Channel Estimation for RIS-Aided Multiuser Millimeter-Wave Systems

频道(广播) 计算机科学 极高频率 信号处理 电信 电子工程 声学 雷达 物理 工程类
作者
Gui Zhou,Cunhua Pan,Hong Ren,Petar Popovski,A. Lee Swindlehurst
出处
期刊:IEEE Transactions on Signal Processing [Institute of Electrical and Electronics Engineers]
卷期号:70: 1478-1492 被引量:141
标识
DOI:10.1109/tsp.2022.3158024
摘要

Channel estimation in the RIS-aided massive multiuser multiple-input single-output (MU-MISO) wireless communication systems is challenging due to the passive feature of RIS and the large number of reflecting elements that incur high channel estimation overhead. To address this issue, we propose a novel cascaded channel estimation strategy with low pilot overhead by exploiting the sparsity and the correlation of multiuser cascaded channels in millimeter-wave massive MISO systems. Based on the fact that the phsical positions of the BS, the RIS and users may not change in several or even tens of consecutive channel coherence blocks, we first estimate the full channel state information (CSI) including all the angle and gain information in the first coherence block, and then only re-estimate the channel gains in the remaining coherence blocks with much less pilot overhead. In the first coherence block, we propose a two-phase channel estimation method, in which the cascaded channel of one typical user is estimated in Phase I based on the linear correlation among cascaded paths, while the cascaded channels of other users are estimated in Phase II by utilizing the partial CSI of the common base station (BS)-RIS channel obtained in Phase I. The total theoretical minimum pilot overhead in the first coherence block is $8J-2+(K-1)\left\lceil (8J-2)/L\right\rceil $, where $K$, $L$ and $J$ denote the numbers of users, paths in the BS-RIS channel and paths in the RIS-user channel, respectively. In each of the remaining coherence blocks, the minimum pilot overhead is $JK$. Moreover, the training phase shift matrices at the RIS are optimized to improve the estimation performance.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
刚刚
1秒前
1秒前
2秒前
葛辉辉发布了新的文献求助10
2秒前
2秒前
共享精神应助baobaonaixi采纳,获得10
2秒前
半颗橙子发布了新的文献求助10
2秒前
3秒前
shimmery完成签到,获得积分10
4秒前
咔咔完成签到 ,获得积分20
4秒前
superworm1发布了新的文献求助10
4秒前
4秒前
hy发布了新的文献求助10
4秒前
舒心赛凤完成签到,获得积分10
4秒前
菠菜菜str完成签到,获得积分10
6秒前
悟空发布了新的文献求助10
6秒前
优雅山柏发布了新的文献求助10
6秒前
6秒前
junc发布了新的文献求助20
6秒前
memory发布了新的文献求助10
6秒前
罗曼长情雪兰完成签到,获得积分10
7秒前
酷炫板凳发布了新的文献求助10
7秒前
Sue发布了新的文献求助10
7秒前
8秒前
张先森完成签到,获得积分10
8秒前
Orange应助饭小心采纳,获得10
8秒前
jason完成签到,获得积分10
8秒前
8秒前
8秒前
糖糖完成签到,获得积分10
9秒前
小二郎应助幸福胡萝卜采纳,获得10
9秒前
9秒前
亵渎完成签到,获得积分10
9秒前
mc1220完成签到,获得积分10
10秒前
10秒前
冰刀完成签到,获得积分10
11秒前
kid1412完成签到 ,获得积分10
12秒前
LU完成签到,获得积分10
12秒前
小蘑菇应助R先生采纳,获得50
12秒前
高分求助中
Continuum Thermodynamics and Material Modelling 3000
Production Logging: Theoretical and Interpretive Elements 2700
Social media impact on athlete mental health: #RealityCheck 1020
Ensartinib (Ensacove) for Non-Small Cell Lung Cancer 1000
Unseen Mendieta: The Unpublished Works of Ana Mendieta 1000
Bacterial collagenases and their clinical applications 800
El viaje de una vida: Memorias de María Lecea 800
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 基因 遗传学 物理化学 催化作用 量子力学 光电子学 冶金
热门帖子
关注 科研通微信公众号,转发送积分 3527742
求助须知:如何正确求助?哪些是违规求助? 3107867
关于积分的说明 9286956
捐赠科研通 2805612
什么是DOI,文献DOI怎么找? 1540026
邀请新用户注册赠送积分活动 716884
科研通“疑难数据库(出版商)”最低求助积分说明 709762