User Selection for MIMO Downlink With Digital and Hybrid Maximum Ratio Transmission

Wang, Zhaoyang; Cao, Yang; Zhang, Dongchen; Hua, Xinhai; Gao, Peng; Jiang, Tao

doi:10.1109/tvt.2021.3110726

Cited by 10 publications

(2 citation statements)

References 18 publications

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“…There are many explanations as to why retransmission occurs, such as multipath effects [ 5 ], radio frequency interference, low SNR, hidden terminal, near/far effects [ 6 ], power mismatch and adjacent-channel interference [ 7 ], which can all lead to retransmission. Although the multipath phenomenon is a serious problem in traditional 802.11a/b/g devices, with the emergence of 802.11n technology and the application of MIMO (Multiple-Input Multiple-Output) and MRC (Maximum-Ratio Combining) [ 8 ] signal processing technology, multipath phenomenon has actually had a positive impact on system throughput. The method of using CSMA/CA media access can effectively avoid near/far effects.…”

Section: Introductionmentioning

confidence: 99%

Environment-Aware Rate Adaptation Based on Occasional Request and Robust Adjustment in 802.11 Networks

Yu,

Wang,

Song

et al. 2023

Sensors

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The IEEE 802.11 standard provides multi-rate support for different versions. As there is no specification on the dynamic strategy to adjust the rate, different rate adaptation algorithms are applied according to different manufacturers. Therefore, it is often hard to interpret the performance discrepancy of various devices. Moreover, the ever-changing channels always challenge the rate adaptation, especially in the scenario with scarce spectrum and low SNR. As a result, it is important to sense the radio environment cognitively and reduce the unnecessary oscillation of the transmission rate. In this paper, we propose an environment-aware robust (EAR) algorithm. This algorithm employs an occasional small packet, designs a rate scheme adaptive to the environment, and enhances the robustness. We verify the throughput of EAR using network simulator NS-3 in terms of station number, motion speed and node distance. We also compare the proposed algorithm with three benchmark methods: AARF, RBAR and CHARM. Simulation results demonstrate that EAR outperforms other algorithms in several wireless environments, greatly improving the system robustness and throughput.

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Section: Introductionmentioning

confidence: 99%

Environment-Aware Rate Adaptation Based on Occasional Request and Robust Adjustment in 802.11 Networks

Yu,

Wang,

Song

et al. 2023

Sensors

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show abstract

“…However, the channel estimation can have low accuracy due to the poor quality of the received signal in the acquisition of shared random source, introducing a high key inconsistency rate and low key entropy after quantization. In [11], the authors consider the scenario that the base station uses the maximum ratio transmission (MRT) to maximize the SNR of the received signal, but this scheme results in limited improvement of the SNR. We also use preprocessing methods to remove the non-reciprocity caused by noise.…”

Section: Introductionmentioning

confidence: 99%

Intelligent Reflecting Surface–Assisted Wireless Secret Key Generation against Multiple Eavesdroppers

Liu

Huang

Sun

et al. 2022

Entropy

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In this paper, we propose an improved physical layer key generation scheme that can maximize the secret key capacity by deploying intelligent reflecting surface (IRS) near the legitimate user aiming at improving its signal-to-noise ratio (SNR). We consider the scenario of multiple input single output (MISO) against multiple relevant eavesdroppers. We elaborately design and optimize the reflection coefficient matrix of IRS elements that can improve the legitimate user’s SNR through IRS passive beamforming and deteriorate the channel quality of eavesdroppers at the same time. We first derive the lower bound expression of the achievable key capacity, then solve the optimization problem based on semi-definite relaxation (SDR) and the convex–concave procedure (CCP) to maximize the secret key capacity. Simulation results show that our proposed scheme can significantly improve the secret key capacity and reduce hardware costs compared with other benchmark schemes.

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Joint Subchannel Allocation and Beamforming for Multicast in Ultra-Dense LEO Backbone Network

Qian

Qin

et al. 2022

GLOBECOM 2022 - 2022 IEEE Global Communications Conference

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User Selection for MIMO Downlink With Digital and Hybrid Maximum Ratio Transmission

Cited by 10 publications

References 18 publications

Environment-Aware Rate Adaptation Based on Occasional Request and Robust Adjustment in 802.11 Networks

Environment-Aware Rate Adaptation Based on Occasional Request and Robust Adjustment in 802.11 Networks

Intelligent Reflecting Surface–Assisted Wireless Secret Key Generation against Multiple Eavesdroppers

Joint Subchannel Allocation and Beamforming for Multicast in Ultra-Dense LEO Backbone Network

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