Tian Hong-bo, Yin Qin-ye, Ding Le, Deng Ke. A Fast Algorithm of Blind Multiuser Detection Using Particle Filtering[J]. Journal of Electronics & Information Technology, 2008, 30(6): 1300-1303. doi: 10.3724/SP.J.1146.2006.01856
Citation:
Tian Hong-bo, Yin Qin-ye, Ding Le, Deng Ke. A Fast Algorithm of Blind Multiuser Detection Using Particle Filtering[J]. Journal of Electronics & Information Technology, 2008, 30(6): 1300-1303. doi: 10.3724/SP.J.1146.2006.01856
Tian Hong-bo, Yin Qin-ye, Ding Le, Deng Ke. A Fast Algorithm of Blind Multiuser Detection Using Particle Filtering[J]. Journal of Electronics & Information Technology, 2008, 30(6): 1300-1303. doi: 10.3724/SP.J.1146.2006.01856
Citation:
Tian Hong-bo, Yin Qin-ye, Ding Le, Deng Ke. A Fast Algorithm of Blind Multiuser Detection Using Particle Filtering[J]. Journal of Electronics & Information Technology, 2008, 30(6): 1300-1303. doi: 10.3724/SP.J.1146.2006.01856
Considering the computational complexity of particle filtering, based on the time-observation state space model, a new fast algorithm with low computational complexity is developed for DS-CDMA blind multiuser detection using particle filtering in synchronous systems over flat and fast fading channels. This algorithm classifies the particles when its number exceeds the threshold, and the probability difference of different particles is taken as the criterion whether the particles number is enough, and then the particles number under different circumstance is adjusted adaptively; meanwhile the performance of blind multiuser detection under distinct probability difference of different particles is discussed. Simulation results confirm that this algorithm effectively decreases computational complexity and well remains the performance of blind multiuser detection, meanwhile the performance in proportion to the probability difference.
Hammersley J M and Morton K W. Poor mans Monte Carlo.J of the Royal Statistical Society B, 1954, 16(1): 23-38.[2]Gordon N and Salmond D. Novel approach to non-linear andnon-Gaussian Bayesian state estimation. Proc. of InstituteElectric Engineering, 1993, 140(2): 107-113.[3]Chen R, Wang X, and Liu J S. Adaptive joint detection anddecoding in flat-fading channels via mixture Kalman filtering[J].IEEE Trans. on Information Theory.2000, 46(6):2079-2094[4]Zhang J and Djuric P M. Joint estimation and decoding ofspacetime trellis codes. EURASIP Journal on Applied SignalProcessing, 2002, 2002(3): 305-315.[5]Punskaya E, Andrieu C, and Doucet A, et al.. Particlefiltering for multiuser detection in fading CDMA channels.Proc. 11th IEEE Signal Processing Workshop, Piscataway,USA, 2001: 38-41.[6]Wang X and Poor V. Blind multiuser detection: A subspaceapproach[J].IEEE Trans. on Information Theory.1998, 44(2):677-690[7]Fawer U and Aazhang B. A multiuser receiver for codedivisionmultiple access communications over multipathchannels[J].IEEE Trans. on Communications.1995, 43(2/3/4):1556-1565[8]Tugnait J K and Li Tongtong. Blind asynchronous multiuserCDMA receivers for ISI channels using code-aided CMA.IEEE Trans. on Communications, 2001, 19(8):1520-1530.[9]Huang Y.[J].Zhang J, and Djuric P M. Adaptive BlindMultiuser Detection over Flat Fast Fading Channels usingParticle Filtering. IEEE Global TelecommunicationsConference, Piscataway, USA.2004,:-[10]Huang, Zhang Y J, and Djuric P M. Bayesian detection forBLAST. IEEE Trans. on Signal Processing. 2005, 53(3):1086-1096.[11]Huang Y and Djuric P M. A blind particle filtering detectorof signals transmitted over flat fading channels[J].IEEE Trans.on Signal Processing.2004, 52(7):1891-1900