Hardware computational capabilities continue to increase dramatically enabling ever more sophisticated signal processing at digital transmitters and receivers. The work presented in this manuscript will cover two similar applications of convex optimization methods to important physical layer signal processing problems. The first work formulates relaxations of the tone injection method for PAPR reduction of linearly precoded systems, including as special cases OFDM, OFDMA, and SC-FDMA. A semi-definite programming approach and a sparse signal recovery-inspired approach are presented. Performance in terms of PAPR reduction and effects on power amplifier efficiency at lower PAPR back-off are given are given for several systems. The second work is a convex joint linear equalization and decoding algorithm that requires fewer pilot symbols than traditional methods for QAM transmissions over multi-path channels. The convex optimization framework developed takes into account both signal constellation and LDPC FEC coding information. The integration of FEC coding constraints applies recent developments in linear programming-based decoding. The BER performance of this algorithm is tested over several simulated channel and system configurations.
|Commitee:||Levy, Bernard, Zhao, Qing|
|School:||University of California, Davis|
|Department:||Electrical and Computer Engineering|
|School Location:||United States -- California|
|Source:||DAI-B 75/01(E), Dissertation Abstracts International|
|Subjects:||Communication, Electrical engineering|
|Keywords:||Convex optimization, Digital communication, Digital transmitters, Transceiver design|
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