Wireless communication systems usually employ a concatenated error control coding scheme consisting of an outer error detection code and an inner error correction code. Traditionally, these two codes are decoded separately. When the sub-block structure is used, each data block (input sequence) at the inner encoder consists of several sub-blocks and each of these sub-blocks is protected with the error detection code. The sub-block structure is used in the Wideband CDMA (WCDMA) system specified by the 3rd Generation Partnership Project (3GPP). In this paper, a sub-block recovery scheme is proposed for this concatenated error control coding scheme to utilize the error detection capability introduced by the outer code in the decoding of the inner code. We demonstrate that, if the inner code is a turbo code with a highly structured interleaver and iterative sub-optimal decoding is used, the sub-block recovery scheme is helpful in correcting a typical error pattern, which helps to improve the block error rate performance. We analyze the decoding performance when sub-block recovery is used together with the maximum likelihood (ML) algorithm as well as the log maximum-a-posteriori probability (Log-MAP) and the soft output Viterbi algorithm (SOVA) and demonstrate gains introduced by the sub-block recovery in the latter two cases using computer simulations.

In this paper, we propose and analyze the adaptive modulation system with optimal Turbo Coded V-BLAST (Vertical-Bell-lab Layered Space-Time) technique that adopts extrinsic information from a MAP (Maximum A Posteriori) decoder with iterative decoding as a priori probability in two decoding procedures of V-BLAST scheme; the ordering and the slicing. Also, we consider the AMC (Adaptive Modulation and Coding) using the conventional Turbo Coded V-BLAST technique that simply combines the V-BLAST scheme with the turbo coding scheme. And we compare the proposed iterative decoding algorithm to a conventional V-BLAST decoding algorithm and a ML (Maximum Likelihood) decoding algorithm. In this analysis, the MIMO (Multiple Input Multiple Output) and the STD (Selection Transmit Diversity) schemes are assumed to be parts of the system for performance improvement. Results indicate that the proposed systems achieve better throughput performance than the conventional systems over the whole SNR (Signal to Noise Ratio) range. In terms of transmission rate performance, the suggested system is close in proximity to the conventional system using the ML decoding algorithm. In addition, the simulation result shows that the maximum throughput improvement in each MIMO scheme is respectively about 350 kbps, 460 kbps, and 740 kbps. It is suggested that the effect of the proposed iterative decoding algorithm accordingly gets higher as the number of system antenna increases.

Traditionally, it has been considered that the received signal to noise power ratio should be uniformly preserved to maximize system capacity for uncoded system with reliable feedback channel. However, once channel coding is employed as a building block, another power control scheme presents better performance. In this paper, we consider several power reallocation schemes for an effective use of limited power in a turbo coded system in lognormal shadowing channel. We show that the proposed power reallocation can reduce the decoding error probability by almost two orders of magnitude and provide a power gain of 0.87 dB at a target bit error rate of 10-4 over the equal power allocation among all code symbols. We also propose applying different power levels and cut-off thresholds on systematic and parity bits, and investigate the effect of channel estimation error.

Multiple-Input Multiple-Output (MIMO) systems that realize high-speed data transmission with multiple antennas at both transmitter and receiver are drawing much attention. In line-of sight (LOS) environments, the performance of MIMO systems depends largely on the difference of the phase difference of direct paths from transmit antennas to each receive antenna. When the phase difference of direct paths are close to each other, the spatial division multiplexing (SDM) channels are not orthogonal to each other so signal detection becomes difficult. In this paper, we propose a MIMO system with relative phase difference time-shift modulation (RPDTM) in Rician fading environments. The proposed scheme transmits independent signals from each antenna at each time slot where the relative phase difference between signal constellations used by transmit antennas varies in a pre-determined pattern. This transmission virtually changes the phase difference of direct paths from transmit antennas to each receive antenna without lowering data rate and without knowledge of the channels. In addition, forward error correction coding (ECC) is applied to exploit the time slots where the receiver can detect the signals easily to improve the detection performance. If there are time slots where the receiver can separate the received signal, the receiver can decode the data by using the time slots and the correlation between data. From the results of computer simulation, we show that MIMO system with RPDTM can achieve the better bit error rate (BER) than the conventional MIMO system. We also show that the MIMO system with RPDTM is effective by about Rician factor K = 10 dB.

A method is presented that can substantially reduce the memory requirements of non-binary turbo decoders by efficient representation of the extrinsic information. In the case of the duo-binary turbo decoder employed by the IEEE 802.16e standard, the extrinsic information memory can be reduced by about 43%, which decreases the total decoder complexity by 18%. We also show that the proposed algorithm can be implemented by simple hardware architecture.

Soft-decision decoding techniques are applied to asynchronous frequency-hop/spread-spectrum multiple-access (FH/SSMA) networks, where M-ary frequency shift keying (MFSK) is employed to transmit one modulated symbol per hop. Coding schemes using soft-decision decoded binary convolutional codes or turbo codes are considered, both with or without bit-interleaving. Performances of several soft metrics are examined for each coding scheme. It is shown that when multiple access interference is the main source of errors, the product metric offers the best performance among the soft metrics considered for all coding schemes. Furthermore, the application of soft-decision decoded convolutional codes or turbo codes without bit-interleaving is shown to allow for a much larger number of simultaneously transmitting users than hard-decision decoded Reed-Solomon codes. Finally, it is observed that when soft-decision decoding techniques are employed, synchronous networks attain better performance than asynchronous networks.

We propose an incremental redundancy (IR)-hybrid ARQ (HARQ) scheme which uses double binary turbo codes for error correction. The proposed HARQ scheme provides a higher throughput at all Es/N0 than the binary turbo IR-HARQ scheme. An extra coding gain is also attained by using the proposed HARQ scheme over turbo codes only.

In this paper, it is shown that the bit erasure probability of turbo codes with iterative decoding in the waterfall region is nonlinearly scaled by the information blocklength. This result can be used to predict efficiently the bit erasure probability of the finite-length turbo codes over the binary erasure channel.

We propose reallocating the power resource among the code symbols in such a way to minimize the post decoding error probability of turbo code. We consider several power reallocation policies and investigate their performance in slowly-varying Rayleigh flat fading channel. We show that the proposed scheme can reduce the post decoding error probability by two orders of magnitude and provide a power gain of 0.86 dB at BER=10-6 over the traditional equal power allocation among all code symbols. We also propose applying different power levels and cut-off thresholds on systematic and parity check bits depending on the channel gain, and investigate the effect of channel gain estimation error.

Recently, a versatile user cooperation method called coded cooperation diversity has been introduced, in which the codewords of each mobile are partitioned and transmitted through independent fading channels instead of simple repetition relay, to achieve remarkable gains over a conventional (non-cooperation) system, while maintaining the same information rate and transmission power. In this paper we present an adaptive space-time (AST) coded cooperation scheme based on the decoding operation on the first partition of the codeword at the base station and enables practical adaptive arrangement of resources to adopt the channel condition. Performance analysis and simulation results have proved that the proposed scheme greatly improves error rate performance and system throughput, compared with the previous framework.

We propose a new fixed-rate error correction system with a feedback channel. In our system, the receiver transmits a list of positions of unreliable information bits based on the log a-posteriori probability ratios by outputs of a soft-output decoder to the transmitter. This method is just like that of the reliability-based hybrid ARQ scheme. To dynamically select an appropriate interleaving function with feedback information is a key feature of our system. By computer simulations, we show that the performance of a system with a feedback channel is improved by dynamically selecting an appropriate interleaving function.

Wireless multi-hop networks have drawn much attention for the future generation mobile communication systems. These networks can establish multiple routes from a source node to a destination node because of flexible construction of network topology. Transmissions by multiple routes have enough capability to achieve reliable communication because we can expect to obtain diversity gain by multiple routes. In this paper, we propose the multi-route coding scheme. At first, we discuss a channel model in multi-hop networks employing regenerative relay, which we named the virtual channel model. By using the virtual channel model, a packet is encoded on multiple routes as follows; a bit sequence of a packet is encoded and divided into subpackets, and each subpacket is transmitted on each route. We evaluate its packet error rate performance, and clarify effectiveness of the proposed scheme. In general, we should face degradation of a route condition such as the case when a subpacket does not reach a destination node. Hence, we have to consider the influence of subpacket loss. We also investigate it, and show tolerance of the proposed scheme over that.

In this paper, we define a stopping set of turbo codes with the iterative decoding in the binary erasure channel. Based on the stopping set analysis, we study the block and bit erasure probabilities of turbo codes and the performance degradation of the iterative decoding against the maximum-likelihood decoding. The error floor performance of turbo codes with the iterative decoding is dominated by the small stopping sets. The performance degradation of the iterative decoding is negligible in the error floor region, so the error floor performance is asymptotically dominated by the low weight codewords.

As turbo decoding is a highly memory-intensive algorithm consuming large power, a major issue to be solved in practical implementation is to reduce power consumption. This paper presents an efficient reverse calculation method to lower the power consumption by reducing the number of memory accesses required in turbo decoding. The reverse calculation method is proposed for the Max-log-MAP algorithm, and it is combined with a scaling technique to achieve a new decoding algorithm, called hybrid log-MAP, that results in a similar BER performance to the log-MAP algorithm. For the W-CDMA standard, experimental results show that 80% of memory accesses are reduced through the proposed reverse calculation method. A hybrid log-MAP turbo decoder based on the proposed reverse calculation reduces power consumption and memory size by 34.4% and 39.2%, respectively.

Based on the minimum mean square error (MMSE) detection with iterative soft interference cancellation (SoIC), we propose an adaptive MMSE (A-MMSE) algorithm which acts as an MMSE operator at the beginning of iteration and a maximum ratio combination (MRC) when the interference is nearly cancelled. In our algorithm, a modified metric matrix based on the reliability of soft information from the decoder output is multiplied by the interference part of channel correlation matrix to update the detection operator. The simulation results have shown that this A-MMSE iterative SoIC algorithm can achieve significant performance advantage over the traditional MMSE iterative SoIC algorithm.

We research on an importance sampling (IS) simulation to estimate a low error probability of turbo codes. The simulation time reduction in IS depends on another probability density function (p.d.f.) called simulation p.d.f. The previous IS simulation method can not evaluate the error probability on the low SNR and waterfall region. We derive the optimal simulation p.d.f. which gives the perfect estimator. A new simulation p.d.f. design, which is related to the optimal one, is proposed to overcome the problem of the previous IS method. The proposed IS simulation can evaluate all possible error patterns. Finally, some computer simulations show that the proposed method can evaluate the error probability on the low SNR, waterfall, and error floor regions. At the evaluation of the BER of 10-7, the simulation time of the proposed method is about 1/350 times as short as that of the Monte-Carlo simulation. When the BER is less than 710-8, the proposed method requires shorter simulation time than the conventional IS method.

In this paper, we propose and investigate space-time-frequency turbo coded OFDM transmissions through time-varying and frequency-selective fading channel. The proposed turbo code is a serial concatenated convolutional code which consists of space-frequency and time-frequency domain codes. The aim of the proposed turbo code is to obtain both diversity and coding gains over space-time-frequency domain. Using computer simulations and EXtrinsic Information Transfer (EXIT) charts, we investigate the optimum structure of inner and outer codes. Simulations demonstrate that the proposed system leads to significantly enhanced performance. Moreover, we analyze the computational complexity.

The history of forward error correction in optical communications is reviewed. The various types of FEC are classified as belonging to three generations. The first generation FEC represents the first to be successful in submarine systems, when the use of RS(255, 239) became widespread as ITU-T G.975, and also as G.709 for terrestrial systems. As WDM systems matured, a quest began for a stronger second generation FEC. Several types of concatenated code were proposed for this, and were installed in commercial systems. The advent of third-generation FEC opened up new vistas for the next generation of optical communication systems. Thanks to soft decision decoding and block turbo codes, a net coding gain of 10.1 dB has been demonstrated experimentally. That brought us a number of positive impacts on existing systems. Each new generation of FEC was compared in terms of the ultimate coding gain. The Shannon limit was discussed for hard or soft decision decoding. Several functionalities employing the FEC framing were introduced, such as overall wrapping by the FEC frame enabling the asynchronous multiplexing of different clients' data. Fast polarization scrambling with FEC was effective in mitigating polarization mode dispersion, and the error monitor function proved useful for the adaptive equalization of both chromatic dispersion and PMD.

This paper presents a novel decoding algorithm for turbo codes, in which the likelihood values for redundant parts are updated in order for those values to become more reliable. A criterion for updating the redundant likelihood values is proposed, which is based on the comparisons of the channel values with the re-generated values by the soft-input and soft-output encoders. It is shown that the proposed method can improve the error correcting capabilities, i.e., the improvement of BER/BLER performance and the achievable BER limit.

The maximum a posteriori (MAP) algorithm is the optimum solution for decoding concatenated codes, such as turbo codes. Since the MAP algorithm is computationally complex, more efficient algorithms, such as the Max-Log-MAP algorithm and the soft-output Viterbi algorithm (SOVA), can be used as suboptimum solutions. Especially, the Max-Log-MAP algorithm is widely used, due to its near-optimum performance and lower complexity compared with the MAP algorithm. In this paper, we propose an efficient algorithm for decoding concatenated codes by modifying the Max-Log-MAP algorithm. The efficient implementation of the backward recursion and the log-likelihood ratio (LLR) update in the proposed algorithm improves its computational efficiency. Memory is utilized more efficiently if the sliding window algorithm is adopted. Computer simulations and analysis show that the proposed algorithm requires a considerably lower number of computations compared with the Max-Log-MAP algorithm, while providing the same overall performance.