|Table of Contents|

Citation:
　Fengzhong Qu,Hao Fang,Xingbin Tu,et al.Iterative Sequence Detection Combined with Channel Shortening and Sphere Decoding in Underwater Acoustic Communications[J].Journal of Marine Science and Application,2024,(1):238-246.[doi:10.1007/s11804-024-00387-5]
Click and Copy

Iterative Sequence Detection Combined with Channel Shortening and Sphere Decoding in Underwater Acoustic Communications

Info

Title:
Iterative Sequence Detection Combined with Channel Shortening and Sphere Decoding in Underwater Acoustic Communications
Author(s):
Fengzhong Qu1; 2; 3;  Hao Fang1; 2;  Xingbin Tu1; 2;  Yan Wei1; 2;  Minhao Zhang1; 2;  Shaojian Yang1; 2
Affilations:
Author(s):
Fengzhong Qu1; 2; 3;  Hao Fang1; 2;  Xingbin Tu1; 2;  Yan Wei1; 2;  Minhao Zhang1; 2;  Shaojian Yang1; 2
1 The Engineering Research Center of Oceanic Sensing Technology and Equipment, Ministry of Education, Zhoushan 316021, China
2 The Key Laboratory of Ocean Observation-Imaging Testbed of Zhejiang Province, Zhejiang University, Zhoushan 316021, China
3 Hainan Institute of Zhejiang University, Sanya 572025, China
Keywords:
-
分类号:
-
DOI:
10.1007/s11804-024-00387-5
Abstract:
The demand for high-data-rate underwater acoustic communications (UACs) in marine development is increasing; however, severe multipaths make demodulation a challenge. The decision feedback equalizer (DFE) is one of the most popular equalizers in UAC; however, it is not the optimal algorithm. Although maximum likelihood sequence estimation (MLSE) is the optimal algorithm, its complexity increases exponentially with the number of channel taps, making it challenging to apply to UAC. Therefore, this paper proposes a complexity-reduced MLSE to improve the bit error rate (BER) performance in multipath channels. In the proposed algorithm, the original channel is first shortened using a channel-shortening method, and several dominant channel taps are selected for MLSE. Subsequently, sphere decoding (SD) is performed in the following MLSE. Iterations are applied to eliminate inter-symbol interference caused by weak channel taps. The simulation and sea experiment demonstrate the superiority of the proposed algorithm. The simulation results show that channel shortening combined with SD can drastically reduce computational complexity, and iterative SD performs better than DFE based on recursive least squares (RLS-DFE), DFE based on improved proportionate normalized least mean squares (IPNLMS-DFE), and channel estimation-based DFE (CE-DFE). Moreover, the sea experimental results at Zhairuoshan Island in Zhoushan show that the proposed receiver scheme has improved BER performance over RLS-DFE, IPNLMS-DFE, and CE-DFE. Compared with the RLS-DFE, the BER, after five iterations, is reduced from 0.007 6 to 0.003 7 in the 8–12 kHz band and from 0.151 6 to 0.114 5 in the 13–17 kHz band at a distance of 2 000 m. Thus, the proposed algorithm makes it possible to apply MLSE in UAC in practical scenarios.

References:

Barhumi I, Moonen M (2009) MLSE and MAP equalization for transmission over doubly selective channels.IEEE Transactions on Vehicular Technology 58(8): 4120-4128.DOI: 10.1109/TVT.2009.2024537
Duel-Hallen A, Heegard C (1989) Delayed decision-feedback sequence estimation.IEEE Transactions on Communications 37(5): 428-436.DOI: 10.1109/26.24594
Eyuboglu MV, Qureshi SUH (1988) Reduced-state sequence estimation with set partitioning and decision feedback.IEEE Transactions on Communications 36(1): 13-20.DOI: 10.1109/26.2724
Forney GD (1972) Maximum-likelihood sequence estimation of digital sequences in the presence of intersymbol interference.IEEE Transactions on Information Theory 18(3): 363-378.DOI: 10.1109/TIT.1972.1054829
Gerstacker WH, Schober R (2002) Equalization concepts for EDGE.IEEE Transactions on Wireless Communications 1(1): 190-199.DOI: 10.1109/7693.975457
Kurniawan D, Arifianto MS, Kurniawan A (2019) Low complexity MIMO-SCMA detector.2019 IEEE 5th International Conference on Wireless and Telematics (ICWT), Yogyakarta, Indonesia, 1-5.DOI: 10.1109/ICWT47785.2019.8978244
Li W, Preisig JC (2007) Estimation of rapidly time-varying sparse channels.IEEE Journal of Oceanic Engineering 32(4): 927-939.DOI: 10.1109/JOE.2007.906409
Martin RK, Ding M, Evans BL, Johnson CR (2004) Infinite length results and design implications for time-domain equalizers.IEEE Transactions on Signal Processing 52(1): 297-301.DOI: 10.1109/TSP.2003.820064
Melsa PJW, Younce RC, Rohrs CE (1996) Impulse response shortening for discrete multitone transceivers.IEEE Transactions on Communications 44(12): 1662-1672.DOI: 10.1109/26.545896
Miller CL, Taylor DP, Gough PT (2001) Estimation of co-channel signals with linear complexity.IEEE Transactions on Communications 49(11): 1997-2005.DOI: 10.1109/26.966076
Myburgh HC, Olivier JC (2008) Near-optimal low complexity MLSE equalization.2008 IEEE Wireless Communications and Networking Conference, Las Vegas, 226-230.DOI: 10.1109/WCNC.2008.45
Niu Kai, Chen Kai, Lin Jiaru (2014) Low-complexity sphere decoding of polar codes based on optimum path metric.IEEE Communications Letters 18(2): 332-335.DOI: 10.1109/LCOMM.2014.010214.131826
Pajovic M, Preisig JC (2015) Performance analysis and optimal design of multichannel equalizer for underwater acoustic communications.IEEE Journal of Oceanic Engineering 40(4): 759-774.DOI: 10.1109/JOE.2015.2469935
Qin Zhen, Tao Jun, Han X (2020) Sparse direct adaptive equalization based on proportionate recursive least squares algorithm for multipleinput multiple-output underwater acoustic communications.The Journal of the Acoustical Society of America 148(4): 2280-2287
Qu Fengzhong, Chen Xiang, Deng Pan, Yang Liuqing (2010) Iterative MLSE for MIMO underwater acoustic channels.2010 OCEANS MTS/IEEE SEATTLE, 1-5.DOI: 10.1109/OCEANS.2010.5664399
Rouseff D, Jackson DR, Fox WLJ, Jones CD, Ritcey JA, Dowling DR (2001) Underwater acoustic communication by passive-phase conjugation: Theory and experimental results.IEEE Journal of Oceanic Engineering 26(4): 821-831.DOI: 10.1109/48.972122
Roy S, Duman TM, Mcdonald V, Proakis JG (2007) High-rate communication for underwater acoustic channels using multiple transmitters and space-time coding: Receiver structures and experimental results.IEEE Journal of Oceanic Engineering 32(3): 663-688.DOI: 10.1109/JOE.2007.899275
Song HC (2016) An overview of underwater time-reversal communication.IEEE Journal of Oceanic Engineering 41(3): 644-655.DOI: 10.1109/JOE.2015.2461712
Stojanovic M, Catipovic J, Proakis JG (1993) Adaptive multichannel combining and equalization for underwater acoustic communications.Journal of the Acoustical Society of America 94(3): 1621-1631.DOI: 10.1121/1.408135
Stojanovic M, Preisig J (2009) Underwater acoustic communication channels: Propagation models and statistical characterization.IEEE Communications Magazine 47(1): 84-89.DOI: 10.1109/MCOM.2009.4752682
Turner J, Taylor DP (2009) Reduced complexity decoding of space time trellis codes in the frequency selective channel.IEEE Transactions on Communications 57(3): 635-640.DOI: 10.1109/TCOMM.2009.03.070031
Vikalo H, Hassibi B, Mitra U (2006) Sphere-constrained ML detection for frequency-selective channels.IEEE Transactions on Communications 54(7): 1179-1183.DOI: 10.1109/TCOMM.2006.877946
Viterbi AJ (2006) A personal history of the Viterbi algorithm.IEEE Signal Processing Magazine 23(4): 120-142.DOI: 10.1109/MSP.2006.1657823
Wang Longbao, Tao Jun, Zheng YR (2012) Single-carrier frequencydomain turbo equalization without cyclic prefix or zero padding for underwater acoustic communications.Journal of the Acoustical Society of America 132(6): 3809-3817.DOI: 10.1121/1.4763987
Wang Taotao, Lv Tiejun, Gao Hui (2011).Sphere decoding based multiple symbol detection for differential space-time block coded ultra-wideband systems.IEEE Communications Letters 15(3): 269-271.DOI: 10.1109/LCOMM.2010.011011.101877
Wu Xiaofu, Sun Songgeng (1998) Reduced-state sequence estimator for ISI channels aided by dual decision feedback equalizer.1998 International Conference on Communication Technology, Beijing, 124-127.DOI: 10.1109/ICCT.1998.743.108
Yang TC (2004) Differences between passive-phase conjugation and decision-feedback equalizer for underwater acoustic communications.IEEE Journal of Oceanic Engineering 29(2): 472-487.DOI: 10.1109/JOE.2004.827122

Memo

Memo:
Received date:2022-12-14;Accepted date:2023-03-20。
Foundation item:Supported by the National Natural Science Foundation of China under Grant Nos. 62101489, 62171405 and 62225114.
Corresponding author:Xingbin Tu, E-mail: xbtu@zju.edu.cn
Last Update: 2024-03-19