An adaptive near-far resistant technique for the blind joint multiuser identification and detection in asynchronous CDMA systems is analyzed in fading and dispersive GSM channels.Peer ReviewedPostprint (published version

Rodríguez Fonollosa, Javier

Rodríguez Fonollosa, José Adrián

Vidal Manzano, José

Zvonar, Z

English

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Blind Multiuser Deconvolution in Fading and Dispersive Channels’ Javier R. Fonollosat, Josk A. R. Fonollosat, Zoran Zvonariand Josep Vidalt tuniversitat PoLtkcnica de Catalunya Department of Signal Theory and Communications 08034 Barcelona, SPAIN $Analog Devices Communications Division Wilmington MA 01887-1024, USA fono8tsc.upc.es Zoran.Zvonar@analog.com Abstract - A n  adapt ive  near-far resistant technique for the b l ind  joint mul t iuser  identification and detec-  t ion  in asynchronous C D M A  systems is analyzed i n  fading and dispersive GSM channels. where (M x K L )  matrix 8 [ n ]  depends of the overall dis- crete impulse response for all users and  w[n] is the nor- malized noise vector. There are N = 2 L K  possible s ta te  vectors corresponding t o  L binary symbols of K users. I.  INTRODUCTION Multiuser detection in CDMA systems usually requires either knowledge of the transmitted signature sequences and channel s ta te  information or use of a known train- ing sequence for adaptation. Consequently blind adap- tive multiuser receivers have gained considerable atten- tion [l]. We recently proposed a joint multiuser deconvo- lution scheme [a] characterized by: 0 No knowledge of timing, channel stat.e information or signatures nor use of training sequences is re- quired for any user. 0 The estimate of the signature sequence of each user convolved with its physical channel impulse re- sponse is provided after initial convergence. e T h e  blind multiuser detector is near-far resistant. T h e  purpose of this paper is t o  further investigate the behavior of this scheme in fading and dispersive channels. 11. SYSTEM MODEL We consider the asynchronous CDMA channel K n k = l  where hk(t - nT,t)  is the overall complex channel im- pulse response, given by the convolution of the signature sequence, physical radio channel and the receiving filter impulse responses. It incorporates the amplitude and the delay for user k, and its duration is assumed t o  be smaller or equal to L symbols, i.e. h k ( ~ , t )  = 0,  T < 0, T > LT,\Jt. T h e  total number of active users is K and their trans- mitted sequences are  binary independent symbols bi, [n] E (1, -1). T h e  symbol rate is 1/T and w(t)  is normalized white Gaussian noise. T h e  CDMA channel is sampled at a rate M / T  = l/Ts t o  derive the vector sequence r[n] 111. BLIND IDENTIFICATION A N D  DETECTION ALGORITHM If the overall impulse response for each user was known, tha t  is if the signature sequence, physical channel im- pulse response, amplitude and delay corresponding t o  each user were available, then using this information, the Viterbi algorithm could be employed t o  determine the multiuser maximum-likelihood transmitted sequence. In the method we presented however, the Viterbi algorithm is applied with current estimates of the overall impulse re- sponses which are updated recursively after arbitrary ini- tialization. T h e  number of users (K) is assumed known together with a bound for the impulse response dura- tion ( L ) .  A similar approach was proposed for the blind equalization of single user channels using the Viterbi al- gorithm [3]  and the Baum-Welch identification algorithm [4]. Specific t o  the multiuser approach is the procedure which overcomes the convergence t o  a local minimum [2]. Iv. BEHAVIOR IN FADING AND DISPERSIVE C H A N N E L S  The  blind multiuser algorithm has been tested using the mobile radio channel model for typical urban areas (Type 1) TUXGO, as defined in [5].  Simulations indicate tha t ,  for moderate Doppler frequency (50 Hz) and  multipath spread (1.35 symbols), convergence can still be  attained within few hundred symbols. Afterwards, the algorithm is still able t o  track slow channel variations. Possible modification of the receiver, after the initial convergence, may include a simpler decision-directed MMSE scheme. REFERENCES [l] S. Verd6, “Adaptive Multiuser Detection,” Proc. Third Inter- national Symposium on Spread Spectrum Techniques and Ap- pkcations, Oulu, Finland, pp. 43-50, July 1994. [2] J. R. Fonollosa, J. A. R. Fonollosa, Z. Zvonar, and J. Vidal, “Blind Multiuser Identification and Detection in CDMA Sys- tems,” PTOC. IEEE ICASSP-95, pp. 1876-1879, May 1995. [3] N. Seshadri, “Joint Data and Channel Estimation using Blind Trellis Search Techniques,” IEEE Trans. on Communications. ‘1. = [r (nT) ,  r ( n T S T s ) j  ’ ’ . ’ T ( n T S ( M -  ‘)*,)IT ‘ (2) vol 42, pp. 1000-1011;March 1994. [4] J. A. R. Fonollosa and J. Vidal, “Application of Hidden Markov Models to Blind Channel Characterization and Data Detec- The  observation r[n] is modeled as a probabilistic M length vector sequence of a s ta te  vector s[n] ( 3 )  tion,” Proc. IEEE ICASSP-94, pp. IV 185-188, April 1994. r[n] = X [ n ] s [ n ]  + ~ [ n ]  , [5] GSM recommendation 05.05 (version 3.11.0). Work supported by CIRIT of Catalonia (GRQ93-3021). 384 

Blind multiuser deconvolution in fading and dispersive channels

UPCommons (Universitat Politècnica de Catalunya)

An adaptive near-far resistant technique for the blind joint multiuser identification and detection in asynchronous CDMA systems is analyzed in fading and dispersive GSM channels.Peer Reviewe

UPCommons

https://upcommons.upc.edu/bitstream/2117/102596/1/00550371.pdf

Blind multiuser deconvolution in fading and dispersive channels

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