Abstract:
A channel estimation method which reduces the strain on resources of a Rake receiver using a complex weight gain (CWG) algorithm. In one embodiment, a nonadaptive algorithm is used to average blocks of pilot symbols from several slots. In another embodiment, an adaptive algorithm implements sliding window averaging or a recursive filter. Using a CWG algorithm reduces the memory and processor requirements of the Rake receiver.
Abstract:
A method for differential phase evaluation of M-ary communication data is employed in which the data consists of N sequential symbols r1 . . . rN, each having one of M transmitted phases. Selected sequences of Nnull1 elements that represent possible sequences of phase differentials are evaluated using multiple-symbol differential detection. Using r1 as the reference for each phase differential estimate, sNnull1 phase differential sequences are selected in the form (P2i, P3i, . . . , PNi) for inull1 to s for evaluating said symbol set, where s is predetermined and 1
Abstract:
A method for estimating signal-to-noise ratio (SNR) using a method with low bias that is effective for both positive SNRs and small to negative SNRs. The method is based on an iterative solution for the maximum likelihood estimate of the amplitude from which the SNR can be computed. The method is applicable for various modulated systems, including BPSK, QPSK and MPSK.
Abstract:
A simple and robust CTL is used for time tracking of multipath components of a spread spectrum signal transmitted over a wireless multipath fading channel. A digital code-tracking loop includes the implementations of despreading early and late data samples by use of a pseudonoise sequence, an error signal output generated by the despreading, and adjustment for a plurality of on-time, early and late samples, a data rate of a control signal provided as a fractional proportion of a data rate of error signals.
Abstract:
An apparatus and method for estimation of signal-to-noise ratio (SNR) with low bias that is effective for both positive SNRs and small to negative SNRs. The estimation is based on an iterative solution for the maximum likelihood estimate of the amplitude from which the SNR can be computed. The estimation is applicable for various modulated systems, including BPSK, QPSK and MPSK.