Robust Design for Intelligent Reflecting Surfaces Assisted MISO Systems

Zhang, Jiezhi; Zhang, Yu; Zhong, Caijun; Zhang, Zhaoyang

doi:10.1109/lcomm.2020.3002557

Cited by 88 publications

(62 citation statements)

References 16 publications

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“…In further work, we will estimate the instantaneous channel state information of the eavesdropping links, at least the statistical channel state information of the eavesdropping links, to estimate the secrecy data rate for the considered system. Moreover, we will integrate some other wireless transmission techniques such as the intelligent reflecting surfaces [39], [40] into the considered MEC networks, to further reduce the latency and EnC.…”

Section: Discussionmentioning

confidence: 99%

Intelligent Mobile Edge Computing Networks for Internet of Things

Chen

Kuang

Zhu³

et al. 2021

IEEE Access

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In this work, an intelligent mobile edge computing (MEC) network is studied for Internet of Things (IoT) in the presence of eavesdropping environments, where there are multiple users who can offload their confidential tasks to the computational access point (CAP) for the assistance of computation. One unmanned aerial vehicle (UAV) attacker exists in the system and it can listen to the confidential data transmission from the users to the CAP. We optimize the system design of the intelligent MEC network, by adaptively allocating the offloading ratio and wireless bandwidth, to reduce the linearly weighted cost of the latency as well as energy consumption (EnC). Specifically, starting from the deep reinforcement learning, we devise a deep Q-network (DQN) network to adjust the offloading ratio and transmission bandwidth, which can help calculate the computational tasks and suppress the eavesdropping from the UAV efficiently. We finally provide some simulation results to validate the proposed offloading strategy. In particular, the proposed offloading strategy can achieve a much lower cost compared to the conventional ones, in the terms of latency and EnC.INDEX TERMS Deep reinforcement learning, Internet of Things, mobile edge computing, task offloading, unmanned aerial vehicles.

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Section: Discussionmentioning

confidence: 99%

Intelligent Mobile Edge Computing Networks for Internet of Things

Chen

Kuang

Zhu³

et al. 2021

IEEE Access

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“…Algorithm 1 Alternating optimization algorithm 1: Initialization : Given feasible initial solutions φ 0 , f 0 and the iteration index i = 0. 2: repeat 3: For given transmit beam f i , calculate the optimal phase shift beam accoring to (14), which yields φ i+1 . 4:…”

Section: Joint Design Of the Transmit Beam And Phase Shift Beammentioning

confidence: 99%

“…To fully realize the potential of IRS, the availability of channel state information (CSI) is crucial [14]. However, owing to the passive architecture of the IRS as well as its massive number of reflecting elements, the acquisition of CSI is a challenging task.…”

Section: Introductionmentioning

confidence: 99%

Statistical CSI based design for intelligent reflecting surface assisted MISO systems

Wang

Zhong

2020

Sci. China Inf. Sci.

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This paper considers an intelligent reflecting surface (IRS) aided multiple-input single-output communication system, where statistical channel state information (CSI) is exploited for transmit beamforming and IRS beamforming. A tight upper bound is derived for the ergodic capacity of the system. Based on which, the joint optimization of transmit beam and IRS beam are studied. Depending on whether a line-of-sight path exists between the access point and user, two different cases, namely, Rician fading and Rayleigh fading, are separately treated. Specifically, for the Rician fading case, an iterative algorithm is proposed, which is guaranteed to converge. For the Rayleigh fading case, closed-form designs are obtained for the transmit beam and IRS beam. Simulation results show the proposed beamforming scheme achieves similar performance as the benchmark algorithm requiring instantaneous CSI.

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“…2) Channel Estimation Error: According to [47], the estimated complex channel coefficient h 1 is expressed as…”

Section: E Estimation Error Modelmentioning

confidence: 99%

Joint beamforming for intelligent reflecting surface aided wireless communication using statistical CSI

Dang

Zhang

2020

China Commun.

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Intelligent reflecting surface (IRS) is a novel burgeoning concept, which possesses advantages in enhancing wireless communication and user localization, while maintaining low hardware cost and energy consumption. Herein, we establish an IRS-aided mmWave-MIMO based joint localization and communication system (IMM-JLCS), and probe into its performance evaluation and optimization design.Specifically, first, we provide the signal, channel and estimation error models, and contrive the working process of the IMM-JLCS in detail. Then, by configuring appropriate IRS phase shifts, we derive the closed-form expressions of the Cramér-Rao Lower Bound (CRLB) of the position/orientation estimation errors and the effective achievable data rate (EADR), with respect to the time allocation ratio of the beam alignment and localization stage (BALS). Subsequently, we investigate the trade-off between the two performance metrics, for which we propose a joint optimization algorithm. Finally, we carry out simulations and comparisons to view the trade-off and validate the effectiveness of the proposed algorithm, in the presence of distinct levels of estimation uncertainty and user mobility. Our results demonstrate that the proposed algorithm can find the joint optimal solution for the position/orientation estimation accuracy and EADR, with its optimization performance being robust to slight localization or channel estimation errors and user mobility.

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Robust Design for Intelligent Reflecting Surfaces Assisted MISO Systems

Cited by 88 publications

References 16 publications

Intelligent Mobile Edge Computing Networks for Internet of Things

Intelligent Mobile Edge Computing Networks for Internet of Things

Statistical CSI based design for intelligent reflecting surface assisted MISO systems

Joint beamforming for intelligent reflecting surface aided wireless communication using statistical CSI

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