Peak-to-average power-ratio and intercarrier-interference reduction algorithms for orthogonal frequency-division multiplexing systems

Several new peak-to-average power-ratio (PAPR) and intercarrier interference (ICI) reduction algorithms are developed for different orthogonal frequency-division multiplexing (OFDM) systems.; A new constellation extension technique is proposed for PAPR reduction for OFDM systems whereby the modulation constellation for active subcarriers and the modulation symbols in unused subcarriers are continuously modified. Based on this technique, the PAPR-reduction problem for OFDM systems with real-valued time-domain signals is formulated as a linear-programming (LP) problem where the number of constraints is much larger than that of the variables. The solution of the problem is obtained efficiently by using a new Newton algorithm. Simulations demonstrate that considerable performance improvement can be achieved by using the proposed algorithm relative to that achieved by using some existing algorithms.; The proposed constellation extension technique is applied for PAPR reduction for OFDM systems with complex-valued time-domain signals. In this case, the PAPR-reduction problem is formulated as a minimax optimization problem and an accelerated least-pth algorithm is proposed to obtain the solution. Simulations show that, in many practical situations, considerable performance improvement can be achieved by the proposed algorithm over that achieved by several existing algorithms. Furthermore, the accelerated algorithm offers a tradeoff between performance and computational complexity, which can be used to advantage in practical situations.; Yet another constellation extension technique for PAPR reduction is developed whereby, for each subcarrier, the same data may be represented by points in the original constellation or by extended points. In an attempt to find an optimal representation of the OFDM signal, two de-randomization algorithms are proposed by applying the so called conditional probability method, i.e., the Chernoff-bound based and polynomial-bound based algorithms. In order to further improve the performance, new algorithms based on the selective rotation (SR) and coordinate descent optimization (CDO) are proposed. It is shown that the proposed algorithms outperform several existing algorithms in terms of PAPR reduction and computational complexity. Compared with the proposed Chernoff-bound based algorithm, the proposed polynomial-bound based algorithm achieves a similar performance with much less computational complexity. The performance of the proposed algorithms can be further improved by combining the de-randomization, SR, and CDO algorithms with the selective mapping (SLM) algorithm.; The thesis also deals with ICI reduction in OFDM systems in fast time-varying channels. Two new algorithms are proposed for OFDM systems with complex-valued time-domain signals. A low-complexity ICI-reduction algorithm based on an iterative optimization algorithm is proposed for OFDM systems using 4-quadrature-amplitude-modulation (4-QAM) for all subcarriers. Then an ICI-reduction algorithm based on the sphere decoding (SD) algorithm is proposed for OFDM systems using high-order modulation. By taking channel information into account, a new search strategy to reduce the computational complexity of the SD algorithm is developed. Simulations demonstrate that the proposed iterative algorithm outperforms several existing algorithms in terms of BER performance and computational complexity, and the performance can be further improved by using the proposed SD algorithm. The proposed algorithms can exploit the frequency diversity introduced by channel variations and, therefore, improved performance can be achieved at higher Doppler frequencies.