Pisit Vanichchanunt

APP demodulator for turbo coded differential unitary space-time modulation

In this paper, an iterative multiple symbol differential detection (MSDD) for turbo coded differential unitary space-time modulation (DUSTM) is developed by using an a posteriori probability (APP) demodulator under correlated slow and fast Rayleigh flat fading channels. The metric function necessary for the detection operates based on linear prediction. Two approaches are presented to utilize the metric. In the first approach, the BCJR algorithm is modified to deal with the increased-state trellis of the differential modulation. In the second approach, the VA is modified to find the symbol sequences associated with the survivors for the BCJR algorithm.

Turbo coded multiple symbol differential detection for correlated Rayleigh fading channel

In this paper, the multiple symbol differential detection (MSDD) with iterative decoding (turbo decoding) of code rate 1/2 is modified to work under both correlated slow and correlated fast Rayleigh fading channels.

Iterative multiple symbol differential detection for turbo coded differential unitary space-time modulation

In this paper, an iterative multiple symbol differential detection for turbo coded differential unitary space-time modulation using a posteriori probability (APP) demodulator is investigated. Two approaches of different complexity based on linear prediction are presented to utilize the temporal correlation of fading for the APP demodulator. The first approach intends to take account of all possible previous symbols for linear prediction, thus requiring an increase of the number of trellis states of the APP demodulator. In contrast, the second approach applies Viterbi algorithm to assist the APP demodulator in estimating the previous symbols, hence allowing much reduced decoding complexity. These two approaches are found to provide a trade-off between performance and complexity. It is shown through simulation that both approaches can offer significant BER performance improvement over the conventional differential detection under both correlated slow and fast Rayleigh flat-fading channels. In addition, when comparing the first approach to a modified bit-interleaved turbo coded differential space-time modulation counterpart of comparable decoding complexity, the proposed decoding structure can offer performance gain over 3 dB at BER of 10−5.

Efficient Medium Access Control Protocols for Broadband Wireless Communications

Suvit Nakpeerayuth1, Lunchakorn Wuttisittikulkij1, Pisit Vanichchanunt2, Warakorn Srichavengsup3, Norrarat Wattanamongkhol1, Robithoh Annur1, Muhammad Saadi4, Kamalas Wannakong1 and Siwaruk Siwamogsatham5 1Chulalongkorn University 2King Mongkuts University of Technology North Bangkok 3Thai-Nichi Institute of Technology 4University of Management and Technology 5National Electronics and Computer Technology Center 1,2,3,5Thailand 4Pakistan

An app demodulator for iterative decoding of turbo coded differential space-time modulation with unitary group codes

A modified technique for joint iterative decoding of serial concatenation of turbo code and unitary space-time group code is proposed and evaluated under temporally correlated fading channels. This approach further takes advantage of the system by exploiting the unitary space-time group code which possesses trellis structure of differential modulation. The extrinsic information of modulation symbols is calculated from this trellis structure by using a detector called an a posteriori probability (APP) demodulator. The simulation results show that our modified method is superior to the conventional one at the expense of more complexity.

Turbo decoding over a two-state Markov channel

A decoding system comprising of a turbo decoder and a burst detector is proposed for a two-state, additive white Gaussian noise, Markov channel in which one state represents a good state with high E/sub b//N/sub 0/ and the other state represents a bad state or burst state with low E/sub b//N/sub 0/. As the Gaussian noise model allows soft information from the channel to be used, it enables an improved performance over the commonly used binary-input/binary-output channel model. In the proposed decoding structure, the burst detector is employed to estimate the probability of each channel state and pass it on to the turbo decoder, so that this extra information assists the turbo decoder to perform a more effective decision for each received symbol by adjusting the likelihood function property in accordance with the channel states.