谷歌浏览器插件
订阅小程序
在清言上使用

Low-Latency Retro-Reflective Beam Training for RIS-Assisted Cellular Systems.

WCNC(2023)

引用 0|浏览1
暂无评分
摘要
To compensate for high pathloss and improve coverage in millimeter-wave (mmWave) frequencies, highly directional transmit (Tx) and receive (Rx) beamforming is required. In addition, mmWave frequencies are extremely susceptible to blockages, and when blockage occurs, the link between Tx and Rx may be terminated and an alternate path is required to retain communication. Reconfigurable intelligent surface (RIS) can be considered as a possible solution to not only solve the blockage problem but also to cover dead spots. However, using conventional exhaustive search protocol, the overhead of beam training increases exponentially with the number of RIS reflective beams, as it requires finding the optimal beam pair in the Tx-RIS-Rx link. In this paper, a low-latency retro-reflective (LLRR) beam training protocol for RIS-assisted cellular system is proposed to reduce the overall beam training time by reflecting the RIS beams to the source. Furthermore, the feasibility of the RIS element to provide 180. phase shift is analyzed. Simulation results show that the proposed LLRR beam training significantly reduces the training time compared to the state-of-the-art and achieves gains of approximate to 1.5 bps/Hz and approximate to 9.8 bps/Hz at signal-to-noise ratio of 15 dB when the number of beams at RIS is 64 and 256, respectively.
更多
查看译文
关键词
5G, 6G, beam training, milliter-wave, reconfigurable intelligent surface, retro reflective
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要