采用時(shí)域聯(lián)合稀疏恢復(fù)的多輸入多輸出水聲信道壓縮感知估計(jì)
doi: 10.11999/JEIT151158
基金項(xiàng)目:
國(guó)家自然科學(xué)基金(11274259, 11574258),福建省自然科學(xué)基金(2015J01172)
Compressed Sensing Estimation of Underwater Acoustic MIMO Channels Based on Temporal Joint Sparse Recovery
Funds:
The National Natural Science Foundation of China (11274259, 11574258), The Natural Science Foundation of Fujian Province, China (2015J01172)
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摘要: 多輸入多輸出(MIMO)水聲通信技術(shù)可以在極其有限的水聲信道頻帶資源內(nèi)提高信道容量,但多徑和同道干擾的同時(shí)存在,使傳統(tǒng)信道估計(jì)算法如最小二乘算法、壓縮感知估計(jì)算法的性能急劇下降??紤]到通信數(shù)據(jù)塊間水聲信道多徑結(jié)構(gòu)存在一定的相關(guān)性,該文利用這種數(shù)據(jù)塊間多徑結(jié)構(gòu)的時(shí)間域相關(guān)性建立水聲MIMO信道的時(shí)域聯(lián)合稀疏模型,并利用同步正交匹配追蹤算法進(jìn)行多個(gè)數(shù)據(jù)塊聯(lián)合稀疏恢復(fù)信道估計(jì),提高M(jìn)IMO信道多徑稀疏位置的檢測(cè)增益并抑制同道干擾,提高水聲MIMO信道的估計(jì)性能。仿真和MIMO水聲通信海試實(shí)驗(yàn)表明了所提方法的有效性。
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關(guān)鍵詞:
- MIMO水聲信道估計(jì) /
- 同道干擾 /
- 分布式壓縮感知 /
- 同步正交匹配追蹤
Abstract: Multiple-Input-Multiple-Output (MIMO) under water acoustic communication is capable of improving the channel capacity in extremely limited bandwidth. However, the performance of traditional channel estimation algorithms, such as Least Squares (LS) method, Compressed Sensing (CS) method decreases rapidly because of the simultaneous presence of the Co-channel Interference (CoI) and multipath. As the sparse multipath structures between adjacent data blocks exhibit temporal correlation features, in this paper, the temporal correlation of sparse multipath structures is exploited to establish temporal joint sparse MIMO channel estimation model, and the Simultaneous Orthogonal Matching Pursuit (SOMP) algorithm is utilized for compressed sensing estimation of MIMO channels. Simulation and sea trial results validate the effectiveness of the proposed method. -
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