to optimize the allocation of computation resources of both vehicles and VEC servers to reduce the energy and delay is a challenging issue when deploying the VEC systems. In this article, we try to address this issue and propose a vehicular application offloading and computational resources allocation strategy. We formulate an optimization problem and present an efficient offloading scheme for vehicular applications. Extensive simulation results are offered to analyze the performances of the proposed scheme. In comparison with the benchmark schemes, the proposed scheme can outperform them in terms of computation cost.

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Section: Discussionmentioning

confidence: 99%

Computational Resources Allocation and Vehicular Application Offloading in VEC Networks

Gu¹,

Yang²,

et al. 2022

Electronics

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“…Another challenge is that the massive deployment of IRS to form HetNets would require optimized techniques to serve multiple data streams. A centralized coordination for the IRS-assisted HetNets and transceivers need continuous channel training for learning the CSI [ 44 , 109 ].…”

Section: Conclusion Future Work and Limitationmentioning

confidence: 99%

Design and Application of Intelligent Reflecting Surface (IRS) for Beyond 5G Wireless Networks: A Review

Okogbaa

Ahmed

Khan

et al. 2022

Sensors

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The existing sub-6 GHz band is insufficient to support the bandwidth requirement of emerging data-rate-hungry applications and Internet of Things devices, requiring ultrareliable low latency communication (URLLC), thus making the migration to millimeter-wave (mmWave) bands inevitable. A notable disadvantage of a mmWave band is the significant losses suffered at higher frequencies that may not be overcome by novel optimization algorithms at the transmitter and receiver and thus result in a performance degradation. To address this, Intelligent Reflecting Surface (IRS) is a new technology capable of transforming the wireless channel from a highly probabilistic to a highly deterministic channel and as a result, overcome the significant losses experienced in the mmWave band. This paper aims to survey the design and applications of an IRS, a 2-dimensional (2D) passive metasurface with the ability to control the wireless propagation channel and thus achieve better spectral efficiency (SE) and energy efficiency (EE) to aid the fifth and beyond generation to deliver the required data rate to support current and emerging technologies. It is imperative that the future wireless technology evolves toward an intelligent software paradigm, and the IRS is expected to be a key enabler in achieving this task. This work provides a detailed survey of the IRS technology, limitations in the current research, and the related research opportunities and possible solutions.

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“…The IRS not only backscatters its own data (secondary data) that can come from embedded sensors and similar devices but also passively reflects the AP signals (primary data) [1], [2]. This capability is helpful in smart homes, smart cities, and Internet of Things (IoT) networks, where heterogeneous sensors [3], network technologies, and communication protocols improve energy efficiency, spectral efficiency, and other metrics. Although ambient backscatter communication (AmBC) may achieve the same task, strong direct-link interference greatly impacts the backscatter signal detection [4].…”

Section: Introductionmentioning

confidence: 99%

IRS-Enabled Backscattering in a Downlink Non-Orthogonal Multiple Access System

et al. 2022

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Intelligent reflecting surface (IRS)-enabled backscatter communications can be enabled by an access point (AP) that splits its transmit signal into modulated and unmodulated parts. This letter integrates non-orthogonal multiple access (NOMA) with this method to create a twouser primary system and a secondary system of IRS data. Considering the decoding order, we maximize the rate of the strongest primary user by jointly optimizing the IRS phase shifts, power splitting (PS) factor at the AP, and NOMA power coefficients while guaranteeing the quality of service (QoS) for both weak user and IRS data in the primary and secondary systems, respectively. The resulting optimization problem is non-convex. Thus, we split it into three parts and develop an alternating optimization (AO) algorithm. The advantage is that we derive closed-form solutions for the PS factor and NOMA power coefficients in the first two parts. In the third part, we optimize the phase shifts by exploiting semi-definite relaxation (SDR) and penalty techniques to handle the unit-modulus constraints. This algorithm achieves substantial gains (e.g., 40-68%) compared to relevant baseline schemes.

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Robust Max-Min Energy Efficiency for RIS-Aided HetNets With Distortion Noises

Cited by 93 publications

References 54 publications

Computational Resources Allocation and Vehicular Application Offloading in VEC Networks

Computational Resources Allocation and Vehicular Application Offloading in VEC Networks

Design and Application of Intelligent Reflecting Surface (IRS) for Beyond 5G Wireless Networks: A Review

IRS-Enabled Backscattering in a Downlink Non-Orthogonal Multiple Access System

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