Max Log MAP Research Articles

An Improved Sliding Window Algorithm for Max-Log-MAP Turbo Decoder and Its Programmable LSI Implementation

Thanks to the possibility of being able to implement them in decoders in relatively simple ways, turbo codes are being applied to various areas of engineering. Wireless communications is one of the most important applications, where various types of data communications are required and the speed of information and data capacity need to be changed with different rates of parity bit puncturing being adopted to obtain highly efficient transmission. In such applications, adaptation to various turbocoding specifications on a real-time basis is needed as well as good bit-error-rate performance. We present a new concept for simplifying metric computation and programmable circuit configurations that focuses on the convolutional decoder, which occupies a significant portion of allocated hardware, and we fundamentally treat a simplified log-domain version of the maximum a posteriori (MAP) algorithm, usually know as the Max-Log-MAP (MLM), as a base algorithm. The sliding window method provides an attractive way of computing metrie values for the Max-Log-MAP. However, this algorithm does cause degradation, especially when a high rate code is used, generated by bit puncturing. We propose a new means of avoiding this problem and demonstrate that the sliding window, and a modified version as well as other methods, should be flexibly selected to utilize hardware resources depending on turbo specifications. We demonstrated that our proposed methods provide almost the same BER performance as MLM even when a high rate puncturing rate of 5/6 is applied. Finally, we describe the new hardware architecture that we invented to cope with these programmability issues. We show that a turbo-decoding circuit can be implemented in the processor core and its associated unit to configure an LSI macro circuit. The proposed unit has about 60-K gates. We demonstrate that this architecture can be applied to about the 1.5-Mbps information bit throughput of turbo decoding with a 200-MHz clock cycle, which is achievable with today's advanced CMOS technologies.

Combined Max-Log-MAP and Log-MAP of turbo codes

A new decoding algorithm which combines Max-Log-MAP (MLM) decoding and Log-MAP (LM) decoding is suggested. The proposed scheme observes the reliability measure of stopping criterion to determine which decoding algorithm should be used. It is shown that the proposed scheme provides nearly LM performance with nearly MLM decoding complexity.

Turbo equalization with sequential sequence estimation over multipath fading channels

We investigate the performance of a turbo equalization scheme over frequency-selective fading channels, where a soft-output sequential algorithm is employed as the estimation algorithm. The advantage of this scheme comes from the low computational complexity of the sequential algorithm, which is only linearly dependent on the channel memory length. Simulation results of an 8-PSK trellis-coded modulation (TCM) system show that the performance of this scheme suffers approximately 2-dB loss compared with that of the turbo max-log maximum a posteriori (MAP) probability equalizer after 5 iterations.

On SOVA for nonbinary codes

For binary codes, Fossorier et al. (see ibid., vol.2, p.137-9, 1998) have shown that the soft-output Viterbi algorithm (SOVA) becomes equivalent to the max-log-maximum a posteriori (MAP) algorithm after a modification. In this letter, we generalize such modified SOVA to nonbinary cases, motivated by the fact that the performance gap between the original SOVA and the max-log-MAP algorithm broadens in these cases, The equivalence between the two algorithms is proved in a more compact form. The modified SOVA requires only add-compare-select operations and is well suited for high-speed parallel implementation.

On the equivalence between SOVA and max-log-MAP decodings

It is shown that after a proper simple modification, the soft-output Viterbi algorithm (SOVA) proposed by Hagenauer and Hoeher (1989) becomes equivalent to the max-log-maximum a posteriori (MAP) decoding algorithm. Consequently, this modified SOVA allows to implement the max-log-MAP decoding algorithm by simply adjusting the conventional Viterbi algorithm. Hence, it provides an attractive solution to achieve low-complexity near-optimum soft-input soft-output decoding.