Adaptive Interference Suppression for the Downlink of a Direct Sequence CDMA System with Long Spreading Sequences

  • Authors:
  • Colin D. Frank;Eugene Visotsky;Upamanyu Madhow

  • Affiliations:
  • Advanced Radio Technology Group, Global Telecommunications Solution Sector, Motorola, 1501 W. Shure Drive, IL27-3G6, Arlington Heights, IL 60004, USA;Communication Systems and Technologies Labs, Motorola Labs, Schaumburg, IL 60196, USA;Department of Electrical and Computer Engineering, University of California, Santa Barbara, CA 93106, USA

  • Venue:
  • Journal of VLSI Signal Processing Systems
  • Year:
  • 2002

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Abstract

A simple approach for adaptive interference suppression for the downlink (base-to-mobile link) of a direct sequence (DS) based cellular communication system is presented. The base station transmits the sum of the signals destined for the different mobiles, typically attempting to avoid intra-cell interference by employing orthogonal spreading sequences for different mobiles. However, the signal reaching any given mobile passes through a dispersive channel, thus destroying the orthogonality. In this paper, we propose an adaptive linear equalizer at the mobile that reduces interference by approximately restoring orthogonality. The adaptive equalizer uses the pilot's spreading sequence (which observes the same channel as the spreading sequence for the desired mobile) as training. Simulation results for the linear Minimum Mean Squared Error (MMSE) equalizer are presented, demonstrating substantial performance gains over the RAKE receiver. Long spreading sequences (which vary from symbol to symbol) are employed, so that the equalizer adapts not to the time-varying spreading sequences, but to the slowly varying downlink channel. Since the inter-cell interference from any other base station also has the structure of many superposed signals passing through a single channel, the adaptive equalizer can also suppress inter-cell interference, with the tradeoff between suppression of intra- and inter-cell interference and noise enhancement depending on their impact on the Mean Squared Error (MSE).