This thesis investigates the use of Maximum Likelihood Sequence Estimation (MLSE) in the presence of unknown channel parameters. MLSE is a fundamental problem that is closely related to many modern research areas like Space-Time Coding, Overloaded Array Processing and Multi-User Detection. Per-Survivor Processing (PSP) is a technique for approximating MLSE for unknown channels by embedding channel estimation into the structure of the Viterbi Algorithm (VA). In the case of successful acquisition, the convergence rate of PSP is comparable to that of the pilot-aided RLS algorithm. However, the performance of PSP degrades when certain sequences are transmitted. In this thesis, the blind acquisition characteristics of PSP are discussed. The problematic sequences for any joint ML data and channel estimator are discussed from an analytic perspective. Based on the theory of indistinguishable sequences, modifications to conventional PSP are suggested that improve its acquisition performance significantly. The effect of tree search and list-based algorithms on PSP is also discussed. Proposed improvement techniques are compared for different channels. For higher order channels, complexity issues dominate the choice of algorithms, so PSP with state reduction techniques is considered. Typical misacquisition conditions, transients, and initialization issues are reported. / Master of Science

Enhanced Data Rates for Global Evolution (EDGE) is one of the 3G wireless communication standards, which provides higher data rates by adopting 8-PSK modulation in TDMA system infrastructure of GSM. In this thesis, a turbo detection receiver for Enhanced General Packet Radio Services (EGPRS) system, which is the packet switching mode of EDGE, is studied. In turbo detection, equalization and channel decoding are performed iteratively. Due to 8-ary alphabet of EGPRS modulation, full state trellis based equalization, as usually performed in GSM, is too complex not only for turbo detection but even for conventional equalization / so suboptimum schemes have to be considered. The Delayed Decision Feedback Sequence Estimation (DDFSE) is chosen as suboptimal and less complex trellis based scheme and it is examined as a conventional equalization technique firstly. It is shown that the DDFSE has a fine tradeoff between performance and complexity and can be a promising candidate for EGPRS. Then it is employed to reduce the number of the trellis state in turbo detection. Max-log-MAP algorithm is used for soft output calculations of both SISO equalizer and SISO decoder. Simulation results illustrate that proposed turbo detection structure improves bit error rate and block error rate performance of the receiver with respect to the conventional equalization and decoding scheme. The iteration gain varies depending on modulation type and coding rate of Modulation Coding Scheme (MCS) employed in EGPRS.