A Low-Complexity Iterative Channel Estimation and Detection Technique for Doubly Selective Channels

Abstract

In this paper, we propose a low-complexity iterative joint channel estimation, detection and decoding technique for doubly selective channels. The key to the proposed technique is a segment-by-segment processing strategy under the assumption that the channel is approximately static within a short segment of a data block. Through a virtual zero-padding technique, the proposed segment-by-segment equalization approach inherits the low-complexity advantage of the conventional frequency domain equalization (FDE), but does not need the assistance of guard interval (for cyclic-prefixing or zero-padding), thereby avoiding the spectral and power overheads. Furthermore, we develop a low-complexity bidirectional channel estimator, where the Gaussian message passing (GMP) Abstract-In this paper, we propose a low-complexity iterative joint channel estimation, detection and decoding technique for doubly selective channels. The key to the proposed technique is a segment-by-segment processing strategy under the assumption that the channel is approximately static within a short segment of a data block. Through a virtual zero-padding technique, the proposed segment-by-segment equalization approach inherits the low-complexity advantage of the conventional frequency domain equalization (FDE), but does not need the assistance of guard interval (for cyclic-preſxing or zero-padding), thereby avoiding the spectral and power overheads. Furthermore, we develop a lowcomplexity bidirectional channel estimator, where the Gaussian message passing (GMP) technique is used to exploit the channel correlation information, and the intermediate channel estimation results in the iterative process are employed to perform intertap interference cancellation. Simulation results demonstrate the effectiveness of the proposed detection and channel estimation algorithms.

Multicast Systems With Fair Scheduling in Non-identically Distributed Fading Channels

“…To compare the performance in the adaptive discrete rate modulation schemes, we generate the average received SNR of each MS following the distribution uniform (12,15) when M = 3. As the number of groups increases, the average received SNR distributions for three new groups follow uniform (15,18) when M = 6, uniform (18,21) when M = 9, uniform (21,24) when M = 12 and uniform (24,27) when M = 15, respectively.…”

“…For convenience, part of this table is reproduced in this paper as Table 1. These parameters are actually applied in an AWGN channel, whereas for a frequency-selective fading channel, we The Number of Groups can exploit efficient equalization and detection approaches to approach the performance of the corresponding system over an AWGN channel [27]. The Number of Groups the number of groups increases and accordingly the average received SNR increases with the above defined uniform distribution, there is a system spectral efficiency improvement.…”

Superposition coded modulation and iterative linear MMSE detection

“…We have assumed that channel state information (CSI) is perfectly known in this paper. Discussions can be found in [39] for situations when CSI is not perfectly known but estimated.…”

A sub-block orthogonal single carrier frequency domain equalization system in fast Rayleigh fading channel

“…Or we can rebuild the CP using the feedback of the decoder [7], but if the equalizer works serially between sub-blocks, the delay of the algorithm is much higher, and if the decoder works parallelly with several blocks [10], the equalizer will suffer from the lack of a priori information of the transmit signals in the beginning of the iteration. In this section, we suggest orthogonal sub-blocked FDLE algorithm taking into account the special case of 2 sub-blocks.…”

“…And the definition of h Δ max is similar to (10). In the following, we let Λ 2 σhalf = diag{|σ half (i)| 2 }.…”