Near-Far Resistant Linear Multiuser Detection

Abstract

This dissertation studies linear detectors for Code-Division Multiple-Access channels perturbed by additive white Gaussian noise, under the assumption that the ensemble of user code waveforms is known to the receiver. In particular the near-far problem of Direct-Sequence Spread-Spectrum Multiple- Access channels, i.e., the problem of demodulating a weak transmitter in the presence of powerful interferers, is solved with a linear receiver. Two multiuser performance measures are used to quantify the performance degradation due to the presence of multiuser interference: The asymptotic efficiency, which is equivalent to bit-error-rate in the low background noise region, and the near-far resistance, which measures a detector's robustness to the near-far problem. Conventional single-user detection in a multiuser channel is not near- far resistant, while the substantially higher performance of the optimum multiuser detector requires exponential complexity in the number of users. We show that the near-far resistance of optimum multiuser detection is achieved by a linear receiver (whose complexity per demodulated bit is only linear in the number of users). The optimum linear detector for worst-case energies - the decorrelating detector - is found, along with existence conditions, which are always satisfied in the models of practical interest. Its implementation does not require knowledge of the received energies, its bit-error-rate is energy- independent, and it achieves optimum near-far resistance.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1989
Accession Number
ADA206363

Entities

People

  • R. Lupas

Organizations

  • Princeton University

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Amplitude Modulation
  • Code Division Multiple Access
  • Communication Systems
  • Computational Complexity
  • Computations
  • Demodulation
  • Detection
  • Digital Communications
  • Information Science
  • Information Theory
  • Mathematical Analysis
  • Multiple Access
  • Probability
  • Random Variables
  • Resistance
  • Theorems

Fields of Study

  • Engineering

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Radio communications and signal processing.