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Title Comparison of Exact and Approximate Multi-User Detection for GSM
Author Nie, Lili
Supervisor Winther, Ole (Department of Informatics and Mathematical Modeling, Technical University of Denmark, DTU, DK-2800 Kgs. Lyngby, Denmark)
Institution Technical University of Denmark, DTU, DK-2800 Kgs. Lyngby, Denmark
Thesis level Master's thesis
Year 2005
Abstract In today s Group Special Mobile (GSM) system, interference is one of the main constraints in increasing cellular capacity. Multi-User Detection (MUD) is a kind of Interference Cancellation (IC) technique, which can be combined with other IC methods, such as antenna diversity, whitening. This dissertation investigates exact and approximate MUD GSM receivers. It is shown that exact MUD solution provides a big Bit Error Rate (BER) gain compared to conventional receivers. However, it has exponential complexity, making it infeasible to implement it on the limited Mobile Station (MS). In this thesis, the approximation to the exact solution is based on Mean Field theory. Two suboptimum algorithms: Fully Factorized Mean Field (FFMF) receiver and Structured Mean Field (SMF) receiver are implemented and evaluated. FFMF has very low complexity, comparable to that of the Linear Minimum Mean Squared Error (LMMSE) receiver, but much better BER performance for interference dominated scenarios. The SMF receiver gives faster convergence speed. However, for one Cochannel Interference (CCI), its performance is only close to that of FFMF solution in most of the tested CIR range and better than that of FFMF receiver at low CIR values. Besides, topics such as digital phase modulation, GSM basics, the multi-path fading channel and conventional GSM receivers are also studied.
Imprint Department of Informatics and Mathematical Modeling, Technical University of Denmark, DTU : DK-2800 Kgs. Lyngby, Denmark
Pages 105
Keywords Adjacent Channel Interference (ACI); Cochannel Interference (CCI); Fully Factorized Mean Field (FFMF); Group SpÕcial Mobile (GSM); Interference Cancellation (IC); Inter-Symbol Interference (ISI); Linear Minimum Mean Squared Error (LMMSE)
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Admin Creation date: 2006-06-22    Update date: 2012-12-17    Source: dtu    ID: 185910    Original MXD