Tucker-2模型在AF MIMO中继系统的信道估计

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"基于Tucker-2模型的AF MIMO中继系统信道估计技术的研究论文" 在无线通信领域，特别是多输入多输出（MIMO）中继系统中，信道估计是实现高效通信的关键环节。本文针对MIMO中继系统的特性，提出了一种基于Tucker-2模型的信道估计新方法。作者包括来自中国传媒大学信息与工程学院的Chentao Wang、Jianhe Du、Qiaoqian Hu和Yijun Wu。 Tucker-2模型是一种高级的多维数据分析工具，通常用于处理高阶张量数据。在本文提出的方案中，源节点利用特定的信道训练序列向中继节点发送信号，这些序列在空间和时间上进行编码，形成三向空间-时间编码。在接收端，即目的地节点，接收到的信号被构造成Tucker-2模型。通过交替最小二乘（ALS）算法，可以对模型进行拟合，从而分别估计出源-中继和中继-目的地的信道矩阵。该提案的一大优点在于，它能够独立地估计源-中继和中继-目的地的信道，两个通道的估计精度互不影响，这在传统的信道估计方法中可能是一个挑战。此外，文中详细分析了所提方法的可行性，并对其性能进行了深入讨论。模拟结果证实了该提案的有效性，表明采用Tucker-2模型进行信道估计能显著提高MIMO中继系统的性能，尤其是在信道条件变化或存在噪声的情况下。这一创新技术对于提升MIMO中继系统的通信质量和可靠性具有重要意义，为未来无线通信网络的设计和优化提供了新的思路。关键词：Tucker-2模型；信道估计；多输入多输出中继系统；交替最小二乘算法；三向空间-时间编码

A Tucker-2 Model Based Channel Estimation Technique in

AF MIMO Relay Systems

Chentao Wang; Jianhe Du; Qiaoqian Hu; Yijun Wu

Communication University of China

School of Information and Engineering, Communication University of China, Beijing 100024

E-Mail: dujianhe1@gmail.com

ABSTRACT

For multiple-input multiple-output (MIMO) relay systems, we

present a Tucker-2 model based scheme for channel estimation.

The channel training sequences at the source node are transmitted

to the relay node for three-way space-time coding. Then the

received signals at the destination node are formulated as a

Tucker-2 model, and the source-relay and relay-destination

channel matrixes can be estimated by alternating least squares

(ALS) algorithm to fit this mode. At the same time, the feasibility

of the proposed approach is analyzed in detail. The proposed

scheme can preferably estimate the source-relay and relay-

destination channel matrixes. Moreover, the estimation accuracies

of source-relay and relay-destination channel are not interacted.

Simulation results indicate the effectiveness of the proposed

scheme.

Keywords

Tucker-2 model; channel estimation; relay; ALS algorithm

1. INTRODUCTION

Due to its broader coverage, higher transmission rates and

reliability in wireless channels, relay node has recently been

regarded as a promising technique [1]. In another aspect, MIMO

systems in improving transmission rates and reliability have

widely applied to research and practice. When we associate the

concept of relaying systems with that of MIMO technology [2]，

the system’s performance can be further improved by exploiting

the spatial dimension. To maximize the received signal-to-noise

ratio (SNR) or some other performance parameters, we present

several designs for the optimal relay amplifying factors [3-4]. In

any case, the advantages of a MIMO relay network can be

obtained by providing accurate channel state information (CSI)

for all links.

Relay strategies are classified into amplify-and-forward (AF) and

decode-and-forward (DF) schemes. In AF scheme, the received

signals at the relay nodes are linearly transformed, by using

simple AF processing operations, then transmit amplified signals

to the destination nodes. When relay nodes have a limited

capability of signal processing, AF scheme can reduce costs of

operation compared with DF schemes. As in the AF scheme, the

reliability of signal detection deeply relays on the accuracy of CSI

available at the receiver node. Some research works assume the

perfect CSI knowledge at the destination node for convenience.

Other channel estimation schemes are dedicated to the estimation

of the source - relay - destination (compound) channel, while it is

well-known that the CSI estimation of both source to relay and

relay to destination channels is necessary to optimize the whole

communication system.

From the wireless signal processing point of view, combining two

or more domains is one of the most common technologies. Some

algebraic models of matrix manipulation can be used at

transmitter node and/or receiver node. This technology grows

quickly because it can preserve the multidimensional nature of the

symbol data and the symbol data statistics through using of the

multilinear algebra. Compared with conventional matrix-based

technologies, the practical motivation for Multi-way signal

processing technology of communication systems comes from the

fact that it can simultaneously benefit from more than two forms

of diversity to perform channel estimation and signals separation

under model identifiability with more relaxed conditions.

New wireless communication systems based on Multi-way signal

processing technology have been studied over the past ten years

[5-6]. The tensor algebra or multilinear favors the appropriate

integration of Multi-way signal processing to those domains

whose processing strategies use the presence of redundancy of

information symbol in unsupervised and/or blind (or semi-blind)

signal estimation systems. Multi-way signal processing

technology, relying on signal special structure in code-spatial-

temporal dimension and uniqueness of decomposition, is capable

of completing signal detection and channel estimation with none

or a small amount of CSI and coding matrix through fitting multi-

way matrix model. Researches have shown that, multi-way signal

processing technology, applying to MIMO system, can further

improve communication systems’ spectral efficiency and

reliability [7-11].

There are several papers on the joint signal and channel estimation.

Sidiropoulos [7] exploited Khatri-Rao space-time codes and

proposed a joint receiver based on Parallel Factor (PARAFAC)

model. Using time-varying linear constellation precoding, De [8]

proposed a semi-blind receiver. On the basis of [7-8], De [9]

designed a semi-blind receiver, relying on space-time-frequency

codes. Du [10] proposed a semi-blind receiver in MIMO relaying

system for joint information symbols, source-relay channel and

relay-destination channel matrixes. On the basis of [10] and relay

encoding, Ximenes [11] proposed a nested PARAFAC model

based joint receiver. Above methods referring to PARAFAC

model are capable of achieving joint signal and channel

estimation effectively, but demand that data stream is equal to the

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ICCIS 2017, November 7-9, 2017, Wuhan, China

ACM ISBN 978-1-4503-5348-9/17/11…$15.00

DOI: https://doi.org/10.1145/ 3158233.3159330

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