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This paper considers a device-to-device (D2D) fog-radio access network wherein a set of users are required to store/receive a set of files. The D2D devices are connected to a subset of the cloud data centers and thus possess a subset of the data. This paper is interested in reducing the total time of communication, i.e., the completion time, required to disseminate all files among all devices using instantly decodable network coding (IDNC). Unlike previous studies that assume a fully connected communication network, this paper tackles the more realistic scenario of a partially connected network in which devices are not all in the transmission range of one another. The joint optimization of selecting the transmitting device(s) and the file combination(s) is first formulated, and its intractability is exhibited. The completion time is approximated using the celebrated decoding delay approach by deriving the relationship between the quantities in a partially connected network. The paper introduces the cooperation graph and demonstrates that the problem is equivalent to a maximum weight clique problem over the newly designed graph. Extensive simulations reveal that the proposed solution provides noticeable performance enhancement and outperforms previously proposed IDNC-based schemes. [ABSTRACT FROM PUBLISHER]

In this paper, we show how the presence of locality within a binary cyclic code can be exploited to improve decoding performance and to reduce decoding complexity. We pursue two approaches. Under the first approach, we show how the ordered statistics decoding (OSD) method can be modified by inserting a simple single round belief-propagation step at the start that involves only the local codes. The resultant locality-aware OSD algorithm yields an appreciable signal-to-noise ratio (SNR) gain for a given level of reliability and essentially the same level of decoder complexity. Under the second, trellis decoding approach, we show that the careful introduction of locality results in the creation of a cyclic subcode that possesses lower maximum state complexity. In addition, we present a simple means of deriving an upper bound to the state complexity profile of any cyclic code that is based only on the zeros of the code. Furthermore, we show how the decoding speed of either locality-aware OSD or trellis decoding can be significantly increased in the presence of locality, in the moderate-to-high SNR regime, by making the use of a quick-look decoder that often returns the maximum likelihood code word. [ABSTRACT FROM AUTHOR]

This paper presents a simple and very flexible method for constructing quasi-cyclic (QC) low density parity-check (LDPC) codes based on finite fields. The code construction is based on two arbitrary subsets of elements from a given field. Some well known constructions of QC-LDPC codes based on finite fields and combinatorial designs are special cases of the proposed construction. The proposed construction in conjunction with a technique, known as masking, results in codes whose Tanner graphs have girth 8 or larger. Experimental results show that codes constructed using the proposed construction perform well and have low error-floors. Also presented in the paper is a reduced-complexity iterative decoding scheme for QC-LDPC codes based on the section-wise cyclic structure of their parity-check matrices. The proposed decoding scheme is an improvement of an earlier proposed reduced-complexity iterative decoding scheme. [ABSTRACT FROM PUBLISHER]

In this paper, we devise a fast encoding algorithm for triply extended Reed–Solomon codes. The proposed approach requires approximately two XORs per bit, which improves the prior result of three XORs per bit established by certain maximum distance separable (MDS) array codes. We also prove that, for MDS codes with two and three parities, the scheduling algorithms require at least two XORs per bit. To the best of our knowledge, this is the first provable scheduling algorithm for the triple-parity MDS codes to approach the theoretical lower bounds. The implementation with SIMD instructions is provided. The simulations show that the proposed approach is competitive, as compared with other cutting edge implementations. [ABSTRACT FROM AUTHOR]

A source coding problem in which a central source has to satisfy the demands of several receivers, with each receiver having some subset of the messages (side-information) held by the source is considered. The source has knowledge of only the cardinality of the side-information at each receiver. The encoding scheme used by the source to transmit at a higher throughput is referred to as an informed source code. A technique to obtain informed source codes by using $\ell $ -th Near Maximum Distance Separable (Near-MDS) Codes is presented. The advantage of using $\ell $ -th Near-MDS codes is the reduction in field size required. For certain informed source coding problems, the code obtained from $\ell $ -th Near-MDS codes is shown to be of the minimum length under certain field size restrictions. The same technique can be used for a given index coding problem to obtain index codes. The index codes obtained through this technique are optimal for, but not limited to, special cases of index coding problems discussed in the paper. Finding an optimal solution to a general index coding problem is NP hard and this technique helps in finding binary suboptimal solutions. Using the Gilbert-Varshamov bound, an upper bound on the lengths of optimal binary informed source codes is obtained. [ABSTRACT FROM PUBLISHER]

In this paper, we propose a new multi-edge metric-constrained quasi-cyclic progressive edge-growth algorithm (MM-QC-PEGA), which is suitable for constructing both single- and multi-weighted (binary) QC low-density parity-check (LDPC) codes with arbitrary lengths, rates, circulant sizes, and variable node (VN)-degree distributions. The MM-QC-PEGA is able to detect all cyclic-edge-set-minimum-virtual cycles (CMVCs), as it accurately computes the metric value of each CMVC with an a posteriori test. In addition, we propose a new greatest-common-divisor (GCD)-approximation for time efficiently approximating the metric value of a CMVC without a posteriori tests, and propose a new GCD-approximated MM-QC-PEGA (G-MM-QC-PEGA) by using the GCD-approximation to replace the a posteriori test involved in the MM-QC-PEGA. As a result, the G-MM-QC-PEGA is faster than the MM-QC-PEGA, and the CMVCs undetectable to the G-MM-QC-PEGA under multi- and single-weighted QC-LDPC code graphs have minimum lengths of eight and ten, respectively. Moreover, we propose a new masking technique that is efficient in masking the parity-check matrix consisting of an array of arbitrary circulants of the same size. Compared with the several existing works, our proposed algorithms could perform better or comparably in terms of avoiding generating small cycles and error performances. Our proposed algorithms somewhat perfect the works of QC-LDPC code construction. [ABSTRACT FROM PUBLISHER]

In entropy coding, universal coding of integers (UCI) is a binary universal prefix code, such that the ratio of the expected codeword length to $\max \{1, H(P)\}$ is less than or equal to a constant expansion factor $K_{\mathcal {C}}$ for any probability distribution $P$ , where $H(P)$ is the Shannon entropy of $P$. $K_{\mathcal {C}}^{*}$ is the infimum of the set of expansion factors. The optimal UCI is defined as a class of UCI possessing the smallest $K_{\mathcal {C}}^{*}$. Based on prior research, the range of $K_{\mathcal {C}}^{*}$ for the optimal UCI is $2\leq K_{\mathcal {C}}^{*}\leq 2.75$. Currently, the code constructions achieve $K_{\mathcal {C}}=2.75$ for UCI and $K_{\mathcal {C}}=3.5$ for asymptotically optimal UCI. In this paper, we construct a class of UCI, termed $\iota $ code, to achieve $K_{\mathcal {C}}=2.5$. This further narrows the range of $K_{\mathcal {C}}^{*}$ to $2\leq K_{\mathcal {C}}^{*}\leq 2.5$. Next, a family of asymptotically optimal UCIs is presented, where their expansion factor infinitely approaches 2.5. Then, tighter upper bounds of the expansion factors are derived for several classic UCIs. Finally, we prove that the length of the first codeword of optimal UCI is one. [ABSTRACT FROM AUTHOR]

In this paper, a class of $p$ -ary 3-weight linear codes and a class of binary 2-weight linear codes are proposed respectively by virtue of the properties of the perfect nonlinear functions over $\mathbb {F}_{p^{m}}$ and $(m,s)$ -bent functions from $\mathbb {F}_{2^{m}}$ to $\mathbb {F}_{2^{s}}$ , where $p$ is an odd prime and $m, s$ are positive integers. The weight distributions are completely determined by the sign of the Walsh transform of weakly regular bent functions and the size of the preimage of the employed $(m,s)$ -bent functions at the zero point, respectively. As a special case, a class of optimal linear codes meeting Griesmer bound is obtained from our construction. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the fundamentals of puncturing and shortening for polar codes, based on binary domination. For punctured and shortened polar codes, we prove that the partial order by binary domination completely determines both incapable bit patterns (by puncturing) and fixed bit patterns (by shortening). In particular, we give a necessary and sufficient condition for an encoder output bit to be fixed by additionally shortening a single encoder input bit, as well as a necessary and sufficient condition for an encoder input bit to be made incapable by additionally puncturing a single encoder output bit. We also identify all the puncturing bit patterns yielding a given incapable bit pattern. These results provide a guidance to design a practical rate-matching scheme for polar codes. As an example, we present a rate-matching scheme based on our analytical observations. Numerical results show that it performs well over a wide range of code lengths and rates, compared with conventional rate-matching schemes. [ABSTRACT FROM AUTHOR]

A class of network codes have been proposed in the literature where the symbols transmitted on network edges are binary vectors and the coding operation performed in network nodes consists of the application of (possibly several) permutations on each incoming vector and XOR-ing the results to obtain the outgoing vector. These network codes, which we will refer to as permute-and-add network codes, involve simpler operations and are known to provide lower complexity solutions than scalar linear network codes. The complexity of these codes is determined by their degree which is the number of permutations applied on each incoming vector to compute an outgoing vector. Constructions of permute-and-add network codes for multicast networks are known. In this paper, we provide a new framework based on group algebras to design permute-and-add network codes for arbitrary (not necessarily multicast) networks. Our framework allows the use of any finite group of permutations (including circular shifts, proposed in prior works) and admits a trade-off between coding rate and the degree of the code. Further, our technique permits elegant recovery and generalizations of the key results on permute-and-add network codes known in the literature. [ABSTRACT FROM AUTHOR]

This paper develops a non-coherent index modulation (IM) system in which activation patterns are characterized by multi-level block codes. We analyze performance of such a system under the maximum-likelihood (ML) receiver and when the set of activation patterns follows a multi-level code generated from asymptotically optimal alphabets. An asymptotic analysis of the pair-wise error probability (PEP) shows that the system can exploit a diversity order that is determined by the distance of the worst codeword pair in the $l_{1}$ metric, known as the Manhattan norm. We then explore the rate-diversity tradeoff for the developed non-coherent IM system as a function of the code length. Specifically, Gilbert-style bounds on the data rates for systems based on binary and ternary codes are obtained that can ensure a given diversity order. We approach the problem of packing in the $l_{1}$ metric by partitioning codes into permutation modulation codes (PMCs) and obtaining Gilbert-style bounds on PMCs. Several achievable rates for non-coherent binary and ternary IM systems, as well as a tradeoff between the information rate and codeword error probability (CEP) are also derived. Finally, simulation results are provided to corroborate the theoretical analysis. [ABSTRACT FROM AUTHOR]

In any transmission scheme, security against eavesdroppers is of importance. Contrary to classical encryption, security directly at the physical layer can be achieved by applying suited coding and modulation schemes. In this paper, coded modulation schemes, i.e., the use of higher-order constellations, is studied for generating both security against a wiretapper and reliability for the legitimate user. Specifically, a multilevel coding (MLC) scheme is considered. The influence of the constellation, in particular its cardinality and its dimensionality, on the gained security is assessed. As LSB component code, a practical secure coding scheme based on punctured LDPC codes is used. The security level for the employed LDPC code ensembles within MLC constructions is examined with an adapted density evolution technique. Results from numerical simulations cover the theoretical considerations and match with the derived asymptotic behavior. The results are compared to the situation when straightforwardly applying a binary code according to the BICM approach. [ABSTRACT FROM AUTHOR]

Some nonlinear codes, such as Kerdock and Preparata codes, can be represented as binary images under the Gray map of linear codes over rings. This paper introduces MAP decoding of Kerdock and Preparata codes by working with their quaternary representation (linear codes over $\mathbb {Z}_{4}$) with the complexity of $\mathcal {O}(N^{2}\log _{2} N)$ , where N is the code length in $\mathbb {Z}_{4}$. A sub-optimal bitwise APP decoder with good error-correcting performance and complexity of $\mathcal {O}(N\log _{2} N)$ that is constructed using the decoder lifting technique is also introduced. This APP decoder extends upon the original lifting decoder by working with likelihoods instead of hard decisions and is not limited to Kerdock and Preparata code families. Simulations show that our novel decoders significantly outperform several popular decoders in terms of error rate. [ABSTRACT FROM AUTHOR]

Distributed arithmetic coding (DAC) is a variant of AC that can realize Slepian-Wolf coding in a nonlinear way. In our previous work, we defined codebook cardinality spectrum (CCS) and Hamming distance spectrum (HDS) for DAC. In this paper, we make use of CCS and HDS to analyze tailed DAC, which is a form of DAC that, as traditional AC, maps the last few symbols of each source block onto non-overlapped intervals. First, we derive the exact HDS formula for tailless DAC, a form of DAC that maps all the symbols of each source block onto overlapped intervals, and show that the HDS formula previously given is in fact approximation. Then, the HDS formula is extended to tailed DAC. Using CCS, we also deduce the average codebook cardinality, which is closely related to decoding complexity, and rate loss of tailed DAC. The effects of tail length are extensively analyzed. It is revealed that by increasing tail length to a value not close to the bitstream length, closely spaced codewords within the same codebook can be removed at the cost of a higher decoding complexity and a larger rate loss. Finally, theoretical analyses are verified by experiments. [ABSTRACT FROM PUBLISHER]

This paper proposes a novel lower bound on the Bhattacharyya parameter of synthesized channels in polar codes. The proposed bound is a result of a newly defined merge operation that reduces the cardinality of output alphabets of a symmetric binary-input discrete memoryless channel. By repeated applications of the proposed merge operation, we establish a universal bound on the Bhattacharyya parameters of synthesized channels that holds for any symmetric binary-input discrete memoryless transmission channel. We then discuss some applications of the new bound. For example, using the derived universal lower bound along with the existing upper bound, we find a partial order among the Bhattacharyya parameters of those synthesized channels that cannot be ordered through existing results. This ordering can help efficient design of polar codes. In addition, some extremal behaviors of the binary-symmetric channel are also proved. [ABSTRACT FROM AUTHOR]

A decoding algorithm for polar (sub)codes with binary 2t × 2t polarization kernels is presented. It is based on the window processing (WP) method, which exploits the linear relationship of the polarization kernels and the Arikan matrix. This relationship enables one to compute the kernel input symbols probabilities by computing the probabilities of several paths in Arikan successive cancellation (SC) decoder. In this paper we propose an improved version of WP, which has significantly lower arithmetic complexity and operates in log-likelihood ratios (LLRs) domain. The algorithm identifies and reuses common subexpressions arising in computation of Arikan SC path scores. The proposed algorithm is applied to kernels of size 16 and 32 with improved polarization properties. It enables polar (sub)codes with the considered kernels to simultaneously provide better performance and lower decoding complexity compared with polar (sub)codes with Arikan kernel. [ABSTRACT FROM AUTHOR]

The code design problem for multilevel coded modulation with iterative decoding (MLCM-ID) has been left unsolved over a decade. In this paper, we define the code design criterion for MLCM-ID based on a novel concept—parametrically-mapped EXIT (PM-EXIT) function. We derive the EXIT functions for MLCM-ID, and present the mathematical work by which the three area theorems of PM-EXIT function are proved. This gives theoretical support of the curve-fitting techniques used in MLCM-ID, and also provides firm proof that the PM-EXIT function design rule allows in principle capacity-achieving code assignment. The simulation results perfectly match the theoretical analysis, and also confirm that the design rule proposed fully exploits the flexibility of MLCM-ID in the choice of codes. Both in theory and simulations, our code design is verified. [ABSTRACT FROM PUBLISHER]

This paper presents a method to calculate the exact average block error probability of some random code ensembles under maximum-likelihood decoding. The proposed method is applicable to various channels and ensembles. The focus is on both spherical and Gaussian random codes on the additive white Gaussian noise channel as well as binary random codes on both the binary symmetric channel and the binary erasure channel. While for the uniform spherical ensemble Shannon, in 1959, argued with solid angles in N-dimensional space, the presented approach projects the problem into two dimensions and applies standard trigonometry. This simplifies the derivation and also allows for the analysis of the independent identically distributed (i.i.d.) Gaussian ensemble which turns out to perform better for short blocklengths and high rates. Moreover, a new lower bound on the average block error probability of the uniform spherical ensemble is found. For codes with more than three codewords, it is tighter than the sphere packing bound, but requires exactly the same computing effort. Furthermore, tight approximations are proposed to simplify the computation of both the exact average error probability and the two bounds. For the binary symmetric channel and the binary erasure channel, bounds on the average block error probability for i.i.d. random coding are derived and compared to the exact calculations. [ABSTRACT FROM AUTHOR]

Memory maximum-distance-separable (mMDS) sliding window codes are a type of erasure codes with high erasure-correction capability and low decoding delay. In this paper, we study two types of systematic mMDS sliding window codes over erasure channels, i.e., scalar codes defined over a finite field $GF(2^{L})$ , and vector codes defined over a vector space $GF(2)^{L}$. We first devise an efficient heuristic algorithm to produce an mMDS sliding window scalar code over relatively small $GF(2^{L})$. Then, we investigate a special class of mMDS sliding window vector codes whose encoding/decoding are achieved by basic circular-shift and bit-wise XOR operations, and propose a general method to generate such mMDS vector codes. Our complexity analysis shows that the proposed vector codes yield much lower encoding/decoding complexity than the scalar codes. The theoretical and numerical results also demonstrate that mMDS sliding window codes dominate MDS block codes in terms of decoding delay and erasure-correction capability. [ABSTRACT FROM AUTHOR]

In this paper, we characterize the finite-length performance of separable circulant-based spatially-coupled (SCB-SC) LDPC codes for transmission over the additive white Gaussian noise channel. For a general class of finite-length graph-based codes, it is known that the existence of small absorbing sets causes a performance degradation in the error floor regime. We first present the mathematical conditions for the existence of absorbing sets in binary SCB-SC codes. This analysis enables us to find the exact number of absorbing sets as a function of the design parameters. In particular, our results show that the choice of the cutting vector affects the number of absorbing sets and, therefore, the error floor performance of the code. For a fixed column weight, we find provably optimal cutting vectors that result in the least number of absorbing sets. Furthermore, we extend our analysis to nonbinary SCB-SC codes, where we show that the choice of the cutting vector is not as critical as in the binary case. We provide an algorithm which provably removes the problematic nonbinary absorbing sets from nonbinary SCB-SC codes by informed selection of edge labels. Our simulation results show the superior error floor performance of our designed binary and nonbinary SCB-SC codes compared with binary unstructured and nonbinary quasi-cyclic SC codes available in the open literature. [ABSTRACT FROM PUBLISHER]

In this paper, we present a computationally efficient method for estimating error floors of low-density parity-check (LDPC) codes over the binary symmetric channel (BSC) without any prior knowledge of its trapping sets (TSs). Given the Tanner graph $G$ of a code, and the decoding algorithm $\mathcal {D}$ , the method starts from a list of short cycles in $G$ , and expands each cycle by including its sufficiently large neighborhood in $G$. Variable nodes of the expanded sub-graphs $\mathcal {G}_{\text{EXP}}$ are then corrupted exhaustively by all possible error patterns, and decoded by $\mathcal {D}$ operating on $\mathcal {G}_{\text{EXP}}$. Union of support of the error patterns for which $\mathcal {D}$ fails on each $\mathcal {G}_{\text{EXP}}$ defines a subset of variable nodes that is a TS. The knowledge of the minimal error patterns and their strengths in each TSs is used to compute an estimation of the frame error rate. This estimation represents the contribution of error events localized on TSs, and therefore serves as an accurate estimation of the error floor performance of $\mathcal {D}$ at low BSC cross-over probabilities. We also discuss trade-offs between accuracy and computational complexity. Our analysis shows that in some cases the proposed method provides a million-fold improvement in computational complexity over standard Monte-Carlo simulation. [ABSTRACT FROM AUTHOR]

In this paper, we present a deliberate bit flipping (DBF) coding scheme for binary two-dimensional (2-D) channels, where specific patterns in channel inputs are the significant cause of errors. The idea is to eliminate a constrained encoder and, instead, embed a constraint into an error correction codeword that is arranged into a 2-D array by deliberately flipping the bits that violate the constraint. The DBF method relies on the error correction capability of the code being used so that it should be able to correct both deliberate errors and channel errors. Therefore, it is crucial to flip minimum number of bits in order not to overburden the error correction decoder. We devise a constrained combinatorial formulation for minimizing the number of flipped bits for a given set of harmful patterns. The generalized belief propagation algorithm is used to find an approximate solution for the problem. We evaluate the performance gain of our proposed approach on a data-dependent 2-D channel, where 2-D isolated-bits patterns are the harmful patterns for the channel. Furthermore, the performance of the DBF method is compared with classical 2-D constrained coding schemes for the 2-D no isolated-bits constraint on a memoryless binary symmetric channel. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Message-passing decoders typically perform well for nonbinary low-density parity-check (NB-LDPC) codes with large computational complexity. As another type of simplified decoders, symbol-reliability-based decoders further reduce the computational complexity. However, the previously proposed algorithms suffer severe error performance degradation for NB-LDPC codes with low column weights. In this paper, a weighted bit-reliability based (wBRB) decoder for NB-LDPC codes is developed and implemented with efficient layered partial-parallel structure. It not only balances the tradeoff between complexity and error performance, but also reduces the memory usage significantly. Furthermore, to enhance the performance of the wBRB decoder, a full bit-reliability-based (FBRB) decoder is proposed. The FBRB decoder is derived based on the binary matrix representation of the nonzero entries in the parity-check matrix. Since more bit-reliability values are passed through the edges of the Tanner graph, the FBRB decoder can achieve better error performance and faster convergence rate than the wBRB decoder. Both of the decoders are implemented on a Xilinx Virtex-5 XC5VLX155T FPGA device for a (403,226) code over GF($2^5$). The results shows that they achieve 118.98 and 95.73 Mbps throughput with 15 iterations, respectively. [ABSTRACT FROM AUTHOR]

This paper studies an extension and improvement of the joint detection-decoding algorithm for nonbinary LDPC-coded modulation systems. The iterative joint detection-decoding (IJDD) algorithm in [1] combines nonbinary LDPC decoding with signal detection based on the hard-message passing strategy, resulting in significantly reduced decoding complexity. However, it applies only to majority-logic decodable nonbinary LDPC codes with high column weight. For nonbinary LDPC codes with low column weight, a noticeable performance loss will be incurred. To handle this problem, we propose a reliability-based iterative joint detection-decoding (also termed improved IJDD) algorithm, which combines the accumulated reliability of symbols based on the one-step majority-logic decoding (MLGD) algorithm and a Chase-like local list decoding algorithm. Simulation results show that the improved IJDD algorithm outperforms the IJDD algorithm by about 0.3 dB using nonbinary LDPC codes with high column weight, and by about 3 dB using nonbinary LDPC codes with low column weight (dv = 4), while maintaining the low complexity of decoding. Compared to the FFT-QSPA, the proposed algorithm has a performance degradation of 0.5 dB in the high column weight regime, and about 1 dB in the low column weight regime. [ABSTRACT FROM AUTHOR]

In this paper, we propose an efficient coding scheme for the binary Chief Executive Officer (CEO) problem under logarithmic loss criterion. Courtade and Weissman obtained the exact rate-distortion bound for a two-link binary CEO problem under this criterion. We find optimal parameters of the binary symmetric test-channel model for the encoder of each link by using the given bound. Furthermore, an efficient coding scheme based on compound low-density generator matrix (LDGM)–low-density parity-check (LDPC) codes is presented to achieve the theoretical rates. In the proposed encoding scheme, a binary quantizer using LDGM codes and a syndrome generator using LDPC codes are applied. The proposed decoder employs a sum-product algorithm and a soft estimator to produce an approximate a posteriori distribution of the source bits given the data received through both links. Our numerical examples verify a close performance of the proposed coding scheme to the theoretical bound in several cases. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

A new coded modulation scheme is proposed. At the transmitter, the concatenation of a distribution matcher and a systematic binary encoder performs probabilistic signal shaping and channel coding. At the receiver, the output of a bitwise demapper is fed to a binary decoder. No iterative demapping is performed. Rate adaption is achieved by adjusting the input distribution and the transmission power. The scheme is applied to bipolar amplitude-shift keying (ASK) constellations with equidistant signal points and it is directly applicable to two-dimensional quadrature amplitude modulation (QAM). The scheme is implemented by using the DVB-S2 low-density parity-check (LDPC) codes. At a frame error rate of 10^-3, the new scheme operates within less than 1.1 dB of the AWGN capacity \frac12\log_2(1+\mathsfSNR) at any spectral efficiency between 1 and 5 bits/s/Hz by using only 5 modes, i.e., 4-ASK with code rate 2/3, 8-ASK with 3/4, 16-ASK and 32-ASK with 5/6, and 64-ASK with 9/10. [ABSTRACT FROM AUTHOR]

While many communications media, such as wireless and certain classes of wireline channels, typically lead to bursty errors, most decoders are designed assuming memoryless channels. Consequently, communication systems generally rely on interleaving over tens of thousands of bits to match decoder assumptions. Even for short high rate codes, awaiting sufficient data in interleaving and de-interleaving is a significant source of unwanted latency. We construct an extension to the recently proposed Guessing Random Additive Noise Decoding (GRAND) algorithm, which we call GRAND-MO for GRAND Markov Order. By foregoing interleaving and instead making use of the bursty nature of noise, low-latency communication is possible with block error rates outperforming their interleaved counterparts by a substantial margin. We establish that certain well-known binary codes with structured code-word patterns are ill-suited for use in bursty channels, but Random Linear Codes (RLCs) prove robust to correlated noise. We further demonstrate that by operating directly on modulated symbols rather than de-mapped bits, GRAND-MO achieves further performance and complexity gains by exploiting information that is lost in demodulation. As a result, GRAND-MO provides one potential solution for applications that require ultra-reliable low latency communication. [ABSTRACT FROM AUTHOR]

We study the optimal maximum likelihood (ML) block decoding of general binary codes sent over two classes of binary additive noise channels with memory. Specifically, we consider the infinite and finite memory Polya contagion and queue-based channel models, which were recently shown to approximate well binary modulated correlated fading channels used with hard-decision demodulation. We establish conditions on the codes and channels parameters under which ML and minimum Hamming distance decoding are equivalent. We also present results on the optimality of classical perfect and quasi-perfect codes when used over the channels under ML decoding. Finally, we briefly apply these results to the dual problem of syndrome source coding with and without side information. [ABSTRACT FROM AUTHOR]

A Mixed Error Reduction (MER) scheme is presented for soft-decision decoding of binary product block codes. The MER scheme is realized by combining two algorithms having different performance objectives: bit-error-rate (BER) reduction followed by word-error-rate (WER) reduction. BER reduction is achieved by employing soft-in soft-out, possibly iterative, algorithm whose aim here is to improve the residual signal-to-noise ratio with each iteration. For WER reduction a two-step, soft-in hard-out, sub-optimal algorithm for decoding product codes is presented. This decoding algorithm guarantees correct decoding (at least) up to half the minimum Euclidean distance of the product code. The MER scheme exhibits good WER, as well as BER performance, with low computational burden. [ABSTRACT FROM AUTHOR]

Consider the identification (ID) via channels problem, where a receiver decides whether the transmitted identifier is its identifier, rather than decoding it. This model allows to transmit identifiers whose size scales doubly-exponentially in the blocklength, unlike common transmission codes with exponential scaling. Binary constant-weight codes (CWCs) suffice to achieve the ID capacity. Relating parameters of a binary CWC to the minimum distance of a code and using higher-order correlation moments, two upper bounds on binary CWC sizes are proposed. These bounds are also upper bounds on identifier sizes for ID codes constructed by using binary CWCs. We propose two constructions based on optical orthogonal codes (OOCs), which are used in optical multiple access schemes, have constant-weight codewords, and satisfy cyclic cross-correlation and auto-correlation constraints. These constructions are modified and concatenated with outer Reed-Solomon codes to propose new binary CWCs being optimal for ID. Improvements to the finite-parameter performance are shown by using outer codes with larger minimum distance vs. blocklength ratios. We illustrate ID regimes for which our ID code constructions perform significantly better than existing constructions. [ABSTRACT FROM AUTHOR]

We propose a new probabilistic amplitude shaping (PAS) scheme based on short linear block codes. In the proposed system, the capacity-approaching signal distribution is generated in the process of decoding linear block codes for a given information bit sequence. We associate the design problem of shaping codes with the classical covering problem, suggesting the use of good covering codes for shaping. From simulation results, it is demonstrated that by selecting perfect binary codes as our shaping codes, the proposed scheme offers a shaping gain of around 0.3–1.0 dB. By comparing with the enumerative sphere shaping (ESS) of the same block length, we verify that the proposed scheme achieves significantly lower storage complexity and computational complexity at the receiver even with comparable block error rate performance. [ABSTRACT FROM AUTHOR]

A common technique for the partial encryption of compressed images and videos encrypts only the sign bits of some syntax elements such as the quantized transform coefficients or the motion vector differences. The sign bit can be interpreted as the most significant bit (MSB) in the binary representation of the syntax element. Our work is motivated by the key observation that the binary code used for this representation has an impact on the quality of the reconstruction at the eavesdropper and on the size of the stream to be encrypted. Therefore, we address the problem of optimal binary code design for partial encryption. Ideally, the goal is to simultaneously maximize the eavesdropper’s distortion and minimize the length of the compressed MSB stream. Since these two objectives are conflicting in general, we formulate the problem as the maximization of a weighted sum of the eavesdropper’s distortion and of the probability of the MSB being 0. We cast the problem as a binary integer linear program equivalent to a maximum weight matching problem, which has a polynomial-time solution algorithm. We show that when the source to be quantized and the quantizer are symmetric, the problem can be converted to a linear program of a smaller size, for a family of distortion metrics. Extensive experiments assess the performance of the optimized binary code in comparison with existing approaches. The results reveal that certain existing partial encryption schemes could benefit from the proposed design. [ABSTRACT FROM AUTHOR]

We are interested in a communication system that operates under stringent power constraints, but is flexible with bandwidth constraints. Our approach is to consider some of the key elements in a transceiver and optimize them for low power consumption, as opposed to optimizing them to minimize, say, average probability of error. An obvious consequence of this is that high complexity components of the system, such as matched filters, forward error correction that employs iterative decoders, coherent demodulators, and bandwidth-efficient modulation formats, are not feasible for this research. Rather, our system is designed using $M$ -ary FSK with non-coherent detection, optimized two-pole bandpass filters (BPF), and Reed-Solomon (RS) codes with hard-decision decoding. Among other things, we show that by properly optimizing the key parameters of the BPFs and RS codes, we can design the system to be significantly less complex than an optimal one, and only lose about 1.2 ($M$ =16) to 1.5 ($M$ =2) dB in terms of performance. [ABSTRACT FROM AUTHOR]