Quasi-maximum-likelihood multiple-symbol differential detection for time-varying Rayleigh fading channel

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Quasi-maximum-likelihood multiple-symbol differential detection for time-varying Rayleigh fading channel

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The maximum-likelihood multiple-symbol differential detector (ML-MSDD) has better bit-error-rate performance than many other detectors for differential modulation. Unfortunately, the computational complexity of ML-MSDD quickly becomes prohibitive as the observation window size grows. While low-complexity MSDD algorithms for the time-invariant Rayleigh fading channel have been considered before, there is a need for low-complexity MSDD algorithms for general time-varying Rayleigh fading channels. A polynomial-time complexity approach called semi-definite relaxation (SDR) is employed to achieve differential detection with near maximum-likelihood (ML) performance. The proposed SDR quasi-maximum-likelihood (QML) multiple-symbol differential detection (SDR-QML-MSDD) is efficient in that its complexity is polynomial in the observation window size, even in the worst case, while it exhibits almost the same performance as ML-MSDD does.

Inspec keywords: error statistics; differential detection; quadrature phase shift keying; differential phase shift keying; time-varying channels; polynomials; Rayleigh channels; maximum likelihood detection

Other keywords: computational complexity; differential quadrature phase shift keying; differential modulation; differential QPSK; observation window size; quasi-maximum-likelihood multiple-symbol differential detection; differential phase-shift keying; polynomial-time complexity approach; DPSK; time-varying Rayleigh fading channel; low-complexity algorithms; semi-definite relaxation

Subjects: Signal detection; Information theory; Probability and statistics; Interpolation and function approximation (numerical analysis); Modulation and coding methods

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