Beamspace Joint Azimuth, Elevation, and Delay Estimation for Large-Scale MIMO-OFDM System

算法 计算机科学 方位角 多输入多输出 正交频分复用 计算复杂性理论 多径传播 离散傅里叶变换(通用) 频道(广播) 分数阶傅立叶变换 数学 傅里叶变换 电信 傅里叶分析 数学分析 几何学
作者
Ziqiang Wang,Lei Xie,Qun Wan
出处
期刊:IEEE Transactions on Instrumentation and Measurement [Institute of Electrical and Electronics Engineers]
卷期号:72: 1-12 被引量:3
标识
DOI:10.1109/tim.2023.3270972
摘要

Due to the capability to separate the line-of-sight signal from multipath signals in both time-space domains, the joint azimuth, elevation angle and time delay estimation technique is of great importance in the Internet of Things. However, as mainstream devices develop toward the large-scale multiple-input and multiple-output (MIMO) system, real-time processing gradually becomes computationally impractical for traditional element-space three-dimensional (3-D) joint angle and delay estimation (JADE) methods. In this paper, based on the measured channel state information acquired from a large-scale uniform rectangular array-orthogonal frequency division multiplexing (OFDM) system, a computationally efficient 3-D beamspace JADE algorithm is proposed. Firstly, we develop a method to select the beam that contains the line-of-sight path as the optimal beam. Then, for the parameter estimation, we transform the channel state information into the beamspace by utilizing the discrete Fourier transform sequence, and propose a modified 3-D beamspace matrix pencil (MP) algorithm only with the optimal beam and its adjacent beams, which contributes to conspicuous computational savings. Moreover, the estimation of delay, elevation and azimuth for the line-of-sight path are paired automatically with only one eigenvalue decomposition, and the multi-dimensional grid search is avoided. Experiment results demonstrate that the proposed approach could correctly select the optimal beam with high probability, and its parameter estimation accuracy is superior to the state-of-the-art JADE techniques while significantly reducing the computational complexity.
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
更新
大幅提高文件上传限制,最高150M (2024-4-1)

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
kk发布了新的文献求助10
1秒前
asdfghjkl完成签到,获得积分10
2秒前
3秒前
锅子碗XXX完成签到,获得积分10
3秒前
ymy123发布了新的文献求助10
4秒前
4秒前
5秒前
6秒前
沐风完成签到,获得积分20
6秒前
现代含之颂晴空应助1651616采纳,获得10
6秒前
6秒前
踏实的幻珊完成签到 ,获得积分10
7秒前
8秒前
8秒前
ws驳回了李健应助
10秒前
10秒前
11秒前
11秒前
加油呀发布了新的文献求助10
11秒前
Bobo发布了新的文献求助10
12秒前
12秒前
星辰大海应助ccc采纳,获得10
12秒前
沐风发布了新的文献求助30
13秒前
jwhardaway完成签到,获得积分10
13秒前
jayus发布了新的文献求助10
14秒前
木森完成签到,获得积分10
14秒前
15秒前
卷卷发布了新的文献求助10
15秒前
15秒前
jwhardaway发布了新的文献求助30
16秒前
18秒前
汉堡包应助孑轸采纳,获得10
20秒前
21秒前
尘羽临风发布了新的文献求助10
21秒前
wml完成签到,获得积分10
23秒前
懒羊羊大王完成签到,获得积分10
23秒前
萧水白应助修辞采纳,获得10
24秒前
nullsci完成签到,获得积分10
25秒前
高分求助中
The late Devonian Standard Conodont Zonation 2000
Nickel superalloy market size, share, growth, trends, and forecast 2023-2030 2000
The Lali Section: An Excellent Reference Section for Upper - Devonian in South China 1500
Very-high-order BVD Schemes Using β-variable THINC Method 870
Mantiden: Faszinierende Lauerjäger Faszinierende Lauerjäger 800
PraxisRatgeber: Mantiden: Faszinierende Lauerjäger 800
A new species of Coccus (Homoptera: Coccoidea) from Malawi 500
热门求助领域 (近24小时)
化学 医学 生物 材料科学 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 基因 遗传学 催化作用 物理化学 免疫学 量子力学 细胞生物学
热门帖子
关注 科研通微信公众号,转发送积分 3256273
求助须知:如何正确求助?哪些是违规求助? 2898535
关于积分的说明 8301409
捐赠科研通 2567721
什么是DOI,文献DOI怎么找? 1394646
科研通“疑难数据库(出版商)”最低求助积分说明 652913
邀请新用户注册赠送积分活动 630557