Incremental redundancy, or Hybrid type-II ARQ (HARQ), algorithms use a combination of forward error correction and retransmissions to guarantee reliable packet data communications. In this work, we propose a HARQ algorithm that exploits received packet reliability to improve system performance. Specifically, the receiver uses the average magnitude of the log-likelihood ratios of the information bits as the packet reliability metric, which is then used to determine the sizes of subsequent retransmissions. The proposed retransmission strategy attempts to maximize user throughput while satisfying a maximum packet delay constraint. The performance of our reliability-based HARQ algorithm is evaluated in static and time-varying channels through simulations. Furthermore, analytical results on the relationship between the reliability metric, the code rate and the block error rate are presented.

An adaptive iterative (turbo) decision-feedback equalizer (DFE) for channels with intersymbol interference (ISI) is presented. The filters are computed directly from the soft decisions and received data to minimize a least-squares (LS) cost function. Numerical results show that this method gives a substantial improvement in performance relative to a turbo DFE computed from an exact channel estimate, assuming perfect feedback. Adaptive reduced-rank estimation methods are also presented, based on the multistage Wiener filter (MSWF). The adaptive reduced-rank turbo DFE for single-input/single-output channels is extended to multiple-input/multiple-output (MIMO) channels with ISI and multiple receive antennas. Numerical results show that for MIMO channels with limited training, the reduced-rank turbo DFE can perform significantly better than the full-rank turbo DFE.

Incremental redundancy, or hybrid type-II ARQ (HARQ), algorithms use a combination of forward error correction and retransmissions to guarantee reliable packet data communication. In our previous work (V. Tripathi et al. 2003), we have proposed an adaptive HARQ algorithm that exploits received codeword reliability for optimizing the size of the subsequent retransmissions. The optimization is based on two mappings: the codeword reliability to block error rate (BLER) mapping and the coding rate to codeword reliability mapping. We provide analytical approximations for these mappings for any convolutional code. Through simulations, the approximations are shown to be accurate in the range of interest.

Hybrid ARQ (HARQ) schemes use a combination of forward error correction and retransmissions to guarantee reliable packet data communications. In this work, we propose a HARQ scheme that exploits channel state information and received packet quality to improve system performance. Specifically, the receiver uses the average magnitude of the log-likelihood ratios corresponding to the received information bits, in order to determine the sizes of subsequent retransmissions. The proposed retransmission strategy attempts to maximize user throughput while satisfying a maximum packet delay constraint. The performance of our reliability-based type II HARQ (RBHARQ) scheme is evaluated in static and time-varying channels through simulations.

The scenario considered is one where a single new user is to be acquired on the reverse link by the base station, and where the channel parameters of the interfering users are known. Following a minimum mean squared error (MMSE) strategy for suppressing the multiaccess interference, the parameter estimation problem is posed in a maximum likelihood framework, To reduce complexity, the solution is implemented in two stages: first, the estimated tap delays are restricted to be at chip spacings; second, the number of taps is reduced by allowing for arbitrary spacing between them. The performance of the proposed techniques is studied through numerical simulations. It is shown that significant gains can be obtained by exploiting the structure of the interference and acquiring the channel parameters jointly.