To obtain good trade-offs between complexity and performance onpeak-to-average power ratio (PAPR) reduction in orthogonal frequency division multiplexing (OFDM)using partial transmitting sequence (PTS) schemes, a trellis structure based PTS factor searchmethod is proposed. The trellis search is with a variant constraint length L_C, 1 ≤ L_C ≤ V-1,where V is the number of PTS subblocks. The method is to decide a PTS factor by searching all thepossible paths obtained by varying L_C consecutive factors. The trellis search can be viewed as ageneral PTS factor search model. If L_C = V-1, it is a full search, and if L_C = 1, it is aniterative search. Using different constraint lengths, trellis factor search PTS exhibits differentPAPR reduction performances. A larger L_C results in a better performance and L_C = V-1 results inthe optimum. However, a larger L_C requires more computation. This helps to choose a good trade-offbetween complexity and performance.
In this paper performances of wavelet transform domain (WTD) adaptive equalizers based on the least mean￣square (LMS) algorithm are analyzed. The optimum Wiener solution, the condition of convergence, the minimum mean square error (MSE) and the steady state excess MSE of the WTD adaptive equalizer are obtained. Constant and time varying convergence factor adaptive algorithms are studied respectively. Computational complexities of WTD LMS equalizers are given. The equalizer in WTD shows much better convergence performance than that of the conventional in time domain.
