A Novel Cooperative Communication System Based on Multilevel Convolutional Codes

The authors propose a system where single antenna mobile users share antennas to transmit their information cooperatively to the common base station. Each mobile user overhears the coded information transmitted by other users, detects it and further encodes it along with its own information. The encoding is done using multilevel coding scheme with convolutional codes as component codes. The proposed system considers the self-information of user u at level u to reduce complexity while decoding. The coded symbols are mapped to M-ary quadrature amplitude modulation constellation using multi-resolution modulation partitioning. This enables the component codes to be designed for lower order constellation. Each cooperative user transmits multilevel coded symbols to the common base station, thus creating transmit diversity. The base station receives noisy superposition of independent Rayleigh faded signals transmitted by cooperative users and pass it through a multistage decoder. The multistage decoder employs maximum likelihood based Viterbi decoder at each stage to detect the information of each user. The Viterbi decoder applies max-log approximation to reduce the branch metric complexity. The proposed cooperative multilevel coding system outperforms non-cooperative multilevel coding system and is less complex than the existing cooperative multilevel coding system.     

Iterative multiuser interference reduction: turbo CDMA

We view the asynchronous random code division multiple-access (CDMA) channel as a time-varying convolutional code. We study the case where the users encode their data, and, therefore, the single user transmitters and the CDMA channel appear as the concatenation of two coding systems. At the receiver we employ serial turbo decoding strategies. Unlike conventional turbo codes where both the inner and outer code may be selected, in our case, the inner code is due to the CDMA channel which we assume to be random. Nevertheless, the decoding system resembles the decoder of a serial turbo code and single-user performance is obtained even for numbers of users approaching the spreading code length     

基于 G.722.1 的分布式语音编码

在语音通信网络中，为获得良好的语音通信质量，抗丢包技术不可或缺。为此，本文基于 ITU G.722.1 语音编码器，提出一种分布式语音编码方法。该方法在 G.722.1 编码器的基础上，构建一个互补编码器；然后在编码端，对同一帧语音分别用 G.722.1 编码器和其互补编码器进行语音编码，并发送编码结果；在解码端，在接收到其中任一语音码流时，用 G.722.1 解码器进行解码，其语音质量不低于 G.722.1 编码器的解码结果，而在接收到两个语音码流时，用 G.722.1 解码器先分别对两个语音码流进行解码，然后对解码结果进行联合处理，其最终的语音质量有明显提升，即有一定编码增益。仿真实验结果表明，本文分布式语音编码方法的抗丢包效果明显，相对于原始编解码器其语音质量进一步提升。      

Soft-decision COVQ for turbo-coded AWGN and Rayleigh fadingchannels

A robust soft-decision channel-optimized vector quantization (COVQ) scheme for turbo coded additive white Gaussian noise (AWGN) and Rayleigh fading channels is proposed, The log likelihood ratio (LLR) generated by the turbo decoder is exploited via the use of a q-bit scalar soft-decision demodulator. The concatenation of the turbo encoder, modulator, AWGN channel or Rayleigh fading channel, turbo decoder, and q-bit soft-decision demodulator is modeled as an expanded discrete memoryless channel (DMC). A COVQ scheme for this expanded discrete channel is designed. Numerical results indicate substantial performance improvements over traditional tandem coding systems, COVQ schemes designed for hard-decision demodulated turbo coded channels (q=1), as well as performance gains over a recent soft decoding COVQ scheme by Ho (see IEEE Commun. Lett., vol.3, p.208-10, 1999)     

Bandwidth-efficient turbo trellis-coded modulation using puncturedcomponent codes

We present a bandwidth-efficient channel coding scheme that has an overall structure similar to binary turbo codes, but employs trellis-coded modulation (TCM) codes (including multidimensional codes) as component codes. The combination of turbo codes with powerful bandwidth-efficient component codes leads to a straightforward encoder structure, and allows iterative decoding in analogy to the binary turbo decoder. However, certain special conditions may need to be met at the encoder, and the iterative decoder needs to be adapted to the decoding of the component TCM codes. The scheme has been investigated for 8-PSK, 16-QAM, and 64-QAM modulation schemes with varying overall bandwidth efficiencies. A simple code choice based on the minimal distance of the punctured component code has also been performed. The interset distances of the partitioning tree can be used to fix the number of coded and uncoded bits. We derive the symbol-by-symbol MAP component decoder operating in the log domain, and apply methods of reducing decoder complexity. Simulation results are presented and compare the scheme with traditional TCM as well as turbo codes with Gray mapping. The results show that the novel scheme is very powerful, yet of modest complexity since simple component codes are used     

Joint (3,k)-regular LDPC code and decoder/encoder design

Recently, low-density parity-check (LDPC) codes have attracted a lot of attention in the coding theory community. However, their real-world applications are still problematic mainly due to the lack of effective decoder/encoder hardware design approaches. In this paper, we present a joint (3,k)-regular LDPC code and decoder/encoder design technique to construct a class of (3,k)-regular LDPC codes that not only have very good error-correcting capability but also exactly fit to high-speed partly parallel decoder and low-complexity encoder implementations. We also develop two techniques to further modify this joint design scheme to achieve more flexible tradeoffs between decoder hardware complexity and decoding speed.     

Iterative decoding of codes over complex numbers for impulsive noise channels

We discuss the decoding of error-correcting block codes over complex numbers for the transmission over impulsive noise channels. The encoder multiplies a vector of complex information symbols resulting from a modulation scheme, e.g., quadrature amplitude modulation (QAM), with a unitary generator matrix G. Choosing the inverse Fourier transform as G, the encoding procedure is similar to orthogonal frequency-division multiplex (OFDM) modulation. The maximum a posteriori (MAP) receiver is analyzed and a suboptimum decoder based on the turbo decoding principle is derived. Simulation results show the excellent performance of the iterative decoder.     

一种CQI辅助的HARQ改进方案

下一代移动通信系统在高速移动的条件下,需要更高的吞吐量和更大的带宽。这就需要采用更好的信道编码（turbo码等）、HARQ策略和信道均衡技术。但是,turbo译码是一个复杂的过程,在进行信号处理时会耗费用户大量的时间和功率。因此与turbo译码相关的HARQ策略会对系统性能产生很大影响。提出了一种CQI辅助的HARQ策略。这种策略主要利用了已经测量得到的CQI来跳过HARQ在首次传输和重传过程中不必要的解调和译码过程。通过采用HARQ策略,当误帧率高于门限时可以节省UE端大约55%的功率。     

Joint source and channel coding using turbo codes over rings

Turbo codes are a practical solution for achieving large coding gains. We present a new turbo coding scheme where the component codes are convolutional codes (CCs) over the ring of integers modulo M, with M being the alphabet size of the source encoder. The a priori knowledge of the source statistics is used during the iterative decoding procedure for improved decoder performance. As an example of application, we examine differential pulse code modulation (DPCM) encoded image transmission     

Permuted M-matrices for the reduction of phase-induced intensity noise in optical CDMA network

Two codeword families and the corresponding encoder/decoder schemes are present for spatial/frequency optical code-division multiple-access communications. These 2-D codewords have multiple weights per row and can be encoded/decoded via compact hardware. With the proposed decoding mechanism, the intended user will reject interfering users and multiple-access interference is fully eliminated. In addition, the power of the same wavelength contributed by all interfering codewords is split and detected by distinct photodiodes in the decoder. Thus the performance degradation due to the beat noise arising in the photodetecting process is improved, as compared with the traditional 1-D coding scheme, and a larger number of active users is supported under a given bit-error rate.     

A Reconfigurable ASIP for Convolutional and Turbo Decoding in an SDR Environment

Future mobile and wireless communication networks require flexible modem architectures to support seamless services between different network standards. Hence, a common hardware platform that can support multiple protocols implemented or controlled by software, generally referred to as software defined radio (SDR), is essential. This paper presents a family of dynamically reconfigurable application-specific instruction-set processors (ASIPs) for channel coding in wireless communication systems. As a weakly programmable intellectual property (IP) core, it can implement trellis-based channel decoding in a SDR environment. It features binary convolutional decoding, and turbo decoding for binary as well as duobinary turbo codes for all current and upcoming standards. The ASIP consists of a specialized pipeline with 15 stages and a dedicated communication and memory infrastructure. Logic synthesis revealed a maximum clock frequency of 400 MHz and an area of 0.11 mm$^{2}$ for the processor's logic using a low power 65-nm technology. Memories require another 0.31 mm$^{2}$ . Simulation results for Viterbi and turbo decoding demonstrate maximum throughput of 196 and 34 Mb/s, respectively. The ASIP hence outperforms state-of-the-art decoder architectures targeting software defined radio by at least a factor of three while consuming only 60% or less of the logic area.      

Joint source-channel turbo coding for binary Markov sources

We investigate the construction of joint source-channel (JSC) turbo codes for the reliable communication of binary Markov sources over additive white Gaussian noise and Rayleigh fading channels. To exploit the source Markovian redundancy, the first constituent turbo decoder is designed according to a modified version of Berrou's original decoding algorithm that employs the Gaussian assumption for the extrinsic information. Due to interleaving, the second constituent decoder is unable to adopt the same decoding method; so its extrinsic information is appropriately adjusted via a weighted correction term. The turbo encoder is also optimized according to the Markovian source statistics and by allowing different or asymmetric constituent encoders. Simulation results demonstrate substantial gains over the original (unoptimized) Turbo codes, hence significantly reducing the performance gap to the Shannon limit. Finally, we show that our JSC coding system considerably outperforms tandem coding schemes for bit error rates smaller than 10/sup -4/, while enjoying a lower system complexity.     

Near-optimal decoding for coded and power-controlled DS-CDMA downlink

We first present the traditional decoding approach that employs the common pilot-channel-based maximal ratio combining and the Viterbi or iterative decoding cannot achieve the optimal error-rate performance for downlink direct-sequence code-division multiple-access (CDMA) signals when a fast power control technique is applied together with a convolutional or turbo coding. Then, as an efficient method to realize a nearly optimal decoding, we propose a branch metric power readjustment (BMPR) technique, where the downlink power control command generated by the mobile station is used not only to adjust the base station power in the transmitter side, but also to readjust the decoder input branch metric power in the receiver side. Numerical results show that the BMPR technique applied to the IMT-2000 wideband-CDMA system can improve the transmit power utilization by up to 0.4 dB for the block-error rate of 10/sup -2/.     

乘积码基于相关运算的迭代译码

乘积码是一种能以Turbo码的思想实现译码的级联码，具有一般编码无法达到的纠错能力。本文提出一种新的乘积码迭代译码算法，其核心思想是通过输出软信息与接收软信息进行线性迭加的方式来实现反馈，此时只须提供-1和1组成的软输出矩阵就能获得很高的编码增益，仿真表明，将子译码器译码后的结果再进行一次相关运算作为软输出，译码性能可以得到进一步的提高。     

A unified turbo/Viterbi channel decoder for 3GPP mobile wireless in 0.18-/spl mu/m CMOS

A channel decoder chip compliant with the 3GPP mobile wireless standard is described. It supports both data and voice calls simultaneously in a unified turbo/Viterbi decoder architecture. For voice services, the decoder can process over 128 voice channels encoded with rate 1/2 or 1/3, constraint length 9 convolutional codes. For data services, the turbo decoder is capable of processing any mix of rate 1/3, constraint length 4 turbo encoded data streams with an aggregate data rate of up to 2.5 Mb/s with 10 iterations per block (or 4.1 Mb/s with six iterations). The turbo decoder uses the logMAP algorithm with a programmable logsum correction table. It features an interleaver address processor that computes the 3GPP interleaver addresses for all block sizes enabling it to quickly switch context to support different data services for several users. The decoder also contains the 3GPP first channel de-interleaving function and a post-decoder bit error rate estimation unit. The chip is fabricated in a 0.18-/spl mu/m six-layer metal CMOS technology, has an active area of 9 mm/sup 2/, and has a peak clock frequency of 110.8 MHz at 1.8 V (nominal). The power consumption is 306 mW when turbo decoding a 2-Mb/s data stream with ten iterations per block and eight voice calls simultaneously.     

On iterative decoding in some existing systems

Iterative decoding is used to achieve backward compatible performance improvement in several existing systems. Concatenated coding and iterative decoding are first set up using composite mappings, so that various applications in digital communication and recording can be described in a concise and uniform manner. An ambiguity zone detection (AZD) based iterative decoder, operating on generalized erasures, is described as an alternative for concatenated systems where turbo decoding cannot be performed. The described iterative decoding techniques are then applied to selected wireless communication and digital recording systems. Simulation results and utilization of decoding gains are discussed     

Iterative threshold decoding without interleaving for convolutional self-doubly orthogonal codes

A novel iterative error control technique based on the threshold decoding algorithm and new convolutional self-doubly orthogonal codes is proposed. It differs from parallel concatenated turbo decoding as it uses a single convolutional encoder, a single decoder and hence no interleaver, neither at encoding nor at decoding. Decoding is performed iteratively using a single threshold decoder at each iteration, thereby providing good tradeoff between complexity, latency and error performance.     

Turbo Receiver for Multicarrier Spread Spectrum Systems Employing Parity Bit Selected Spreading Sequences

In this paper a turbo receiver for multicarrier spread spectrum systems employing parity bit selected spreading code (MC-SS-PB) is proposed where detection and decoding are performed iteratively for each detected bit in the receiver. In MC-SS-PB systems, the parity bits generated by a linear block encoder are used to select a spreading code from a set of orthogonal spreading sequences. The selected spreading code is then used to spread the signals in all subcarriers. In the proposed receiver, soft information passes between the detector and the decoder on multiple iterations. Detection is performed by using the received signal in combination with the extrinsic likelihood provided by a soft input soft output decoder. The turbo receiver is further extended to a multiple user system where the multiple access interference is estimated in each iteration and subtracted out from the received signal. Simulations show a significant reduction in bit error rates when a turbo receiver is used in these systems.     

Turbo Decoding as Iterative Constrained Maximum-Likelihood Sequence Detection

The turbo decoder was not originally introduced as a solution to an optimization problem, which has impeded attempts to explain its excellent performance. Here it is shown, that the turbo decoder is an iterative method seeking a solution to an intuitively pleasing constrained optimization problem. In particular, the turbo decoder seeks the maximum-likelihood sequence (MLS) under the false assumption that the input to the encoders are chosen independently of each other in the parallel case, or that the output of the outer encoder is chosen independently of the input to the inner encoder in the serial case. To control the error introduced by the false assumption, the optimizations are performed subject to a constraint on the probability that the independent messages happen to coincide. When the constraining probability equals one, the global maximum of the constrained optimization problem is the maximum-likelihood sequence detection (MLSD), allowing for a theoretical connection between turbo decoding and MLSD. It is then shown that the turbo decoder is a nonlinear block Gauss-Seidel iteration that aims to solve the optimization problem by zeroing the gradient of the Lagrangian with a Lagrange multiplier of -1. Some conditions for the convergence for the turbo decoder are then given by adapting the existing literature for Gauss-Seidel iterations     

Multistage Iterative Decoding With Complexity Reduction for Concatenated Space–Time Codes

Space–time encoders exploiting concatenated coding structures are efficient in attaining the high rates available to large-dimensional multiple-transmitter, multiple-receiver wireless systems under fading conditions, while also providing maximal diversity benefits. We present a multistage iterative decoding structure that takes full advantage of the concatenated nature of the transmission path, treating the modulator and channel stages as an additional encoder in serial concatenation. This iterative decoder architecture allows an encoder employing decoupled coding and modulation to reach the performance of coded modulation systems. It also admits reduced-complexity decoding with a computational load that is nonexponential in the number of antennas or the transmission bit rate, and makes practical decoding for large transmitter arrays possible. The performance curves for these methods follow the shape of the Fano bound, with only a modest power penalty.