雙向MIMO中繼系統(tǒng)中一種低復(fù)雜度的聯(lián)合信道估計方法

杜建和; 花妍; 林和昀; 田沛

doi:10.11999/JEIT170463

雙向MIMO中繼系統(tǒng)中一種低復(fù)雜度的聯(lián)合信道估計方法

doi: 10.11999/JEIT170463

1.
(中國傳媒大學(xué)信息工程學(xué)院北京 100024)
2.
(北京郵電大學(xué)信息與通信工程學(xué)院北京 100876)

基金項目:

國家自然科學(xué)基金(61601414, 61561037)，國家高技術(shù)研究發(fā)展計劃(2015AA01A705, 2014AA01A701)

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- 文章訪問數(shù): 1319
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- 被引次數(shù): 0
出版歷程
- 收稿日期: 2017-05-16
- 修回日期: 2017-09-16
- 刊出日期: 2017-12-19

A Low-complexity Algorithm for Joint Channel Estimation in Two-way MIMO Relay Communication Systems

1.
(School of Information and Engineering, Communication University of China, Beijing 100024, China)
2.
(School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China)

Funds:

The National Natural Science Foundation of China (61601414, 61561037), The National High Technology Research and Development Program of China (2015AA01A705, 2014AA01A701)

摘要

摘要: 對于雙向多輸入多輸出(MIMO)中繼系統(tǒng)，如何在減少中繼負(fù)擔(dān)的情況下獲得精確的信道狀態(tài)信息(CSI)成為信道估計的一個難點。該文針對雙向MIMO中繼系統(tǒng)，提出一種低復(fù)雜度的聯(lián)合信道估計方法。所提方法在兩個用戶端同時發(fā)送正交信道訓(xùn)練信號至中繼，中繼采用所設(shè)計的放大因子放大所接收的信號并轉(zhuǎn)發(fā)至兩個用戶。每個用戶對所接收的信號構(gòu)造平行因子(PARAFAC)模型，并根據(jù)實際系統(tǒng)要求，分別設(shè)計了迭代和非迭代的兩種擬合算法對PARAFAC模型進(jìn)行擬合，從而聯(lián)合估計出所有信道的CSI。所提信道估計方法無需在中繼處進(jìn)行信道估計，減輕了中繼的負(fù)擔(dān)。與已有信道估計方法相比，所提方法設(shè)計靈活，采用的擬合算法具有較低的復(fù)雜度，而且在使用較少信道訓(xùn)練信號的情況下具有較高的信道估計精度。
- 雙向MIMO中繼 /
- 低復(fù)雜度 /
- 信道狀態(tài)信息 /
- 平行因子
Abstract: For two-way Multiple-Input Multiple-Output (MIMO) relay communication systems, the main challenge is to get full knowledge of all channel matrices with minimal cost of signal handling at the relay node. In this paper, a low-complexity joint channel estimation scheme for two-way MIMO relay communication systems is proposed. Both users transmit orthogonal channel training signals to the relay node simultaneously. Then the relay amplifies the received signals by using designed amplification factors, and forwards the amplified signals to both users. The received signals at each user is formulated as a PARAllel FACtor (PARAFAC) model, and then the iterative and non-iterative fitting algorithms are derived to estimate the Channel State Information (CSI) knowledge of all links involved. Compared with existing schemes, the proposed scheme has the advantages of design flexibility and low complexity, and has higher estimation accuracy with a few number of channel training signals.
- Two-way MIMO relay /
- Low-complexity /
- Channel State Information (CSI) /
- Parallel factor

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參考文獻(xiàn)(21)

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