Spatial processing, Power Control, and channel allocation for OFDM wireless communications

Abstract

OFDM is mainly designed to combat the effect of multipath reception, by dividing the wide-band frequency selective fading channel into many narrow-band flat subchannels. OFDM offers flexibility in adaptation to time-varying channel condition by adopting the parameters at each subcarrier accurately. The purpose of this work is to use this flexibility and study the OFDM systems with power control, multiple transmit and receive antennas, the problem of Peak to Average Power Ratio (PAPR), and the effect of OFDM in providing QoS.

An OFDM uplink multiuser wireless network, combined with power control and receive beamforming is proposed to achieve the desired SINR at each OFDM subchannel. Consequently, better overall BER with the same total power is achieved. To reduce the receiver complexity, joint time-domain beamforming and power control is also provided. The proposed algorithm is also extended to COFDM.

We use distributed schemes to maximize the maximum achievable data rate for each receiver in a multiuser downlink transmission using MIMO/OFDM, by finding the optimal transmit and receive weight vectors. We propose iterative algorithms to distribute the limited power (per carrier or per user) to multiple streams and multiple antennas in order to maximize the allocated rate per user. The game theoretic analogy of the problem is stated and the convergence of the algorithms are discussed.

To increase the information rate of low PAPR OFDM codes, we propose two frameworks. Super Golay sequences constructed from 16QAM constellation having PAPR bounded up to 3dB are defined, and constructed by recursive structures. Cyclic-Golay codes are also proposed and constructed by a framework that can be used to obtain the cyclic shift of any code represented by Boolean algebraic functions. These codes are in general a subset of generalized Reed-Muller codes, and have lower error correction capabilities compared to Golay sequences. An extension of the majority logic Reed algorithm for decoding Reed-Muller codes of any order is provided. To reduce decoding complexity, recursive maximum-likelihood decoding schemes are also provided, and the complexity of these algorithms are analyzed.

We also address a scheduling algorithm for wireless networks that provides QoS for mobile users in a shared environment and at the same time utilizes the system resources efficiently. We introduce an income maximization notion, and propose optimal and suboptimal approaches to increase throughput and maintain the QoS for each user, and generate high income for service provider. This notion is used to determine the optimal subcarrier allocation to different users of an OFDMA system based on their required QoS. Optimal and sub-optimal algorithms are presented and their performances and complexities are studied.