Synchronization Algorithms In OFDM Broadband Wireless Baseband Receiver

OFDM (orthogonal frequency-division multiplexing) has been chosen as the physical layer transmission solution in many wireless communication standards because of its high bandwidth utilization and robustness to the multipath effect. However, OFDM is far more vulnerable to synchronization errors, which determines the performance of the baseband receiver, compared with the single carrier systems. In this thesis, the synchronization algorithms, containing carrier frequency offset (CFO) synchronization and symbol synchronization, in broadband wireless receiver are deeply analyzed and researched, the performance of these algorithms are demonstrated and evaluated in depth.CFO can be divided into an integer part (IFO), which is a multiple of the subcarrier spacing, and a fractional part (FFO), which is less than one half of the subcarrier spacing. Since the existing algorithms have the problems of high complexity, low bandwidth efficiency or poor performance, two FFO synchronization methods are introduced.1.) A FFO estimation algorithm is proposed for a constant modulus (CM) signaling based OFDM systems. The FFO can be estimated via minimizing the power difference of data on the same subcarriers between two consecutive OFDM symbols. The identifiability problem is proved and curve fitting is exploited to simplify the proposed algorithm. Furthermore, the theoretical mean and mean square error (MSE) of the proposed algorithm is derived.2.) A FFO tracking algorithm for CM signaling based OFDM systems is suggested. Provided that the channel frequency response (CFR) is known to the receiver, the FFO can be tracked through minimizing the power difference between received signal and the CFR. Also, the identifiability problem is assured and polynomial rooting method is applied to simplify the tracking algorithm. Performance analysis shows that the proposed algorithm is not sensitive to the channel estimation errors. With the help of space time block codes (STBC), these two proposed methods are also applicable in multiple input multiple output (MIMO) OFDM systems. Numerical results show that these two algorithms can effectively lower the bit-error rate (BER) compared with existing methods.Then two IFO estimation algorithms are proposed.1.) A IFO estimation method based on linear precoding is introduced. A linear precoding scheme is applied on data in predefined subcarriers before the inverse discrete Fourier transform (IDFT) to impose a correlation structure, which is exploited to estimate the offset after the discrete Fourier transform (DFT) in the receiver. The allocation of these predefined subcarriers is optimized to obtain the best performance.2.) A IFO estimation method based on the power reallocation is suggested. The key idea behind this method is a power reallocation technique which modifies the power of data in some predefined subcarriers over two consecutive OFDM symbols, thus the IFO can be estimated in the receiver via analyzing the distribution of these subcarriers. Instead of exhaustive search, a low-complexity solution is proposed. More subcarriers and OFDM symbols can be employed to improve the robustness of this method to the multipath effect. This method can be applicable in MIMO-OFDM systems. These two IFO estimation algorithms are bandwidth efficient since no pilot or null subcarriers are needed.At last, a two-step OFDM symbol timing synchronization scheme is proposed. The optimal timing point is the arrival time of the first path. This scheme is based on a training symbol known by the receiver, thus it is suitable for the burst transmission. The proposed scheme contains coarse and fine synchronization. At the first stage, a coarse synchronization using the cyclic prefix based maximum likelihood method can compute a rough estimate and provide a search area for next step. The joint problem of channel and fine symbol timing offset estimation at the second stage is solved by genetic algorithm (GA). For each point in the search area, GA supposes it is the first path delay and randomly searches the channel impulse response (CIR) to minimize the error between received signals and convolution results between the training symbol and the CIR. Through comparing the objective function values corresponding to each point in the search area, GA can obtain the accurate final results. It is demonstrated that this two-step scheme can afford better estimation accuracy compared with existing method under low signal to noise ratio (SNR) condition. The proposed algorithm can afford flexibility for system design via choosing different search radius, thus providing tradeoff between speed and accuracy.