Adaptive Space-Time Chip-Level Equalization for ... - Semantic Scholar

Adaptive Space-Time Chip-Level Equalization for WCDMA Downlink with Code-Multiplexed Pilot and Soft Handover Frederik Petr´e

Geert Leus




Luc Deneire

Marc Engels

Marc Moonen



Interuniversity Micro-Electronics Center (IMEC) - Kapeldreef 75, B-3001 Leuven - Belgium

Abstract— In the downlink of WCDMA systems, multi-path propagation destroys the orthogonality of the user signals and causes multi-user interference (MUI). Chip-level equalization can restore the orthogonality and suppress the MUI. However, adaptive implementations of the chip-level equalizer receiver that can track time-varying multi-path channels are hard to realize in practice for two reasons : loss of spectral efficiency when using a training sequence and loss of performance when using pure blind techniques. In this paper, we propose new training-based and semiblind space-time chip-level equalizer receivers for the downlink of WCDMA systems employing long spreading codes and a continuous code-multiplexed pilot. The proposed receivers exploit the presence of common pilot symbols in the so-called Common PIlot CHannel (CPICH) of the Universal Terrestrial Radio Access (UTRA) for 3G systems. Moreover, they can simultaneously track multiple base-station signals, whenever the mobile station enters soft handover mode. For both receivers, we derive a Recursive Least Squares (RLS) algorithm for adaptive processing. The proposed receivers are compared with the conventional space-time RAKE receiver and the ideal space-time chip-level equalizer receiver both in terms of performance and complexity.

I. I NTRODUCTION In the downlink of WCDMA systems, the different users are multiplexed synchronously to the transmission channel by short orthogonal spreading codes that are user specific and a long overlay scrambling code that is base-station specific. The MUI is essentialy caused by the channel, since the different user signals are distorted by the same multipath channel when propagating to the mobile station of interest. Therefore, chip-level equalization can restore the orthogonality of the user signals and suppress the MUI [1]. Ideal non-adaptive Zero-Forcing (ZF) and Minimum Mean Squared Error (MMSE) chip equalizer receivers, consisting of a linear chip-level equalizer followed by a descrambler and a despreader, have been introduced in [2], [3] and [4]. However, adaptive implementations of such chip equalizer receivers that can track time-varying multipath channels are hard to realize in practice. Current proposals use blind algorithms to determine the equalizer coefficients. One method applies a standard single-user blind channel equalization algorithm [5]. Another method, pursued in [6] and [7], makes use of the fact that, in the absence of noise, the received signal after equalization should lie in the subspace spanned by the user codes. Although these blind algorithms do not require







Also PhD student at KULeuven, E.E. Dept., with I.W.T.-scholarship Postdoctoral Fellow F.W.O., KULeuven, E.E. Dept., ESAT/SISTA Professor at KULeuven, E.E. Dept., ESAT/SISTA

any training overhead, they lead to a reduced system performance. In this paper, we propose new training-based and semi-blind space-time chip equalizer receivers for the WCDMA downlink employing long spreading codes and a continuous codemultiplexed pilot. The proposed receivers exploit the presence of common pilot symbols in the so-called Common PIlot CHannel (CPICH) of the Universal Terrestrial Radio Access (UTRA) [8] and offer both a good performance and a high spectral efficiency. Moreover, they can simultaneously track multiple base-station signals, whenever the mobile station enters soft handover mode. Whereas the pilot-trained receiver only assumes knowledge of the pilot symbols, the pilot code and the desired user code for each base-station, the enhanced pilot-trained receiver additionally assumes knowledge of the other active user codes for each base-station. For both receivers we derive a Recursive Least Squares (RLS) algorithm for adaptive processing. The proposed receivers are compared in terms of performance and complexity with the conventional spacetime RAKE receiver and the ideal fully-trained space-time chip equalizer receiver. II. DATA MODEL

FOR MULTI - CELL

WCDMA

DOWNLINK

A. Multi-channel framework Let us consider the downlink of a multi-cell WCDMA system with active base-stations, transmitting to the mobile station of interest. Each base-station transmits a synchronous code division multiplex, employing short orthogonal Walsh-Hadamard spreading codes that are user specific and a long overlay scrambling code that is base-station specific. The multi-user chip sequence, transmitted by the -th base-station, consists of active user signals and a continuous pilot signal :







     !   mod "$# &% '( !) '  mod "$#  (1)   *,+&.0- / . Each user’s data symbol sequence   (piwith '  ) is spread by a factor #  with the lot symbol sequence   (pilot composlength-"$# user composite code sequence  ( '    ite code sequence ). The 1 -th user’s composite code se  (pilot composite code sequence for the  -th base-station  '    ) is the multiplication of the user specific (pilot quence specific) short Walsh-Hadamard spreading code and the basestation specific long scrambling code. For notational simplicity,

we assume that the power of a symbol sequence is incorporated in the symbol sequence itself. We assume that the mobile station is equipped with receive antennas. The received antenna signals are sampled at the chiprate
 and the obtained samples are  stacked in the received vector sequence 


   , which can be written as :     "!  $#  (2)    



 

 



 

  &           -  

 &%  

%& received noise
vector sequence and '  '   is the discrete-time vector channel from the -th base-station to the receive an)* tennas, modeled as an FIR vector filter of order + with delay index , . Note that, if we would sample at -/. times the chip rate and apply - -fold polarization diversity at the receiver side, the data model described in Equation 2 would become a multi-channel model with -/.0- instead of merely diversity channels per base-station [9]. #

where

 

('

 

is the











'

'

III. S PACE - TIME

RECEIVERS

In [10], we have introduced several block-based chip equalizer receivers. Since in practice, the multi-path fading channel is time-varying, we propose an adaptive version that updates the equalizer coefficients on the fly. In this paper, we derive an adaptive version of the different block-based chip-level equalizer receivers and provide complexity figures for each of them. The adaptive receivers address a single symbol at once and consist of parallel branches, one for each base-station connected to the mobile station of interest. The -th branch basically consists of two parts : a pilot-aided updating part and a user specific detection part. Note that, like for the block processing algorithms, in order to simultaneously track base-stations the mobile station should  be equipped with at least receive antennas for chip rate sampling. However, when we use a temporal over21 21 sampling factor of -/. and we exploit fold polariza43 tion diversity at the receiver, we obtain -.0(good for  45 soft-handover between base-stations) with only receive antenna at the mobile station.





  %



' 

' 

 

A. Preliminary definitions



We introduce the following 687 block ;"< : => $@   .. ;"< ? . $@ B  7



 # % 

 # %



%

%





:9%

#

6 %

:9



output matrix

 # %$@A!   .. 6  % :9 # $ %. @ % 7 !  

CD E

(3) @ where represents the symbol instant and the processing delay. :9GH The 6F+ pilot symbol vector for the -th basestation at the -th symbol instant is defined as follows :
  I

%



' 



' 



' 

  # % 



 %

# %





 M The multi-user composite code matrix L stacks the -th base-station’s active user composite code vectors at the -th symbol instant :

RQ
M ONAP  P L



 

#



 

 



 M Note that the multi-user spreading code matrix L S can M be similarly defined as L , stacking the -th base-station’s active user spreading code vectors for each symbol instant.

 #





B. Pilot-aided adaptive RAKE receiver To enable relevant performance and complexity comparisons, we have simulated a space-time pilot-aided adaptive RAKE receiver, extended to enable soft handover. For the sake of conciseness, it is sufficient here to remark that the complex9 for the updating of the ity of this receiver is of TU6 + 9 RLS algorithm and of TU6 + for detection. The details of this RAKE receiver can be found in [9].



ADAPTIVE CHIP - LEVEL EQUALIZER





# 

J The multi-user chip vector transmitted by the -th base@ station at the -th symbol instant starting at delay is defined by : K :9 $@  $@A!  ( 6