This paper addresses the design of practical short-length coding schemes for Distributed Hypothesis Testing (DHT). While most prior work on DHT has focused on information-theoretic analyses—deriving bounds on Type-II error exponents via achievability schemes based on quantization and quantize-binning—the practical implementation of DHT coding schemes has remained largely unexplored. Moreover, existing practical coding solutions for quantization and quantize-binning approaches were developed for source reconstruction tasks considering very long code lengths, and they are not directly applicable to DHT. In this context, this paper introduces efficient short-length implementations of quantization and quantize-binning schemes for DHT, constructed from short binary linear block codes. Numerical results show the efficiency of the proposed coding schemes compared to uncoded cases and to existing schemes initially developed for data reconstruction. In addition to practical code design, the paper derives exact analytical expressions for the Type-I and Type-II error probabilities associated with each proposed scheme. The provided analytical expressions are shown to predict accurately the practical performance measured from Monte Carlo simulations of the proposed schemes. These theoretical results are novel and offer a useful framework for optimizing and comparing practical DHT schemes across a wide range of source and code parameters.

Orthogonal time frequency space (OTFS) modulation is widely acknowledged as a prospective waveform for future wireless communication networks. To provide insights for the practical system design, this paper analyzes the outage probability of OTFS modulation with finite blocklength. To begin with, we present the system model and formulate the analysis of outage probability for OTFS with finite blocklength as an equivalent problem of calculating the outage probability with finite blocklength over parallel additive white Gaussian noise (AWGN) channels. Subsequently, we apply the equivalent noise approach to derive a lower bound on the outage probability of OTFS with finite blocklength under both average power allocation and water-filling power allocation strategies, respectively. Finally, the lower bounds of the outage probability are determined using the Monte-Carlo method for the two power allocation strategies. The impact of the number of resolvable paths and coding rates on the outage probability is analyzed, and the simulation results are compared with the theoretical lower bounds.

This paper investigates practical coding schemes for Distributed Hypothesis Testing (DHT). While the literature has extensively analyzed the information-theoretic performance of DHT and established bounds on Type-II error exponents through quantize and quantize-binning achievability schemes, the practical implementation of DHT coding schemes has not yet been investigated. Therefore, this paper introduces practical implementations of quantizers and quantize-binning schemes for DHT, leveraging short-length binary linear block codes. Furthermore, it provides exact analytical expressions for Type-I and Type-II error probabilities associated with each proposed coding scheme. Numerical results show the accuracy of the proposed analytical error probability expressions, and enable to compare the performance of the proposed schemes.

We explore the problem of distributed Hypothesis Testing (DHT) against independence, focusing specifically on Binary Symmetric Sources (BSS). Our investigation aims to characterize the optimal quantizer among binary linear codes, with the objective of identifying optimal error probabilities under the Neyman-Pearson (NP) criterion for short code-length regime. We define optimality as the direct minimization of analytical expressions of error probabilities using an alternating optimization (AO) algorithm. Additionally, we provide lower and upper bounds on error probabilities, leading to the derivation of error exponents applicable to large code-length regime. Numerical results are presented to demonstrate that, with the proposed algorithm, binary linear codes with an optimal covering radius perform near-optimally for the independence test in DHT.

We consider correlated sources coding over a up-link non-orthogonal multiple access shadowed κ-µ fading channel. The sufficient condition for lossless coding is determined by the intersection of the Slepian-Wolf region and multiple access channel region, assuming source-channel separation holds. The exact expression for the outage probability upper bound is derived by dividing the sufficient conditions into three cases. The accuracy of the analytical results is verified by the Monte-Carlo simulations. The analytical results indicate that more than 2ndorder diversity gain can be achieved with a larger ratio of line-of-sight dominant component in single cluster or multiple clusters with non-line-of-sight component. It is also found that the shadowed κ-µ fading well represents one-sided Gaussian, Rayleigh, Rician, and Nakagami-m fading in calculating the outage probability. Furthermore, the ϵ-outage achievable rate is analyzed, which is found to be larger with higher source correlation and/or average signal-to-noise ratio.

In this paper, we conduct rate-distortion and outage probability analyses for Wyner-Ziv (WZ) systems, where the information sequences from a source and a helper are transmitted to the destination over block Rayleigh fading multiple access channels (MACs). This work has been motivated by decision-making systems, where the aim is to make right decisions based on the observations. Hence, the most critical performance metric is the accuracy of decisions, even allowing distortion in wireless transmission. A sufficient condition for the successful transmissions is that the WZ and MAC regions intersect. For the ease of calculating the outage probability, we propose an approximated, yet accurate, WZ rate region. The outage probabilities of the WZ systems are then evaluated both in orthogonal and MAC transmissions. It is shown that the transmission efficiency of the system with MAC is significantly improved compared to orthogonal transmission. Furthermore, a helper-selection scheme is introduced to further reduce the outage probability of the WZ-MAC systems. The results show that the outage probability decreases, of which decay corresponds to the (L+1)-order diversity with L helpers in small value range of the average signal-to-noise ratio (SNR), while it converges into L as the average SNR becomes large.

This paper focuses on a lossy transmission of binary symmetric source (BSS) with down-link non-orthogonal multiple access (DL-NOMA). The transmitted binary sequences are lossy-compressed descriptions of the same BSS, which are overlapped in a specified signal format, corresponding to the receivers with pre-determined distortion requirements. Despite a higher spectrum efficiency achieved by DL-NOMA, redundancy may still remain if the overlapped descriptions are correlated. In this work, a system combining DL-NOMA and successive refinement, referred to as DN-SR, is proposed. Specifically, instead of re-constructing the source by a single description, the receiver can achieve a low distortion by first recovering the basic description, and then refining it with the help of another refinement description. If the two descriptions are made independent, transmission efficiency of the conventional DL-NOMA can be further improved. As the main contribution, this paper derives the outage probability of DN-SR in closed-form, assuming block Rayleigh fading channels. The advantage of DN-SR is numerically studied in terms of the system outage probability, compared to both the conventional DL-NOMA, and a modified DL-NOMA which exploits the correlation between descriptions, referred to as DN-CE. Finally, the optimal power allocation to the two descriptions is investigated for DN-SR, aiming to minimize the system outage probability.

The$L$-link binary Chief Executive Officer (CEO) problem under logarithmic loss is investigated in this paper. A quantization splitting technique is applied to convert the problem under consideration to a$(2L-1)$-step successive Wyner-Ziv (WZ) problem, for which a practical coding scheme is proposed. In the proposed scheme, Low-Density Generator-Matrix (LDGM) codes are used for binary quantization while Low-Density Parity-Check (LDPC) codes are used for syndrome generation; the decoder performs successive decoding based on the received syndromes and produces a soft reconstruction of the remote source. The simulation results indicate that the rate-distortion performance of the proposed scheme can approach the theoretical inner bound based on binary-symmetric test-channel models.

This paper presents an in-depth performance analysis of lossy communications in a single-relay system, where the recovered information is not necessarily lossless in both the relay and the destination. In this system, the relay continues transmitting the sequence with source-relay (S-R) link errors to the destination even if errors are detected after decoding, i.e., so-called lossy-forward (LF) strategy. The problem can be decomposed into two parts as follows: a point-to-point coding problem in the S-R link and a lossy source coding problem with an LF relay in the source-destination (S-D) and a relay-destination (R-D) links. To begin with, we derive the admissible rate region of the lossy source coding problem with the LF relay for a specified distortion requirement. Then, we focus on the analysis of outage probability over block Rayleigh fading channels. Finally, a practical encoding/decoding scheme is proposed for the evaluation of system performance by computer simulations. Due to the suboptimal channel coding and incomplete utilization of joint typicality, the theoretical performance cannot be achieved in the simulation; however, the tendency of curves in simulations matches that in theoretical calculation.

Wireless sensor networks (WSNs) are the core component in the big data era. Due to the unreliable transmission environment, it is significantly useful to introduce a helper to refine the system performance. To begin with, we formulate the system model of WSNs as a problem of multiterminal source coding. Subsequently, we propose a 3D distributed compress-bin scheme and derive a corresponding inner bound by analyzing the expected rate-distortion. Finally, we investigate the performance improvement of a helper by comparing the derived inner bound with the Berger-Tung inner bound and through simulation. Both the theoretical bounds and simulation results indicate that a helper can obviously improve the system performance.

In this work, we investigate the MARC (Multiple Access Relay Channel) setup, in which two Markov sources communicate to a single destination, aided by one relay, based on Joint Source Channel Network (JSCN) LDPC codes. In addition, the two source nodes compress the information sequences with an LDPC source code. The compressed symbols are directly transmitted to both a relay and a destination nodes in two transportation phases. Indeed, the relay performs the concatenation of the received compressed sequences to obtain a recovered sequence, which is encoded with an LDPC channel code, before being forwarded to the destination. At the receiver, we propose an iterative joint decoding algorithm that exploits the correlation between the two sources-relay data and takes into account the errors occurring in the sources-relay links to estimate the source data. We show based on simulation results that the JSCN coding and decoding scheme into a MARC setup achieves a good performance with a gain of about 5 dB compared to a conventional LDPC code.

Non-orthogonal transmission is considered to be one of the promising techniques for improving the throughput of the existing and future wireless communication networks. We concentrate on the transmission of both independent and correlated binary sources over a non-orthogonal multiple access relay channel (MARC), which consists of two sources, one relay, and one destination. The lossy decode-and-forward (DF), developed from the conventional DF, is adopted at the relay. Two time slots are required with non-orthogonal transmission over such network setup, while three time slots are required with the conventional orthogonal transmission. We analyze the outage probability of transmission of independent binary sources over the non-orthogonal MARC based on the theorem of multiple access channel (MAC) with a helper, which combines the Slepian-Wolf rate region and the MAC capacity region. For the performance verification, we implement a practical coding-decoding chain, which is applicable to the transmission of both independent and correlated binary sources. Exclusive-OR based multi-user complete decoding is introduced at the relay node, and iterative joint decoding is utilized at the destination by taking into consideration the estimated intra-link error probability and correlation information between the sources. The practical simulation results are well matched with the theoretical analyses.

Inter-block-interference (IBI) caused in the pursuit of spectral efficiency can deteriorate channel estimation performance. For this problem, previously-proposed chained turbo estimation performs IBI cancelation by using the soft replica of the transmitted signal. The IBI cancelation technique can, however, suffer from a mean squared error (MSE) floor problem, since the soft replica is unavailable at the first turbo iteration. The IBI problem can be avoided by using channel impulse response length constraint. Nevertheless, as shown in this paper, the IBI avoidance approach is difficult to perform independently since it requires unbiased second-order statistics. This paper proposes, therefore, a new conditional ℓ1 regularized minimum mean square error channel estimation algorithm by jointly utilizing the IBI avoidance/cancelation and subspace techniques. Simulation results verify that the proposed algorithm solves the MSE floor problem, and, hence, improves the bit error rate convergence performance in realistic IBI channels including the effect of pulse shaping filters.

In this paper, we design a unified framework decoder for relay systems with iterative decoding. In the proposed scheme, the source node needs to transmit a correlated content to a destination with the help of a relay. Then, a distributed Joint Source Channel (JSC) Low-Density-Parity-Check (LDPC) encoding is applied at the source and the relay. The destination receives simultaneously the source compressed data from the source node, and the source/channel encoded data from the relay node. The cooperative network is mapped into a factor graph on which message passing iterative decoding is applied to estimate the source information. The JSC decoder takes into account the source-relay correlation which involves remarkable improvements even if errors occur at the source-relay link. The Bit Error-Rate (BER) system performance are investigated for different scenario, according to the relay position, and it is shown that the performance of the proposed cooperative scheme is typically about 0.5–1.0 dB better than an equivalent rate point-to-point system.

We investigate the end-to-end outage probability over a multi-source multi-relay network assuming that all the wireless links are suffering from independent block fading variations. The overall transmission is divided into two tandem hops. The first hop represents the transmission between sources and relays, while the relays transmit to the destinations in the second hop. We consider specifically a two-source two-relay single-destination network. Based on the decoding process at the relays, the data recovery at the relays can be classified into three cases based on achievable bounded rate regions. The first case where both relays cannot recover both users' data can be characterized as chief executive officer problem at the second hop. For the second case, the relays recover the data of both users, and the outage probability of the second hop can be computed by exploiting maximum ratio transmission. Finally, for the third case, only one of the users' data is recovered by one of the relays, and the outage probability of the second hop can be calculated by using the theorem of source coding with helper. Numerical results closely follow the theoretical analysis and confirm the improved performance of the multiple-antenna relaying over the single-antenna relaying.

We design rateless codes for correlated multi-source relay networks over packet erasure channels. In particular, we optimize relay combining process of distributed Luby transform (DLT) codes for a multi-source single-relay network where information data is correlated among the sources. Density evolution is used to characterize the asymptotic performance in terms of unrecovered information symbols termed as erasure rate. By exploiting the decoding graph, we derive the closed form expressions for asymptotic performance of DLT codes in a network where correlated sources transmit to a single destination via a relay. Consequently, a design framework is developed to optimize the degree distributions in terms of overhead. It is shown that the proposed DLT codes significantly outperform existing DLT coding schemes in terms of erasure and success rates. Numerical examples are provided to verify the asymptotic analysis. Numerical results also confirm the performance gain of the proposed DLT code as compared to its uncorrelated counterparts in the finite-length regime.

The binary chief executive officer (CEO) problem with an arbitrary number of agents is considered in this paper. A scheme which separates the reconstruction of observations and the final decision of a common source is assumed. Hence, we first derive the outer bound for the rate- distortion region by providing the converse proof of a binary multiterminal source coding problem which is the key to solve the binary CEO problem. The distortion of the binary CEO problem is then determined by the Poisson binomial process based on the using majority voting logic for the final decision. The rate-distortion behavior of the binary CEO problem is then analyzed based on the outer bound by solving a convex optimization problem. It is found that the distortion decreases until it converges to a certain level, as the sum rate and/or the number of agents increases.

Joint optimization of power allocation (PA) and relay position (RP) is investigated for a lossy-forwarding relaying in order to minimize the outage probability. We investigate adaptive PA with fixed relay position, adaptive RP with fixed PA ratio, and joint optimization of the PA and RP under total transmit power constraint. A closed-form expression of the outage probability is derived at the high signal-to-noise ratio regime. It is shown that the closed-form expression is sufficiently accurate compared to numerical calculation results. Then, the optimum PA and the optimum RP can be formulated as a convex optimization problem. It is found that the system performance with the adaptive optimum PA outperforms that with equal power allocation. The outage performance with the adaptive optimum RP outperforms that with midpoint RP. However, the joint optimization of the PA and RP is superior to the semi-adaptive optimization algorithms.

A two-node binary chief executive officer (CEO) problem is investigated. Noise-corrupted versions of a binary sequence are forwarded by two nodes to a single destination node over orthogonal additive white Gaussian noise (AWGN) channels. We first reduce the binary CEO problem to a binary multiterminal source coding problem, of which an outer bound for the rate-distortion region is derived. The distortion function is then established by evaluating the relationship between the binary CEO and multiterminal source coding problems. A lower bound approximation on the Hamming distortion (HD) is obtained by minimizing a distortion function subject to constraints obtained based on the source-channel separation theorem. Encoding/decoding algorithms using concatenated convolutional codes and a joint decoding scheme are used to verify the lower bound on the HD. It is found that the theoretical lower bounds on the HD and the computer simulation-based bit error rate performance curves have the same tendencies. The differences in the threshold signal-to-noise ratio between the theoretical lower bounds and those obtained by simulations are around 1.5 dB in AWGN channel. The theoretical lower bound on the HD in block Rayleigh fading channel is also evaluated by performing Monte Carlo simulation.

Broadband wireless channels observed at a receiver cannot fully exhibit dense nature in a low to moderate signal-to-noise ratio (SNR) regime, if the channels follow a typical propagation scenario such as Vehicular-A or Pedestrian-B. It is hence expected that ℓ1-regularized channel estimation methods can improve channel estimation performance in the broadband wireless channels. However, it is well-known that the ℓ2 multiburst (MB) channel estimation achieves the Cramér-Rao bound (CRB) asymptotically. This is because the ℓ2 MB technique formulated as a minimum-mean-square-error (MMSE) problem improves the mean squared error (MSE) performance by utilizing the subspace projection. Performance analysis shows that ℓ1-regularized channel estimation does not improve the MSE performance significantly over the ℓ2 MB technique so far as the subspace channel model assumption is correct. We demonstrate, however, a receiver with ℓ1-regularized channel estimation can improve bit error rate (BER) performance if the assumption is not always correct. For this purpose, we focus on intermittent transmission (TX) scenario which is defined as a generalized TX sequence having arbitrary length interruption between two continuous TX bursts. A receiver with the ℓ2 MB method suffers from BER deterioration in an intermittent TX scenario having abrupt channel changes. As a solution to the problem, we propose a new algorithm which is a hybrid of ℓ1-regularized least square (LS) and ℓ2 MMSE channel estimation techniques. Simulation results show that the receiver with the proposed algorithm achieves a significant BER gain over that of the ℓ2 MB technique in the intermittent TX scenario.

Peak-to-average power ratio (PAPR) constrained power allocation for multicarrier transmission in multiuser single-input multiple-output (SIMO) communications is considered in this paper. Reducing the PAPR in any transmission system is beneficial because it allows the use of inexpensive energy-efficient power amplifiers. In this paper, we formulate a power allocation problem for single-carrier (SC) frequency division multiple access (FDMA) and orthogonal FDMA (OFDMA) transmission with instantaneous PAPR constraints. Moreover, a statistical approach is considered in which the power variance of the transmitted waveform is controlled. The constraints for the optimization problems are derived as a function of transmit power allocation and two successive convex approximations (SCAs) are derived for each of the constraints based on a change of variables (COV) and geometric programming (GP). In addition, the optimization problem is constrained by a user-specific quality of service (QoS) constraint. Hence, the proposed power allocation strategy jointly takes into account the channel quality and the PAPR characteristics of the power amplifier. The numerical results show that the proposed power allocation strategy can significantly improve the transmission efficiency of power-limited users. Therefore, it is especially beneficial for improving the performance for cell edge users.

This paper proposes a Partial Hybrid Automatic Repeat reQuest (P-HARQ) scheme where the relaying nodes select either forwarding the erroneous packets or requesting retransmission. In contrast to the conventional technique where the erroneous packets is always discarded, the packets found to have errors after decoding are interleaved, re-encoded, and forwarded if relay selects the forwarding mode. This technique is refer to as lossy forwarding. In this paper, the mode selection (either forwarding or requesting retransmission) is based on the confidence indicator (CI). Since the channels are assumed to suffer from block Rayleigh fading, the CI is calculated via online mutual information measurements, block-by- block. Results of computer simulations conducted to confirm the superiority of the proposed P-HARQ technique in terms of bit-error-rate, packet-error-rate and throughput performances in parallel multihop wireless multirelaying systems, are presented.

An outage probability that is independent of signaling schemes is theoretically derived in this paper for an orthogonal multiple-access relay channel (MARC) system, where the estimates of the information sequences sent from source nodes, regardless of whether or not they are correctly decoded at the relay, are exclusive-OR (XOR)-network-coded and forwarded by the relay to the destination. The MARC system described above is referred to as estimates-exploiting MARC (e-MARC) in this paper for convenience. Following the probability derivation of e-MARC, comparisons are then made with the outage probability of the orthogonal MARC with the Select Decode-and-Forward relaying strategy (MARC-SDF). It is found through simulations that when one of the source nodes is far away from both the relay and the destination, the e-MARC system is superior to MARC-SDF in terms of outage performance. We further numerically calculate the outage probabilities for two special cases, and compare them with the probability of e-MARC. Furthermore, the impact of the source correlation on the outage probability of the e-MARC system is also investigated.

Transmission power variance constrained power allocation in single carrier multiuser (MU) single-input multiple-output (SIMO) systems with iterative frequency domain (FD) soft cancelation (SC) minimum mean squared error (MMSE) equalization is considered in this paper. It is known in the literature that peak to average power ratio (PAPR) at the transmitter can be decreased by reducing the variance of the transmit power. In this paper, we derive a power variance constraint to statistically control the PAPR. This constraint is plugged into a convergence constrained power allocation (CCPA) problem and successive convex approximation (SCA) approach via series of geometric programs (GP) is developed. Numerical results are presented in the form of complementary cumulative distribution functions (CCDFs) to demonstrate the effectiveness of the proposed method.

This paper proposes an extrinsic information transfer (EXIT)-chart based optimization technique of LDPC codes for the transmission of quantized Gauss-Markov (GM) source samples over additive white Gaussian (AWGN) noise channels. A joint source and channel (JSC) decoding technique of the proposed code is also devised. In the proposed scheme, no interleaving is performed between the source and the JSC encoder so that the decoder can well exploit the relatively low entropy of the source with memory compared to memory-less sources. At the transmitter, the quantized samples are converted to bit sequences with an injective mapping and the bit sequences are encoded using a systematic binary LDPC code. The proposed JSC decoder is a concatenation of a multi-state BCJR Markov decoder and a sum-product (SP) LDPC decoder. Decoding thresholds of the optimized codes at certain code rates are investigated for both uniform and Lloyd-Max quantizations in different numbers of bits. The decoding thresholds are close to the Gaussian code book Shannon limits for code rate Rc≤ 0.5, although the gap to the Shannon limit notably increases at the higher rates. Finally, the simulation results confirm the significant improvement of coding gain on the bit error rate (BER) performances of the optimized LDPC codes with both the quantization schemes.

Peak to average power ratio (PAPR) constrained power allocation in single carrier multiuser (MU) single-input multiple-output (SIMO) systems with iterative frequency domain (FD) soft cancelation (SC) minimum mean squared error (MMSE) equalization is considered in this paper. To obtain full benefit of the iterative receiver, its convergence properties need to be taken into account also at the transmitter side. In this paper, we extend the existing results on the area of convergence constrained power allocation (CCPA) to consider the instantaneous PAPR at the transmit antenna of each user. In other words, we will introduce a constraint that PAPR cannot exceed a predetermined threshold. By adding the aforementioned constraint into the CCPA optimization framework, the power efficiency of a power amplifier (PA) can be significantly enhanced by enabling it to operate on its linear operation range. Hence, PAPR constraint is especially beneficial for power limited cell-edge users. In this paper, we will derive the instantaneous PAPR constraint as a function of transmit power allocation. Furthermore, successive convex approximation is derived for the PAPR constrained problem. Numerical results show that the proposed method can achieve the objectives described above.

In this paper, we theoretically analyze the outage probability of decode-and-forward (DF) relaying system allowing intra-link errors (DF-IE), where the relay always forwards the decoder output to the destination regardless of whether errors are detected after decoding in the information part or not. The results apply to practical fading scenarios where all the links between the nodes suffer from independent block Rayleigh fading. The key idea of DF-IE system is that the data sequence forwarded by the relay is highly correlated with the original information sequence sent from the source, and hence with a proper joint decoding technique at the destination, the correlation knowledge can well be exploited to improve the system performance. We analyze this problem in the information theoretical framework of correlated source coding. Using the theorems for lossy source-channel separation and for source coding with side information, the exact outage probability is derived. It is then shown that the exact expression can be reduced to a simple, yet accurate approximation by replacing the theorem for source coding with side information by the Slepian-Wolf theorem. Compared with conventional DF relaying where relay keeps silent if errors are detected after decoding, DF-IE can achieve even lower outage probability. Moreover, by allowing intra-link errors, the optimal position of the relay is found to be exactly the midpoint between the source and destination. Results of the simulations are provided to verify the accuracy of the analytical results.

In this paper, we consider the problem of transmitting two correlated binary sources over orthogonal multiple access relay channel (MARC), where two sources are communicating with a common destination with the assistance of a single relay. We assume decode-and-forward relaying strategy, and bit-wise exclusive or (XOR) network coding is performed at the relay node. First, a joint source-channel-network (JSCN) decoding technique is proposed to fully exploit the correlation between the sources, as well as the benefit of network coding. Then the achievable compression rate region of this system is derived based on the theorem for source coding with side information. It is found that the region is a 3-dimensional space surrounded by a polyhedron. Furthermore, the performance limit in Additive White Gaussian Noise (AWGN) channels and the outage probability in block Rayleigh fading channels are derived based on the achievable compression rate region. It is shown that the outage probability can be expressed by a set of triple integrals over the achievable compression rate region. The impact of source correlation on the performance of the system is investigated through asymptotic tendency analysis. The effectiveness of the proposed JSCN decoding technique and the accuracy of the theoretical analysis have been verified through a series of computer simulations, assuming practical channel codes. It is also shown that, as long as the source-relay links are perfect, the 2nd order diversity is always achieved with our proposed technique regardless of the strength of the source correlation.

We propose a novel joint decoding technique for distributed source-channel (DSC) coded systems for transmission of correlated binary Markov sources over additive white Gaussian noise (AWGN) channels. In the proposed scheme, relatively short-length, low-density parity-check (LDPC) codes are independently used to encode the bit sequences of each source. To reconstruct the original bit sequence, a joint source-channel decoding (JSCD) technique is proposed which exploits the knowledge of both temporal and source correlations. The JSCD technique is composed of two stages, which are iteratively performed. First, a sum-product (SP) decoder is serially concatenated with a BCJR decoder, where the knowledge of source memory is utilized during local (horizontal) iterations. Then, the estimate of correlation between the sources is used to update the concatenated decoder during global (vertical) iterations. Therefore, the correlation of the sources is assumed as side information in the subsequent global iteration of each concatenated decoder. From the simulation results of frame/bit error rate (FER/BER), we note that significant gains are achieved by the proposed decoding scheme with respect to the case where the correlation knowledge is not completely utilized at the decoder.

In this paper, the outage probability of a Slepian-Wolf transmission system is analysed theoretically. We consider two correlated binary information sequences where bit-flipping model is adopted, where the the information bits of the second source are the flipped version of the information bits of the first one, with a probability Pf. Here, we extend our previous work of the correlated sources transmission over block Rayleigh fading channels to such that the channel between one source and the destination is assumed to suffer from block Rayleigh fading, whereas the channel between the other source and the destination is assumed to suffer from block Rician fading. The outage probability is analysed theoretically. The results show that when Pf= 0, the outage curves versus signal-to-noise power ratio (SNR) exhibits sharper decay than that with the 2nd order diversity, as the line-of-sight (LOS) component power of Rician channel increases. It is also found that the outage curves asymptotically converge in to that with the 1st order diversity when Pf≠ 0. Furthermore, this paper also determines the optimal power allocation under the condition that total transmit power of the system is kept constant. It can be concluded that increasing the ratio of LOS component power of Rician channels can not always improve the outage performance, so far as Pf≠ 0.

Data inherently including memory can be compressed using either equal or variable length coding. This paper proposes a novel method to compress the data with memory by using equal length code words while maintaining the error correction capability. The main drawback of variable length coding (VLC) is that because of the boundary problem, it is very sensitive to errors, which results in many cases in long burst errors due to error propagation. However, VLC is optimal in the sense of minimizing the expected length of the codeword. To reduce the compression rate using equal length code, a technique called multiple label mapping (MLM) is employed in this paper. Furthermore, MLM is extended with a fine tuning block to achieve compression rates as close to the Shannon limit as possible. Simulation results for symbol error rate (SER) evaluation as well as EXIT analysis indicate that the proposed technique can achieve compression rates very close to the VLC performance while maintaining the error correction capability. Furthermore, it is shown that the SER performance of the proposed joint source-channel coding scheme is very close to the Shannon limit.

This paper proposes a simple coding structure with iterative spatial demapper (ISM) for single carrier transmission of two correlated sources (with instantaneous power control) over fading multiple access channel (Fading MAC) where the receiver has only a single receive antenna. The correlation between the sources is exploited via vertical iteration (VI) loop between the two decoders and analyzed based on the Slepian-Wolf (SW) coding theorem. The proposed structure, of which potential applications are sensor or relay systems requiring relatively small number of the transmission phases, can achieve turbo-like performance over Fading MAC even with short memory convolutional codes (CC). The rate-1 doped accumulator (DACC) is used to flexibly adapt the variation of the correlation between the sources which makes the convergence tunnel between the demapper and decoder open until a point very close to (1,1) mutual information (MI) point. The results of computer simulations confirm that the proposed structure can achieve close performance to the Slepian-Wolf/Shannon limit of two correlated sources using single transmission phase.

A goal of this paper is to theoretically derive the outage probability of the correlated source transmission in block Rayleigh fading channels. The correlation between the two information sources is assumed to be expressed by the bit flipping model, where the information bits transmitted from the second transmitter are the flipped version of the information bits transmitted from the first one, with a probability pe. The source sequences are independently channel-encoded, and then transmitted to the destination block-by-block via different time- or frequency-slots. The channels are assumed to be suffering from independent block Rayleigh fading. This paper shows that the outage probability of this system can be expressed by double integrals with respect to the probability density functions (pdf) of the instantaneous signal-to-noise power ratios (SNRs) of those channels, where the range of the integration is determined by the Slepian-Wolf theorem. The most significant finding made by this paper is that the asymptotic diversity order is one so far as pe is non-zero, and the 2nd order diversity can be achieved only if pe = 0. The major applications of this paper's results include outage evaluation of extract-and-forward (EF) relay systems allowing intra-link (source-relay link) errors, sensor networks, and wireless mesh networks. The latter half of this paper provides results of outage probability calculations for one-way EF relay scenario utilizing the concept of the technique presented in this work.

In this paper, we propose a new joint source-channel decoding technique for transmitting binary Markov sources over AWGN channels. Our approach is based on serially concatenated coding and code doping for inner code. By combining the Markov source and the outer code trellis diagrams, a super trellis is constructed to exploit the time-domain correlation of the source. A modified version of BCJR algorithm is derived based on this super trellis, that can achieve considerable gain in terms of mutual information. The standard BCJR algorithm is used for decoding of inner code where code doping is adopted for better matching of extrinsic information transfer (EXIT) characteristics. EXIT chart analysis is performed to investigate convergence property of the proposed technique and to optimize the code parameters. Simulation results for bit error rate (BER) evaluation and EXIT chart analysis indicate that the proposed technique can achieve significant gains over the system in which source redundancy are not exploited, and thereby the BER performance of the proposed system is very close to the Shannon limit.

We consider the uplink of a time-slotted wireless communication system with a mobile user and a base station equipped with an antenna array of M elements. The space-time varying channel of the system is usually estimated using training sequence in each slot and refined by projecting it to the corresponding spatial signal subspace. However, this method does not work when the space-time channel matrix is full row rank. In this paper, we formulate the channel by a Sylvester matrix using the space-time signal model for this full row rank case and propose a channel estimation method based on the space-time signal subspace projection. We also propose a channel estimation method that incorporates the extended training symbols by the soft information fed back from the decoder to improve the channel estimation performance. Numerical results show that these two methods can be performed separately or jointly to improve the performance of the space-time channel estimation by training sequences.

Two energy and computationally efficient strategies are proposed for Multiple Access Relay Channel (MARC), where all links are suffering from block fading. By exploiting the error probabilities of the intra links, defined as the links between sources and relay, relay can still utilize the received frames, even though they may contain errors, and forward them rather than discard them. This makes efficient utilization of the information of those erroneous frames and thereby reduces the frame error rate (FER). Moreover, by applying differential encoding at sources following the recursive convolutional encoding, differential detection can be used at relay for recovering the received signals from the sources; with the use of differential detection, signals can be recovered without requiring heavy computational burden for channel estimation, and hence, as a whole the necessity of the use of very powerful limit-achieving codes can also be avoided. This leads to energy efficient relay strategies.

In this paper, we propose three low-complexity strategies for Multiple Access Relay Channel (MARC) based on the concept of bit-flipping model. By estimating the error rates of the links between the sources and the relay, and by utilizing the estimate as side information at the destination, it is shown that the proposed relay strategies are superior to the Decode-and-Forward (DF) relay strategy when all links are suffering from Additive White Gaussian Noise (AWGN). Furthermore, extrinsic information transfer (EXIT) analysis is used to track the convergence property with the aim of being able to search for suitable codes, the proposed relay strategies can achieve the performance close to those strategies utilizing relatively strong codes, such as turbo code or LDPC code, with iterative decoding at the relay in order to make intra links error free.

This paper addresses the problem of power allocation for single carrier point-to-point multiple input multiple output (MIMO) systems with iterative frequency-domain (FD) soft cancellation (SC) minimum mean squared error (MMSE) equalization. Two novel heuristic power allocation methods are proposed. The proposed methods explicitly take into account the convergence properties of the iterative equalizer while transmission power is minimized. The proposed heuristic schemes are based on, convergence constraint power allocation (CCPA), technique that decouples the spatial interference between streams using singular value decomposition (SVD), and minimize the transmission power while achieving the target mutual information for each stream after iterations at the receiver side. The proposed heuristic transmission schemes are inspired by well-known greedy algorithm resulting in a simple and efficient solutions to the power allocation problem. Numerical results show that the proposed heuristic schemes can achieve close to optimal performance in the terms of equalizer convergence as well as the total transmission power.

This paper proposes chained turbo equalization (CHATUE) algorithm, a simple detection scheme for block transmission without guard interval (GI), where turbo equalizers for the several consecutive frames exchange information about the interference components. Although the block transmission without GI can significantly increase bandwidth efficiency, the received signal suffers from inter-block interference (IBI) and intersymbol interference (ISI), which can't be effectively compensated by block-by-block equalization.With the CHATUE algorithm, the IBI components are cancelled by utilizing a posteriori feedback from the decoders of the neighboring equalizers (future and past). To best utilize the latest results of the sub-optimal reduced complexity equalization, frequency domain soft cancellation and minimum mean squared error filtering (FD/SC-MMSE), we exploit J matrix to convert the Toeplitz channel matrix structure to a circulant matrix. Results of the computer simulation for single carrier block transmission (SCBT) show that the proposed scheme can achieve good performance.

This paper proposes a technique to compress the data with equal length code words. A novel source coding technique, multiple label mapping (MLM), is introduced. With MLM it is possible to produce a source code which uses equal length code words. Moreover, it is shown that with the MLM technique, it is possible to achieve near limit compression without using variable length coding (VLC). However this requires that the source probability grouping is performed so that after MLM each code word has almost equal appearance probability, and that full a priori feedback is available. Numerical results demonstrate proper operability of the proposed system.

This paper proposes a capacity-approaching, yet simple scheme for multi-input multiple-output (MIMO) channels. The proposed scheme is based on a concatenation of a mixture of short memory-length convolutional codes or repetition codes and a short, and simple rate-1 linear block code, followed by either 1-dimensional (1-D) anti-Gray or Gray mapping of quadrature phase-shift keying (QPSK) modulation. By interpreting the rate-1 code and the 1-D mapping as a multi-D mapping performed over multiple transmit antennas, the error performance is analyzed in two regions. In the error-floor region, a tight union bound and the corresponding design criterion on the asymptotic performance are derived. The bound provides a useful tool to predict the error performance at relatively low bit error rate (BER) values. Based on the obtained design criterion, an optimal rate-1 code for each 1-D mapping is then constructed to achieve the best asymptotic performance. In the turbo pinch-off region, by using extrinsic information transfer (EXIT) charts, the most suitable mixed codes are selected for both symmetric and asymmetric antenna configurations. It is demonstrated that the simple concatenation scheme can achieve a near-capacity performance over the MIMO channels. Furthermore, its error performance is shown to be comparable to that obtained by using well-designed irregular LDPC and RA codes, and therefore, the proposed scheme significantly outperforms a scheme employing a parallel concatenated turbo code. Simulation results in various cases are provided to verify the analysis.

We consider the problem of rate allocation in frequency-selective 2-user Gaussian multiple access fading channels employing turbo equalization. The turbo equalization framework used in this paper contains a soft cancellation frequency domain minimum mean squared error equalizer and two a posteriori probability channel decoders. Using the relationship between the rate of any code and the area under its corresponding decoder extrinsic information transfer (EXIT) function, we derive an upper bound on the rate region of the 2-user turbo system, given the EXIT characteristic of the equalizer for a particular channel realization. With the rate region upper bound, we then study the problem of maximizing the sum rate of both users, and provide an approximate solution to this optimization problem. Based on the obtained result, a practical code selection algorithm for rate allocation at both transmitters is proposed. In addition, we discuss the extension of the proposed algorithm to an outage-based rate allocation approach. Numerical results of capacity calculations and throughput simulations are presented to demonstrate the performance enhancement achieved by the proposed rate allocation technique over automatic repeat request with fixed coding rate.

This paper proposes a capacity-approaching, yet simple scheme over a multiple-input single-output (MISO) wireless fading channel, which is very common in the downlink of a cellular system. The proposed scheme is based on a concatenation of a mixture of short memory-length convolutional codes or repe

This paper proposes a simple yet capacity-approaching concatenation of a mixture of short memory length convolutional codes and simple rate-1 block code followed by either complex 1-dimensional (1-D) anti-Gray or Gray mapping over multiple antenna channels with quadrature phase-shift keying (QPSK). By interpreting rate-1 code together with 1-D mapping as a multi-D mapping employed over multiple transmit antennas, the error performance is analyzed in two regions, the error-floor and turbo pinch-off regions. In the former one, a tight union bound and design criterion on the asymptotic performance are first derived, which provide an useful tool to predict the error performance. Based on the design criterion, an optimal rate-1 code for each 1-D mapping is then constructed to achieve the best asymptotic performance. In the turbo pinch-off area, by using extrinsic information transfer (EXIT) chart, the most suitable mixed codes are selected for both symmetric and asymmetric antenna setups. It is demonstrated that the simple concatenation scheme can achieve near-capacity. Furthermore, its error performance is comparable to that obtained by using well-designed irregular low-density parity-check (LDPC) and repeat accumulate (RA) codes, and thereby, outperforms a scheme employing a parallel concatenated turbo code.

This paper proposes a near-capacity yet simple bit-interleaved coded modulation with iterative decoding (BICM-ID) scheme by employing a multi-dimensional (multi-D) mapping technique in a multi-D constellation carved from a rotated lattice. Using extrinsic information transfer (EXIT) charts, it is shown that the proposed technique fits well with simple convolutional codes in terms of the area property, for which turbo pinch-off can happen at a low Eb/N0value. In particular, both EXIT chart analysis and simulation results indicate that by using just a simple convolutional code together with a 4-D mapping, a turbo pinch-off and a bit error rate (BER) close to 10-6happen at a signal-to-noise ratio (SNR) that is even lower than the BICM constraint capacity limit with a uniform input. The proposed BICM-ID scheme can be considered as an attractive alternative to other bandwidth-efficient coded modulation techniques using powerful turbo-like codes such as turbo or low-density parity-check (LDPC) codes over a Rayleigh fading channel.

This paper proposes a novel linear precoder design technique for single carrier single-user multiple input multiple output (MIMO) systems with frequency-domain (FD) soft cancellation (SC) minimum mean squared error (MMSE) iterative equalization where the convergence properties of the equalizer are taken into account. The proposed precoder design technique, convergence constrained precoding (CCP), minimizes the transmission power while it achieves the target mutual information for each stream after the iterations at the receiver side. We show that the optimality criterion for the proposed design can be formulated as a convex optimization problem. The results demonstrate that our proposed technique outperforms the existing linear precoding techniques by ensuring the convergence with a reduced transmission power. Furthermore, we show that with CCP we can adjust transmission according to convergence properties of the iterative equalizer in a more flexible way than, e.g., minimum sum mean squared error (MinSumMSE) and maximum information rate (MaxRate) precoding.

Performances of BICM-ID systems strongly depend on the matching between mapping rule and code structure. This paper proposes a combined use of extended mapping (EM) and simple repetition code. Even with such a simple structure, turbo cliff happens at a value range of signal-to-noise power ratio (SNR) 1~2 dB to the Shannon limit. This paper then introduces check node as well as irregular node degree allocation to the proposed structure described above, so that we can flexibly change the shape of the decoder EXIT curve. It is shown that EXIT analysis and chain simulation results exactly match each other.

In this the paper, impact of minimum mean squared error (MMSE) based linear precoding on the convergence of iterative multiuser detector in multiuser multiple input multiple output (MIMO) uplink single carrier communications is studied. The influence of linear precoding on iterative MMSE based multiuser detector is investigated via the multi-dimensional EXIT analysis. It is shown that the use of the linear precoding enhances the separability of the EXIT planes of the simultaneous streams over without precoding; This invokes the idea that different code rate be allocated to the each transmitted streams at the transmitter. Especially, in the case of multiuser communication precoding has significant roles in the convergence property of iterative detector.

In this paper, we address the problem of multiple-input multiple-output (MIMO) spatial multiplexing (SM) systems in the presence of antenna fading correlation. It is well known that severe spatial correlations present at the transmitter and/or receiver can significantly compromise the performance of existing SM systems. Recent results showed that joint-over-antenna (JA) iterative detection schemes can improve the performance of SM systems in correlated channels as compared to schemes that detected the signals on an antenna-by-antenna basis. We extend this idea in this paper by incorporating a so-called antenna doping (AD) scheme into the SM system, in order to further counteract the detrimental effects of spatial correlation. Through simulations, we show that AD can improve the performance by 3-4 dB in severe spatial correlation as compared to non-doping systems. This improvement is explained with the aid of extrinsic information transfer (EXIT) charts, which illustrate the convergence behavior of the JA iterative detection with and without AD.

In this paper, we introduce adaptive link control techniques for multiple-input multiple-output (MIMO) systems with broadband single-carrier signaling. Soft cancellation and minimum mean squared error turbo equalization is assumed, where matching between coding and equalization plays crucial roles to achieve high throughput. This paper uses multilevel coded bit-interleaved coded modulation (ML-BICM) with linear mapping as a core part of the transmission, on top of which this paper applies automatic repeat request (ARQ) with adaptive coding (AC) for link control. The reason behind the use of the linear mapping ML-BICM is the separability between the layers in the modulation format: This should bring us a significant benefit in designing the link control strategies because each layer has its own reliability, and the adaptive link control should be optimized based on the each layer's reliabilities. For ARQ with ML-BICM, we introduce layer-by-layer retransmission control, where turbo equalization and retransmission control can be performed independently over the layers because of the layer-separability. The layer-by-layer concept is then applied to AC with ML-BICM, where the code parameters such as code rate and generator polynomials are chosen so that after several iterations the mutual information between the transmitted and the soft-input soft-output decoder output information can reach a value very close to one while minimizing the rate loss due to the mismatch between the equalization and decoder. Extrinsic information transfer analysis is performed for the MIMO channel realization being given. The transmitter is notified of the selected codes for the each layer via the feedback channel, and uses the selected codes for the following transmission, assuming that the channel state information (CSI) stays the same at least over two consecutive frames. Finally, this paper evaluates the throughput performances of the ML-BICM ARQ and AC techniques using multidimensional field measurement data. The performance tendencies are correlated with propagation properties, obtained as results of the high-resolution channel analysis, such as spatial spreads at the transmitter and receiver sides.

This letter presents an adaptative soft-based method for channel estimation in turbo receivers. The proposed approach is based on the particular algebraic structure of multipath Rayleigh-fading channels, and it is suited for mobile systems where the multipath pattern (namely, the times of delay) changes slowly over the time. The method is implemented through a rank-and-subspace tracking algorithm that allows to adapt the estimate to the multipath variations and also to reduce the computational cost with respect to the batch implementation based on eigenvalue decomposition. A performance analysis, in terms of mean square error of the channel estimate and bit error rate, shows the advantages of the proposed technique in communications over time-varying wireless channels

A frequency domain soft-interference canceling minimum mean-square error (MMSE) turbo equalizer is studied. A computationally efficient method for computing extrinsic information transfer (EXIT) function of the equalizer is proposed. The method is based on the Gaussian approximation for the equalizer output and it produces an approximate EXIT chart in a fraction of computational load compared to previous numerical methods. The accuracy of the method is verified for both single-input single-output (SISO) and multiple-input multiple output (MIMO) channels

Multiuser multiple-input-multiple-output (MIMO) wireless systems have great potential in improving information rate, diversity and resistance to against interference. The primary objective of this paper is to derive for broadband signaling a new iterative frequency domain (FD) multiuser MIMO signal detection technique for joint-over-antenna (JA) detection. The proposed detector is based on soft-cancellation and minimum mean square error (MMSE) filtering, followed by maximum a posteriori probability (MAP) detector to detect several of each users transmit antennas. The purpose of jointly detecting several transmit antennas is to preserve the degrees of freedom (DoF) for MMSE. Computational complexities with FD and its time domain (TD) counterpart are evaluated in this paper, and it is shown that FD requires significantly lower complexity than TD. Numerical results show that JA significantly outperforms the receiver that detects transmit antenna signals antenna-by- antenna (AA). The proposed iterative FD JA technique achieves larger performance gains compared to AA when the total number of transmit antennas is larger than the number of receiver antennas, as well as in the presence of spatial correlation.

Convergence properties of frequency domain turbo equalization with multilevel bit-interleaved coded modulation (MLBICM) and bit-interleaved coded modulation (BICM) are studied in measured quasi-static fading channels by the means of semi-analytical convergence analysis. Spatial channel parameters are matched to the reached mutual information on a per-measurement basis and trends in the behavior of the equalizer are obtained, when the channel characteristics, in terms of transmit and receive side azimuth spreads, change. Robust convergence of frequency-domain turbo equalization combined with multilevel BICM is demonstrated through the convergence analysis. Three channel codes are evaluated in the measurement-based simulation showing the effects of outer code selection

Turbo MIMO equalization in a space-time-trellis-coded (STTrC) system is considered in this paper. First, a low complexity MMSE equalizer is derived for decoding of STTrC-coded signals in frequency selective channels. The receiver is further modified so that only the significant portion of the channel impulse response is taken into consideration. The remaining (nonsignificant) portion of the channel impulse response is regarded as unknown co-channel interference (UCCI) and suppressed using the covariance estimation technique. Its performance is evaluated using measurement data obtained by the multidimensional channel sounder. The receiver performance is shown to be within 2 dB from the maximum-likelihood lower bound, which takes into account all multipath components.

A computationally efficient space-time turbo equalization algorithm is derived for frequency selective multiple-input multiple-output (MIMO) channels. The algorithm is an extension of the iterative equalization algorithm by Reynolds and Wang (2001) for frequency selective fading channels. This paper's proposed equalizer performs MIMO channel estimation, multiple user signal detection, and decoding, jointly all in an iterative manner. The iterative channel estimator achieves high accuracy in estimating channel parameters even if only a relatively small number of unique word symbols are available. The multiple user signal detector (MUSD) consists of soft interference cancellers for the multiple users, each followed by a minimum mean square error (MMSE) filter. With this simple structure, the proposed detector achieves a drastic reduction in computational complexity compared with conventional trellis-based turbo equalizers. Simulation results show the proposed equalizer can properly separate multiple user signals in frequency selective MIMO channels.

This paper proposes a new iterative ISI equalization algorithm that offers low computational complexity: order L/sup 2/ with channel memory length L. The proposed algorithm is an extension of D. Reynolds and Xiaodong Wang's SC/MMSE (soft canceller followed by MMSE filter) equalizer (see Signal Processing, vol.81, no.5, p.989-95, 2001): approximations are used properly to reduce the computational complexity. It is shown that the approximations used in the proposed algorithm do not cause any serious performance degradation compared to the conventional trellis-based iterative equalization algorithms.

A diversity combining scheme, adaptive RAKE diversity (ARD), is proposed for a differential phase-shift keying (DPSK) direct sequence code division multiple access (DS/CDMA) mobile communications system. The ARD scheme minimizes the mean squared errors in the diversity combiner output. This suppresses the effects of the interference only paths in the time window for path diversity combining. Bit error rate (BER) performances with the proposed ARD and conventional equal gain combining (EGC) schemes are evaluated through laboratory experiments and compared. Block error rate (BKER) performance with the ARD scheme is also evaluated experimentally. Based upon the BKER evaluation results, an error correction scheme is proposed that is suitable for error occurrence characteristics of ARD output.>

The path diversity improvement inherent within direct sequence spread spectrum (DS/SS) signalling in multipath propagation environments is investigated for mobile/personal radio communications systems that employ DPSK modulation. The bit error rate (BER) performance of post-demodulation selection diversity reception is theoretically analyzed in the presence of noise-only-paths in the time window for diversity combining. Results of laboratory experiments conducted to evaluate the BER performance are also presented. It is shown that the experiment results agree well with the theoretical BER.>

The codeword error rate (WER) performance of noncoherent frequency-shift keying with soft decision decoding of block codes using Chase's second algorithm (1972) is investigated in a Rayleigh fading channel. The received signal envelope is sampled and used as channel measurement information. The theoretical upper and lower bounds of the WER are derived, assuming independent Rayleigh envelope samples in a received block. When the Golay (23, 12, 7) code is used, soft decision decoding with 6-bit error correction capability (3-bit error and 3-bit erasure) requires an average signal-to-noise power ratio about 5 dB lower than that for minimum distance decoding with 3-bit error correction to obtain a WER=10/sup -3/. The effects of bit interleaving on the WER performance when fading envelope variation is slow compared to the bit rate are investigated through computer simulations.>