This paper deals with distributed coding for sensor networks. We consider energy-and-complexity-constrained sensors that communicate with a distant sink at a relatively low data rate with the help of a relay with higher-power and better-processing capabilities. We assume an orthogonal multiple access to the resources. Sources transmit independently and use simple short block codes to limit delay and complexity. The relay performs network encoding of the detected codewords and forwards either partial or complete coded information. The sink jointly decodes observations coming both from sources and relay to simultaneously estimate the information sent by the source nodes. We first analyse the cooperative scheme from an information theoretical point of view in order to determine the resource allocation strategy between the sources and the relay, which maximizes the overall network sum-rate. When a single relay is used and the source-to-relay link is not error-free, occasional detection errors introduce additional errors at the relay output, which, in turn, critically affect decoding performance and yield error-floors at the destination. In the case of a distributed coding scheme based on product codes, we obtain a closed-form asymptotically-tight approximation of the error probability under a minimum-distance decoding of the product code at the destination. The proposed analysis takes explicitly into account the error propagation at the relay output and may be extended to other forms of distributed coding schemes.

The advancements in the field of Digital Video Broadcasting (DVB) have enabled very wide coverages and high capacities in the DVB networks. The advent of Single Frequency Networks (SFN) has played a primary role in making it possible. In this paper we study the distribution of the Signal to Interference Noise Ratio (SINR) for a DVB - 2ndgeneration Terrestrial (DVB-T2)SFN. We also study the relationship of SINR with the distance and the DVB cell size for both indoor and outdoor scenarios. In the end, we demonstrate that the handheld receivers are not properly covered in a DVB-T2 SFN. To highlight the DVB handheld coverage issue, we estimate the handheld receivers' coverage in a SFN designed to cover fixed users.

This paper addresses the problem of decoding and precoding in the K-user MIMO interference channels. At the receiver side, a joint decoding of the interference and the desired signal is able to improve the receive diversity order. At the transmitter side, we introduce a joint linear precoding design that maximizes the joint cut-off rate, known as a tight lower bound on the joint mutual information for high signal-to-noise ratio (SNR). We also derive a closed-form solution of the precoding matrices that maximizes the mutual information when the SNR is close to zero. This solution is characterized by its low computational complexity, and only requires a local channel state information knowledge at the transmitters. Our simulation results show that decoding interference jointly with the desired signal results in a significant improvement of the receive diversity order. Also a substantial bit error rate and sum-rate improvements are illustrated using the proposed precoding designs.

This paper adresses the problem of cooperation application in an existing non-cooperative wireless sensor network. Sensors are low-energy and low-data rate devices. They transmit small independent individually-encoded information packets to the same destination. The cooperation scheme is based on a product code distributed among sources and relays and turbodecoded at the destination. We propose a system where a relay code division multiple access-based transmission is superposed with the sources time division multiple access-scheduled transmissions. A relay interference cancelation algorithm is defined and the whole system is simulated considering source-destination and relaydestination AWGN channels. The source-relay channel is assumed error-free. An optimized energy allocation between the sources and the relay is extracted from simulations.

It is expected that the upcoming DVB-NGH (Digital Video Broadcasting-Next Generation Handheld) shall be based on the existing DVB-T2 technology. Also DVB-NGH enabled Handheld receivers are going to work with the existing DVB infrastructure. In this paper we model the link budget deficits of the Handheld DVB receivers as additional power losses for a typical fixed roof-top DVB-T2 receiver. Because of those additional losses Handhelds get a reduced coverage. The attrition in coverage is especially dramatic for the indoor Handheld receivers. We analyze coverage for two different models of the Population density, i.e. Clark's and Smeed's.

The degree of freedom of the Single Input Single Output (SISO) fading interference channel is asymptotically upperbounded by K/2. This upperbound can be achieved using the Interference Alignment approach (IA), proposed by Cadambe et al., In this work, a new optimized design of the IA scheme is presented. It involves introducing, for each user, a combination matrix so as to maximize the sum rate of the network. The optimal design is obtained via an iterative algorithm proposed in the K-user IA network, and a convergence to a local optimum is achieved. Numerical results enable us to evaluate the performance of the new algorithm and to compare it with other designs.

In this paper, we investigate different HARQ strategies with unreliable feedback channel. In classical approaches, retransmitted packets are different versions of the same user data. In order to improve HARQ performance, we propose to construct redundancy packets by jointly encoding several data packets. This strategy is referred to as HARQ Multiple Packet Incremental Redundancy (MP-IR). It can eliminate imperfect feedback effect on performance at medium to high Signal to Noise Ratio (SNR) values. On the other hand, classical HARQ Single Packet Incremental Redundancy (SP-IR) strategy is more robust at low SNR. This motivates us to introduce a hybrid SP-IR and MP-IR strategy. This strategy can benefit from SP-IR performance at low SNR and MP-IR performance at medium to high SNR. The throughput of the different schemes is analyzed using renewal theory and an appropriate Markov model representation. Simulation results confirming the proposed throughput analysis are also presented.

Most source coding standards (voice, audio, image and video) use Variable-Length Codes (VLCs) for compression. However, the VLC decoder is very sensitive to transmission errors in the compressed bit-stream. Previous contributions, using a trellis description of the VLC codewords to perform soft decoding, have been proposed. Significant improvements are achieved by this approach when compared with prefix decoding. Nevertheless, for realistic VLCs, the complexity of the trellis technique becomes intractable. In this paper, we propose a soft-input VLC decoding method using an a priori knowledge of the lengths of the source-symbol sequence and the compressed bit-stream with Maximum A Posteriori (MAP) sequence estimation. Performance in the case of transmission over an Additive White Gaussian Noise (AWGN) channel is evaluated. Simulation results show that the proposed decoding algorithm leads to significant performance gain in comparison with the prefix VLC decoding besides exhibiting very low complexity. A new VLC decoding method generating additional information regarding the reliability of the bits of the compressed bit-stream is also proposed. We consider the serial concatenation of a VLC with two types of channel code and perform iterative decoding. Results show that, when concatenated with a recursive systematic convolutional code (RSCC), iterative decoding provides remarkable error correction performance. In fact, a gain of about 2.3 dB is achieved, in the case of transmission over an AWGN channel, with respect to tandem decoding. Second, we consider a concatenation with a low-density parity-check (LDPC) code and it is shown that iterative joint source/channel decoding outperforms tandem decoding and an additional coding gain of 0.25 dB is achieved.

The application of distributed coding in many media applications, where low power and low-complexity encoder device is essential, is a new paradigm. In this paper, we propose a new pixel-domain Distributed Video Coding (DVC) scheme, in which both temporal and spatial correlations are exploited at the decoder. The Slepian-Wolf decoder is modified by introducing a source decoder to exploit Wyner-Ziv frame's spatial correlation. We assume the most significant bitplanes to be one-dimensional stationary markov process. The markov characteristic means that this source has a residual redundancy providing additional information for the receiver and can be exploited to correct some errors introduced by the virtual channel, through a joint source-channel decoding scheme.

In this paper, we consider the tracking of mobile terminals based on the received signal strength (RSS) measured from several base stations. The spatial correlation of the random shadowing is exploited in order to improve the position tracking. We define an auto-regressive (AR) model of the temporal evolution of the shadowing. This model allows for performing a joint tracking of the position and the shadowing by applying a Rao- Blackwellized (RB) particle filter approximating the posterior probability distributions numerically. The simulation results show that the tracking can be improved by considering sufficiently high auto-regressive orders.

In cooperative localization, the aim is to compute the locations in Euclidean space of a set of nodes performing pairwise distance measurements. In cases of lack of measurements, several nodes might have multiple feasible solutions meeting the distance constraints. In this paper, we are interested in identifying the nodes that have a unique solution. By employing a semidefmite programming (SDP) formulation of the problem, it is possible to identify only a portion of the uniquely solvable nodes. To improve the identification of these nodes, we develop an iterative algorithm based on SDP. At each iteration, the objective function of the SDP problem is modified in order to identify additional uniquely solvable nodes. We apply this algorithm to study the statistical occurrence of uniquely solvable nodes in uniformly generated networks, and compare the results with the simple SDP. We also investigate the errors in the computed locations for both methods and a variant of the SDP method augmented by bounding constraints on unobserved distances.

Selected mapping (SLM) is considered as a practical probabilistic PAPR reduction method for OFDM systems. A problem of this technique is its high computational complexity due to multiple inverse Fourier transform. We suggest a decimation in frequency IFFT scheme together with an interleaver butterfly ensemble to generate multiple candidates. Orthogonality in the frequency domain is kept and better PAPR reduction performance is achieved without additional complex multiplication. Moreover, we obtain a better error rate over both the AWGN channel and the frequency selective fading channel.

In the absence of the orthogonal design and a very low coding rate channel code, a new bandwidth-efficient multi-user scheme is proposed, which considers random interleavers for different users and multiple antennas at the receiver. Turbo processing is exploited based on the minimum mean square error (MMSE) soft-input soft-output (SISO) detector with interference cancellation (IC) to obtain the receive diversity. The simulation results show that when the number of users K is no more than the product of the number of receive antennas and the reciprocal of the coding rate, the proposed scheme can achieve the single-user performance, which indicates that the uplink user capacity of wireless networks can be dramatically increased with the proposed scheme when more antennas are implemented at the receiver. Meanwhile, it provides a solution to dealing with underdetermined multiple input multiple output (MIMO) systems.

In this paper a novel joint source channel (JSC) decoding technique is presented. The proposed approach enables iterative decoding for serially concatenated arithmetic codes and convolutional codes. Iterations are performed between Soft In Soft Out (SISO) component decoders. For arithmetic decoding, we proposed to employ a low complex trellis search technique to estimate the best transmitted codewords and generate soft outputs. Performance of the presented system are evaluated in terms of PER, in the case of transmission across the AWGN channel. Simulation results show that the proposed JSC iterative scheme leads to significant gain in comparison with a traditional separated decoding. Finally, the practical relevance of the proposed technique is validated under an image transmission system using the SPIHT codec.

In this paper we propose the Arranged List of the Most a priori Likely Tests (ALMLT) algorithm, which is an efficient algorithm for reliability-based soft-decision decoding of long linear block codes. Based on order statistics, we define the mean bit reliabilities and use them to estimate the a priori weight of an error pattern. Each error pattern is represented by a test vector. All the test vectors are sorted according to the increasing order of their weights and saved in a list. Since these weights only depend on the channel SNR, the generation of the list is performed off the transmission. The list of test vectors is then used to decode the received binary sequence similarly as in the Ordered Statistic Decoding (OSD) algorithm. The ALMLT algorithm outperforms the OSD(2) algorithm as illustrated by decoding the binary image of the (255, 239,17) RS code and has a lower mean number of tests, while using the same stopping criterion.

We study the minimum distance of the binary expansion of high-rate Reed-Solomon (RS) codes and product codes in the polynomial basis and show that the binary codes obtained in this way usually have minimum distance equal to the designed symbol minimum distance. We then show that a judicious choice for the code roots may yield binary expansions with larger binary minimum distance and better asymptotic performance. This result is used to design high-rate RS product codes with significantly lower error floors compared to classical constructions.

The genetic code is a key concept in genetics. This code establishes the link between the DNA (desoxyribonucleic acid), composed of nucleic acids, and proteins, composed of amino acids. The genetic code is known to be universal, indeed almost all organisms use this code, and it is degenerated, this means that several sequences of nucleic acids can be translated into the same amino acid. This feature is also present in multiplexed codes which is a new concept recently introduced for robust source coding. In this paper we present a comparison between multiplexed codes and the genetic code. We show why this comparison is relevant, and we point out the fact that the genetic code is almost optimal in the context of multiplexed codes theory.

This letter considers high-rate block turbo codes (BTC) obtained by concatenation of two single-error-correcting Reed-Solomon (RS) constituent codes. Simulation results show that these codes perform within 1 dB of the theoretical limit for binary transmission over additive white Gaussian noise with a low-complexity decoder. A comparison with Bose-Chaudhuri-Hocquenghem BTCs of similar code rate reveals that RS BTCs have interesting advantages in terms of memory size and decoder complexity for very-high-data-rate decoding architectures.

In this paper we propose an image coding scheme based on Block Turbo Codes (BTC) for protecting SPIHT coded images transmitted over wireless channels. An Unequal Error Protection (UEP) scheme using different product codes is also presented. The optimization of the UEP scheme under a transmission budget constraint is investigated. Performance of the proposed system are first evaluated over Gilbert-Elliott (GE) channels. They are then compared to the well-known system of Sherwood and Zeger, through numerical simulations over a single path Rayleigh fading channel. Then, we present an optimized mobile image transmission framework involving a multiuser asynchronous DS-CDMA transmission system over Rayleigh multipath channels. Simulation results for the 512x512 Lena image, transmitted over the ITU Vehicular A channel, show that a significant gain in PSNR is obtained by using the SIC/RAKE multiuser detector in comparison with a conventional detection by the RAKE receiver. Furthermore, performance are also improved when introducing the UEP scheme.

This paper presents a new circuit architecture for turbo decoding, which achieves very high data rates when using product codes as error correcting codes. Although this architecture is independent of the elementary code (convolutional or block) used and of the corresponding decoding algorithms, we focus here on the case of product codes. This innovative circuit architecture stores several data at the same address and performs parallel decoding to increase the data rate. It is able to process several data simultaneously with one memory (classical designs require m memories); its latency decreases when the amount of data processed simultaneously is large. We present results on block turbo decoder designs of 2-data, 4-data and 8-data decoders (where 2, 4 and 8 are the number of data symbols processed simultaneously). For each decoder circuit, the latency is decreased, the area of the processing unit is increased by a factor m and the critical path and memory size are constant (the data rate is increased by m/sup 2/ if we have m parallel decoders).

Advances in the field of information theory have shown that wireless systems using multiple transmitters and multiple receivers can significantly improve the spectral efficiency. Systems using transmit and receive diversity associated with coding such as space time trellis codes have since been developed. A scheme using convolutional turbo codes (CTC) with two transmitters and two receivers has been proposed previously. It exhibits significant gains over space time trellis codes (up to 6 dB at a BER of 10/sup -5/). Our purpose is to extend that study to block turbo codes (BTC). We use the (32, 26, 4) extended BCH product code with two kinds of modulation (QPSK and 16-QAM). Simulations show that BTC associated with transmit and receive diversity perform as well as CTC in terms of the coding gains while achieving higher spectral efficiencies.

In this paper, we propose a complete transmission system for still images which minimizes the distortion introduced by residual transmission errors. This system comprises a source encoder combining DCT (discrete cosine transform) and VQ (vector quantization). The compression rate is equal to 16.7 for an average PSNR (peak signal to noise ratio) of 29.2 dB. The data are then encoded by a BCH (63,57,3) block code and mapped on a 64-QAM constellation. The parameters of the code book and channel encoder have been optimized for 64-QAM. For channel decoding, we use maximum likelihood sequence decoding. The PSNR of the reconstructed image in the receiver is equal to 28.6 dB for a channel SNR of 11 dB. This represents a very small degradation of the PSNR (0.6 dB) in presence of a SER (symbol error rate) of 10% at the input of the receiver.

This paper describes an iterative decoding algorithm for any product code built using linear block codes. It is based on soft-input/soft-output decoders for decoding the component codes so that near-optimum performance is obtained at each iteration. This soft-input/soft-output decoder is a Chase decoder which delivers soft outputs instead of binary decisions. The soft output of the decoder is an estimation of the log-likelihood ratio (LLR) of the binary decisions given by the Chase decoder. The theoretical justifications of this algorithm are developed and the method used for computing the soft output is fully described. The iterative decoding of product codes is also known as the block turbo code (BTC) because the concept is quite similar to turbo codes based on iterative decoding of concatenated recursive convolutional codes. The performance of different Bose-Chaudhuri-Hocquenghem (BCH)-BTCs are given for the Gaussian and the Rayleigh channel. Performance on the Gaussian channel indicates that data transmission at 0.8 dB of Shannon's limit or more than 98% (R/C>0.98) of channel capacity can be achieved with high-code-rate BTC using only four iterations. For the Rayleigh channel, the slope of the bit-error rate (BER) curve is as steep as for the Gaussian channel without using channel state information.

In addition to the source coding artifacts, the encoded bit streams representing codeword indexes of a vector quantized image are vulnerable to transmission or media impairments. Impulse block noise in the received images is the main artifact due to transmission errors. We use the fuzzy set theory to represent the vague concept of a block similarity with its spatial context. This approach is conducted in order to detect and to conceal the transmission errors. Error concealment by searching the best matching codeword is an attractive alternative to the commonly used interpolation approach. It reduces considerably the computational complexity at the receiver end. Simulation results show that the proposed method considerably improves the subjective quality of VQ images transmitted over noisy channels.