An improved list sphere decoder （ILSD） is proposed based on the conventional list sphere decoder （LSD） and the reduced- complexity maximum likelihood sphere-decoding algorithm. Unlike the conventional LSD with fix...An improved list sphere decoder （ILSD） is proposed based on the conventional list sphere decoder （LSD） and the reduced- complexity maximum likelihood sphere-decoding algorithm. Unlike the conventional LSD with fixed initial radius, the ILSD adopts an adaptive radius to accelerate the list cdnstruction. Characterized by low-complexity and radius-insensitivity, the proposed algorithm makes iterative joint detection and decoding more realizable in multiple-antenna systems. Simulation results show that computational savings of ILSD over LSD are more apparent with more transmit antennas or larger constellations, and with no performance degradation. Because the complexity of the ILSD algorithm almost keeps invariant with the increasing of initial radius, the BER performance can be improved by selecting a sufficiently large radius.展开更多
Various efficient generalized sphere decoding (GSD) algorithms have been proposed to approach optimal ML performance for underdetermined linear systems, by transforming the original problem into the full-column-rank o...Various efficient generalized sphere decoding (GSD) algorithms have been proposed to approach optimal ML performance for underdetermined linear systems, by transforming the original problem into the full-column-rank one so that standard SD can be fully applied. However, their design parameters are heuristically set based on observation or the possibility of an ill-conditioned transformed matrix can affect their searching efficiency. This paper presents a better transformation to alleviate the ill-conditioned structure and provides a systematic approach to select design parameters for various GSD algorithms in order to high efficiency. Simulation results on the searching performance confirm that the proposed techniques can provide significant improvement.展开更多
This paper focuses on reducing the complexity of K-best sphere decoding （SD） algorithm for the detection of uncoded multi-ple input multiple output （MIMO） systems. The proposed algorithm utilizes the threshold-pru...This paper focuses on reducing the complexity of K-best sphere decoding （SD） algorithm for the detection of uncoded multi-ple input multiple output （MIMO） systems. The proposed algorithm utilizes the threshold-pruning method to cut nodes with partial Euclidean distances （PEDs） larger than the threshold. Both the known noise value and the unknown noise value are considered to generate the threshold, which is the sum of the two values. The known noise value is the smal est PED of signals in the detected layers. The unknown noise value is generated by the noise power, the quality of service （QoS） and the signal-to-noise ratio （SNR） bound. Simulation results show that by considering both two noise values, the proposed algorithm makes an efficient reduction while the performance drops little.展开更多
We propose a pipeline structure for Schnorr-Euchner sphere decoding algorithm in this article. It divides the search tree of the original algorithm into blocks and executes the search from block to block. When one blo...We propose a pipeline structure for Schnorr-Euchner sphere decoding algorithm in this article. It divides the search tree of the original algorithm into blocks and executes the search from block to block. When one block search of a signal is over, the part in the pipeline structure that processes this block search can load another signal and search. Several signals can be processed at the same time in one pipeline. Blocks are arranged to lower the whole complexity in the way that the previously search blocks are the blocks those have more probability to generate the final solution. Simulation experiment results show the average process delay can drop to the range from 48.77% to 60.18% in a 4-by-4 antenna system with 16QAM modulation, or from 30.31% to 61.59% in a 4-by-4 antenna system with 64QAM modulation.展开更多
Multiple Input Multiple Output (MIMO) technology is of great significance in high data rate wireless communication. The K-Best Sphere Decoding (K-Best SD) algorithm was proposed as a powerful method for MIMO detection...Multiple Input Multiple Output (MIMO) technology is of great significance in high data rate wireless communication. The K-Best Sphere Decoding (K-Best SD) algorithm was proposed as a powerful method for MIMO detection that can approach near-optimal performance. However, some extra computational complexity is contained in K-Best SD. In this paper, we propose an improved K-Best SD to reduce the complexity of conventional K-Best SD by assigning K for each level dynamically following some rules. Simulation proves that the performance degradation of the improved K-Best SD is very little and the complexity is significantly reduced.展开更多
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 ...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 RLSDFE,IPNLMS-DFE,and CE-DFE.Compared with the RLS-DFE,the BER,after five iterations,is reduced from 0.0076 to 0.0037 in the 8–12 k Hz band and from 0.1516 to 0.1145 in the 13–17 k Hz band at a distance of 2000 m.Thus,the proposed algorithm makes it possible to apply MLSE in UAC in practical scenarios.展开更多
Compared to the successive cancellation(SC)-based decoding algorithms,the sphere decoding(SD)algorithm can achieve better performance with reduced computational complexity,especially for short polar codes.In this pape...Compared to the successive cancellation(SC)-based decoding algorithms,the sphere decoding(SD)algorithm can achieve better performance with reduced computational complexity,especially for short polar codes.In this paper,we propose a new method to construct the binary polar codes with the modified multiplicative repetition(MR)-based matrix.Different from the original construction,we first design a 2×2 q-ary kernel to guarantee the single-level polarization effect.Then,by replacing the new-designed binary companion matrix,a novel strategy is further developed to enhance the polarization in the bit level,resulting in a better distance property.Finally,the SD-based Monte-Carlo(SDMC)method is used to construct MR-based binary polar codes,while the resulting codes without the butterfly pattern are decoded by the SD algorithm.Simulation results show that the proposed method with the SD algorithm can achieve a maximum performance gain of 0.27 dB compared to the original method with slightly lower complexity.展开更多
基金The National Natural Science Founda-tion of China ( No 60496316)the National Hi-Tech Re-search and Development Program (863) of China (No2006-AA01Z270)
文摘An improved list sphere decoder （ILSD） is proposed based on the conventional list sphere decoder （LSD） and the reduced- complexity maximum likelihood sphere-decoding algorithm. Unlike the conventional LSD with fixed initial radius, the ILSD adopts an adaptive radius to accelerate the list cdnstruction. Characterized by low-complexity and radius-insensitivity, the proposed algorithm makes iterative joint detection and decoding more realizable in multiple-antenna systems. Simulation results show that computational savings of ILSD over LSD are more apparent with more transmit antennas or larger constellations, and with no performance degradation. Because the complexity of the ILSD algorithm almost keeps invariant with the increasing of initial radius, the BER performance can be improved by selecting a sufficiently large radius.
文摘Various efficient generalized sphere decoding (GSD) algorithms have been proposed to approach optimal ML performance for underdetermined linear systems, by transforming the original problem into the full-column-rank one so that standard SD can be fully applied. However, their design parameters are heuristically set based on observation or the possibility of an ill-conditioned transformed matrix can affect their searching efficiency. This paper presents a better transformation to alleviate the ill-conditioned structure and provides a systematic approach to select design parameters for various GSD algorithms in order to high efficiency. Simulation results on the searching performance confirm that the proposed techniques can provide significant improvement.
基金supported by the National Natural Science Foundation of China(61071083)
文摘This paper focuses on reducing the complexity of K-best sphere decoding （SD） algorithm for the detection of uncoded multi-ple input multiple output （MIMO） systems. The proposed algorithm utilizes the threshold-pruning method to cut nodes with partial Euclidean distances （PEDs） larger than the threshold. Both the known noise value and the unknown noise value are considered to generate the threshold, which is the sum of the two values. The known noise value is the smal est PED of signals in the detected layers. The unknown noise value is generated by the noise power, the quality of service （QoS） and the signal-to-noise ratio （SNR） bound. Simulation results show that by considering both two noise values, the proposed algorithm makes an efficient reduction while the performance drops little.
文摘We propose a pipeline structure for Schnorr-Euchner sphere decoding algorithm in this article. It divides the search tree of the original algorithm into blocks and executes the search from block to block. When one block search of a signal is over, the part in the pipeline structure that processes this block search can load another signal and search. Several signals can be processed at the same time in one pipeline. Blocks are arranged to lower the whole complexity in the way that the previously search blocks are the blocks those have more probability to generate the final solution. Simulation experiment results show the average process delay can drop to the range from 48.77% to 60.18% in a 4-by-4 antenna system with 16QAM modulation, or from 30.31% to 61.59% in a 4-by-4 antenna system with 64QAM modulation.
文摘Multiple Input Multiple Output (MIMO) technology is of great significance in high data rate wireless communication. The K-Best Sphere Decoding (K-Best SD) algorithm was proposed as a powerful method for MIMO detection that can approach near-optimal performance. However, some extra computational complexity is contained in K-Best SD. In this paper, we propose an improved K-Best SD to reduce the complexity of conventional K-Best SD by assigning K for each level dynamically following some rules. Simulation proves that the performance degradation of the improved K-Best SD is very little and the complexity is significantly reduced.
基金Supported by the National Natural Science Foundation of China under Grant Nos. 62101489, 62171405 and 62225114.
文摘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 RLSDFE,IPNLMS-DFE,and CE-DFE.Compared with the RLS-DFE,the BER,after five iterations,is reduced from 0.0076 to 0.0037 in the 8–12 k Hz band and from 0.1516 to 0.1145 in the 13–17 k Hz band at a distance of 2000 m.Thus,the proposed algorithm makes it possible to apply MLSE in UAC in practical scenarios.
基金supported by the National Natural Science Foundation of China(Nos.62261003,62361003,and 61961004)the KR&DP of Guangxi(No.GuiKeAB22080048).
文摘Compared to the successive cancellation(SC)-based decoding algorithms,the sphere decoding(SD)algorithm can achieve better performance with reduced computational complexity,especially for short polar codes.In this paper,we propose a new method to construct the binary polar codes with the modified multiplicative repetition(MR)-based matrix.Different from the original construction,we first design a 2×2 q-ary kernel to guarantee the single-level polarization effect.Then,by replacing the new-designed binary companion matrix,a novel strategy is further developed to enhance the polarization in the bit level,resulting in a better distance property.Finally,the SD-based Monte-Carlo(SDMC)method is used to construct MR-based binary polar codes,while the resulting codes without the butterfly pattern are decoded by the SD algorithm.Simulation results show that the proposed method with the SD algorithm can achieve a maximum performance gain of 0.27 dB compared to the original method with slightly lower complexity.
