In Contention Resolution Diversity Slotted ALOHA (CRDSA) and Irregular Repetition Slotted ALOHA (IRSA), iterative decoding is typically assumed to be instantaneous, overlooking the decoding latency encountered in practical systems. This paper proposes a Partially Parallel Decoding ($\textsf {PPD}$) framework that offers a tunable trade-off between latency, complexity, and throughput. The proposed framework supports both CRDSA and IRSA with AWGN and Rayleigh fading by incorporating, in each iteration of the decoding process, a scheduling algorithm that selects target packets based on the number of available decoders, along with a slot selection algorithm that identifies a subset of time slots for the equalization step to manage complexity. Simulation results show that in both AWGN and fading environments, the PPD framework achieves performance close to that of sequential decoding while significantly reducing latency—by up to$64\times $for CRDSA and$16\times $for IRSA—with a practical number of decoders.

Binary linear block codes (BLBCs) are essential to modern communication, but their diverse structures often require tailor-made decoders, increasing complexity. This work introduces enhanced polar decoding ($\textsf {PD}^{+}$), a universal soft decoding algorithm that transforms any BLBC into a polar-like code compatible with efficient polar code decoders such as successive cancellation list (SCL) decoding. Key innovations in$\textsf {PD}^{+}$include pruning polar kernels, shortening codes, and leveraging a simulated annealing algorithm to optimize transformations. These enable$\textsf {PD}^{+}$to achieve competitive or superior performance to state-of-the-art algorithms like OSD and GRAND across various codes, including extended BCH, extended Golay, and binary quadratic residue codes, with significantly lower complexity. Moreover,$\textsf {PD}^{+}$is designed to be forward-compatible with advancements in polar code decoding techniques and AI-driven search methods, making it a robust and versatile solution for universal BLBC decoding in both present and future systems.

In this paper, by considering the effect of error correcting codes in addition to collision resolution, a novel probabilistic density-evolution analysis of the irregular repetition slotted ALOHA (IRSA) is proposed. Simulation results confirm that the proposed extension analysis can accurately recover the efficiency of the iterative successive interference cancellation (iSIC) scheme for a satellite Internet-of-Things (IoT) system endowed with an error correcting code, and therefore can be used to determine the corresponding optimal degree distributions.

To mitigate the performance degradation caused by channel aging in massive multi-input multi-output (MIMO) systems, channel prediction is investigated in this paper. Based on the existing vector Prony method (VPM) and the Prony-based angular-delay domain (PAD) prediction, two novel channel prediction methods, referred to as the modified VPM (MVPM) and the modified PAD (MPAD), are proposed. In the proposed methods, we decouple the model size from the number of past channel estimates that are involved in the prediction of the future channels, allowing more flexible usage of channel estimates. Simulations demonstrate that when the number of past channel estimates becomes large, the proposed MVPM and MPAD significantly outperform VPM and PAD, respectively. Complexity analysis shows that this improvement in performance comes with a slight increase in computational complexity.

Uncoordinated multiple access has been proposed as a modern technique to provide massive connectivity. Among many proposals, irregular repetition slotted ALOHA (IRSA) was shown to achieve a close-to-optimum throughput by irregular packet repetition and successive interference cancellation (SIC). However, most of the previous works are based on certain ideal assumptions. In this paper, we tackle one of such ideal assumptions, where a decoded packet can always be used to cancel outallits replicas transmitted in other slots. In reality, the random nature of IRSA results in a large dynamic range of the received power that cannot be recovered under a practical quantizer. A SIC limit that dictates the number of recoverable collided packets at a slot should exist. To resolve this issue, we propose a novel protocol, named IRSA with frame partitioning (IRSA-FP), which partitions a frame into several subframes. A feedback mechanism is enforced to inform those users, whose packets have been successfully decoded, to cease their transmissions. We then propose a novel density-evolution-type analysis for IRSA-FP. Simulation results show the performance of the proposed IRSA-FP can be accurately predicted by our analysis and the proposed IRSA-FP outperforms the traditional IRSA when practical SIC limit is introduced.

In this paper, the problem of using uncoordinated multiple access (UMA) to serve a massive amount of heterogeneous users is investigated. Leveraging the heterogeneity, we propose a novel UMA protocol, called iterative collision resolution for slotted ALOHA (IRSA) with non-orthogonal multiple access (NOMA), to improve the conventional IRSA. In addition to the inter-slot successive interference cancellation (SIC) technique used in existing IRSA-based schemes, the proposed protocol further employs the intra-slot SIC technique that enables collision resolution for certain configurations of collided packets. A novel multi-dimensional density evolution is then proposed to analyze and to optimize the proposed protocol. Simulation results show that the proposed IRSA with NOMA protocol can efficiently exploit the heterogeneity among users and the multi-dimensional density evolution can accurately predict the throughput performance. Last, an extension of the proposed IRSA with NOMA protocol to the frame-asynchronous setting is investigated, where a boundary effect similar to that in spatially-coupled low-density parity check codes can be observed to bootstrap the decoding process.

We consider a distributed computing network consisting of a master and multiple workers processing tasks of different types. The master is running multiple applications. Each application stochastically generates real-time jobs with a strict job deadline, where each job is a collection of tasks of some types specified by the application. A real-time job is completed only when all its tasks are completed by the corresponding workers within the deadline. Moreover, we consider unreliable workers, whose processing speeds are uncertain. Because of the limited processing abilities of the workers, an algorithm for scheduling the jobs in the workers is needed to maximize the average number of completed jobs for each application. The scheduling problem is not only critical but also practical in distributed computing networks. In this paper, we develop two scheduling algorithms, namely, a feasibility-optimal scheduling algorithm and an approximate scheduling algorithm. The feasibility-optimal scheduling algorithm can fulfill the largest region of applications' requirements for the average number of completed jobs. However, the feasibility-optimal scheduling algorithm suffers from high computational complexity when the number of applications is large. To address the issue, the approximate scheduling algorithm is proposed with a guaranteed approximation ratio in the worst-case scenario. The approximate scheduling algorithm is also validated in the average-case scenario via computer simulations.

Motivated by the future scenarios of ultra-reliability and low latency communications (URLLC) and integrated access and backhaul (IAB) that are currently discussed in 3GPP, we propose a novel parallelogram-structured constellation design based on minimum distance (MD) criterion for powerdomain uplink NOMA system. In comparison with previous work, which maximizes MD of the superimposition of the usual constellations, such as QPSK and 16 QAM, by inter-constellation rotation, the incorporation of parallelogram-structure into the NOMA constellation design can achieve a much better MD. Since the proposed constellations can be parameterized as a function of the power ratio î±, the signaling overhead for a base station to designate the constellations to be used by each user equipment is minimized. Simulation results show that our proposed constellation design can further improve the symbol error rate, as well as the achievable rate, of the inter-constellation-rotated superposition of usual square constellations.

Delay performance of downlink non-orthogonal multiple access (NOMA) networks is investigated. To fully realize advantages offered by NOMA, we need to consider more realistic network environment; as such, departing from the literature on NOMA, this paper relaxes the full-buffer assumption and allows each user in the network to have its individual delay-cost function. The former captures the sporadic nature of data arrivals in some applications, while the latter accepts potential coexistence of heterogeneous users. In this context, we propose three transmission scheduling algorithms, namely the MDP-based, the c- μ-based, and the learning-based scheduling algorithms. While the MDP-based scheduling algorithm is shown to be delay-optimal, the other two scheduling algorithms enjoy the online feature where transmitters are oblivious to arrival statistics. Moreover, it turns out that the c-μ-based scheduling algorithm is a greedy version of the MDP-based scheduling algorithm and the learning-based scheduling algorithm is asymptotically delay-optimal. Simulation results corroborate our theoretical analysis and fortify the common belief about the superiority of NOMA over OMA, even without the full-buffer assumption and with heterogeneous users.

In this paper, a novel lattice-partition-based downlink non-orthogonal multiple access framework is proposed. This framework is motivated by recognizing the algebraic structure behind the previous scheme recently proposed by Shieh and Huang as a lattice partition in Z and is in fact a generalization of the scheme to any base lattice. The schemes in the proposed framework enjoy many desirable properties such as explicit and systematic design and discrete input distributions. Moreover, the proposed method only requires a limited knowledge of channel parameters. The rates achieved by the proposed scheme with any base lattice and with single-user decoding (i.e., without successive interference cancellation) are analyzed, and a universal upper bound on the gap to the multiuser capacity is obtained as a function of the normalized second moment of the base lattice. Since the proposed framework has a substantially larger design space than that of the previous scheme of Shieh and Huang whose base lattice is a 1-D lattice, one can easily find instances in larger dimensions that can provide superior performance. Design examples with the base lattices A2, D4, E8, and Construction A lattices, respectively, are provided, and both theoretical and simulation results exhibit smaller gaps to the multiuser capacity as dimensions increase.

In this paper, downlink non-orthogonal multiple access (NOMA) with receivers performing single- user decoding i.e., without successive interference cancellation (SIC) is studied. Using lattice partitions, we generalize the scheme recently proposed by Shieh and Huang [1] to general n-dimensional constellations carved from lattices. The achievable rates of the proposed scheme without SIC and the gap to the capacity region are investigated. Design examples based on lattice partition chains in Z2, A2, and D4 are studied. Numerical and simulation results are provided, which demonstrate advantages of the proposed scheme over the one in [1] and any orthogonal multiple access scheme.

In this paper, we propose a new downlink non-orthogonal multiuser superposition transmission scheme for future 5G cellular networks, which we refer to as the lattice partition multiple access (LPMA). In this proposed design, the base station transmits multilevel lattice codes for multiple users. Each user's code level corresponds to a distinct prime and is weighted by a product of all distinct primes of the other users excluding its own. Due to the structural property of lattice codes, each user can cancel out the interference from the other code levels by using the modulo lattice operation in a successive/parallel manner. LPMA can provide better user fairness in symmctrical broadcast channels, compared with non- orthogonal multiple access (NOMA). We demonstrate that the proposed LPMA shows a clear throughput enhancement over the current NOMA scheme.

In this paper, the downlink nonorthogonal multiple access (NOMA) system is studied where purely discrete input distributions are found that achieve the capacity region to within a constant gap without successive interference cancellation (SIC). The approach is a two-step approach where the corresponding linear deterministic model is first studied and the results are then systematically translated into purely discrete input distributions for the original model. A simple yet powerful coding scheme, which adopts off-the-shelf turbo codes with pulse amplitude modulations (PAM) is then used to simulate the proposed input distributions. Simulation results show that the proposed simple scheme under turbo decoding, both with and without SIC, can operate close to information-theoretic bounds of the proposed input distributions, which lies outside the achievable rate region of any orthogonal multiple access (OMA)-type scheme.

Broadcast system that provides low data rate broadcast services, especially those served by machine type communication (MTC), has drawn much attention recently. The main concern for the expansion of those broadcast services is the receiver cost and the service coverage. Allowing the transmission of additional coded packets with binary coding has already been a proven technique to extend the service coverage by recovering the lost native packets from the coded packets. In order to lower the receiver cost, we proposed in our previous work a low cost receiver for wireless broadcast systems by reducing the required buffer for packet recovering. Additionally, one equal weight binary codebook design commodious for the low cost receiver was also proposed. In this work, we revisit the binary codebook design problem for low cost receiver by introducing some increasing weight codebooks suitable for the low cost receiver. Simulation results show that the newly designed codebooks can sustain a good portion of coding gain for broadcast system with the low cost receiver.

This paper proposes a novel physical-layer security scheme for anti-eavesdropping, which is based on friendly jamming with dynamic role assignment (DRA). In particular, the roles of message sender and cooperative jammer could be adaptively re-assigned among multiple coordinating transmitter nodes to enhance secrecy rate. We discuss two different prospect approaches to determine the role assignment patterns, including exhaustive search and a reduced-complexity method invoking Hungarian algorithm. Furthermore, by treating all coordinating transmission nodes as a single virtual entity, the paper also examines DRA-based cooperative jamming for reconfigurable antenna groups, which provides a much higher adaptation flexibility and hence superior security performance.

Network coding is a promising technique for broadcast services by recovering the lost packets from additional coded packets. The current network coding receiver requires additional buffer to store coded packets. However, in some real world communication systems, the receiver cost is the major concern. This paper, first proposes a low cost network coding receiver, which reduces the receiver cost by removing the buffer for coded packets. Codebooks suitable for this low cost receiver are also designed. The simulation results show our low cost scheme preserves a large portion of the network coding gain so it remains a competitive scheme for communication systems aiming to provide broadcast service to low cost receivers.

In this work, we focus on a specific practical constraint on sequential-type decoding algorithms, that is, finite stack size. Under such a practical constraint, the path deletion policy that is required when the stack exceeds its upper limit becomes essential in performance and decoding complexity. We then examined several path deletion schemes for sequential-type decoding algorithms that can produce decoding outputs in an on-the-fly fashion. Our result indicates that path deletion based on Fano metric in most cases can achieve better performance when the memory saving is critical in system design. In case the decoding process is allowed to start after the reception of the entire received word, we proposed an alternative path deletion scheme based on a two-pass decoding structure, in which the backward pass estimates the heuristic function in terms of the M-algorithm for use of the forward decoding search. As the M-algorithm can be hardware-implemented, only the computational complexity of the forward pass is accounted. Simulation results show that the computational complexity of the forward pass not only outperforms the stack algorithm with Fano metric but is smaller than that of the two-pass super-code decoder proposed in [9].

In this work, we proposed a reliability-based enhancement for the decoding of convolutional tail-biting codes (CTBC) from the observations that the decoding does not have to start from the beginning of the received vector, and that the reliability of the received vector can be used to determine a good starting position of the decoding process. Simulations show that our reliability-based enhancement can be used together with existing decoding algorithms of the CTBC to improve either their error rate or complexity.

In order to release the growing demand for computational complexity with respect to increasing information sequence length in the priority-first search decoding algorithm, a path elimination modification is proposed and also analyzed in this work. Specifically, we propose to directly eliminate all paths whose end nodes are Δ-level prior to the farthest node among those that have been visited thus far by the priority-first search. Following the argument on random coding, we then analyze the path elimination window Δ that results in a larger exponent for additional decoding error caused by path elimination than the exponent of the maximum-likelihood error performance, and hence guarantees exponentially negligible performance degradation. Our analytical results indicate that under additive white Gaussian noise (AWGN) channels, the path elimination window required for exponentially negligible performance degradation is just three times the code constraint length for rate one-half convolutional codes. It can be further reduced to 1.7-fold of the code constraint length when rate one-third convolutional codes are considered instead. Simulation results confirm these analytical window sizes. As a consequence, the priority-first search decoding algorithm can considerably reduce its computation burden and memory consumption by directly eliminating a large number of paths with nearly no performance degradation. This makes the priority-first search decoding algorithm with path elimination suitable for applications that demand low-complexity software implementation with near optimal performance.

In this work, we revisited the priority-first sequential-search decoding algorithm proposed in Han et al. (2002). By adopting a new metric other than the conventional Fano one, the sequential-search decoding in Han et al. guarantees the maximum- likelihood (ML) performance, and hence, was named the maximum-likelihood sequential decoding algorithm (MLSDA). In comparison with the other maximum-likelihood decoders, it was shown in Han et al. that the software computational complexity of the MLSDA is in general markedly smaller than that of the Viterbi algorithm. A common problem on sequential-type decoding is that at the signal-to-noise ratio (SNR) below the one corresponding to the cutoff rate, the average decoding complexity per information bit and the required stack size grow rapidly with the information length. This problem somehow prohibits the practical use of sequential-type decoding on convolutional codes with long information sequence at low SNRs. In order to alleviate the problem in the MLSDA, we propose in this work to directly eliminate the top path whose end node is Delta-trellis-level prior to the farthest one among all nodes that have been expanded thus far by the sequential search, which we termed the early elimination. Simulations show that a level threshold Delta around three times of the code constraint length is sufficient to secure a near-ML performance. As a consequence of the small early-elimination threshold required, the proposed early-elimination modification not only can considerably reduce the needed stack size but also makes the average decoding computations per information bit irrelevant to the information length.

Cyclic redundancy check (CRC) bits that are conventionally used for error detection have recently found a new application in universal mobile telecommunications system standard for message length detection of variable-length message communications. It was anticipated that the CRC bits, when they are coworked with the inner convolutional code, can be used to detect the receiver-unaware of the message length-without much degradation in their error detection capability. This is unfortunately not true when the offset or difference between the wrong detected length and the true length is small. Two improvements, i.e., the DoCoMo's reverse CRC method and the flip CRC method, were accordingly proposed. In this paper, we revisited the flip CRC modification by considering the impact of joint decoding of the CRC code and the convolutional code. By generalizing the condition for the selection of the flip polynomials, we found that under error-free transmission, the range of the length offsets, at which the false length probability conditioning on the true message length can be made exactly zero (and hence, is minimized), can be extended from to , where and are, respectively, the number of the CRC bits and the memory order of the convolutional code. In addition, an upper bound and a lower bound for the overall false length probability with respect to a uniform pick of the true message length over a candidate message length set are derived. It is then confirmed numerically that the two bounds almost coincide for moderate value. Simulations show that the false length probability obtained analytically under error-free transmission assumption only mildly degrades for moderate-to-high SNRs. Interestingly, we also found that the system block error rate of the flip CRC method can be well approximated by the performance curve of the adopted convolutional code up to a certain SNR, and approach an error floor determined well by the previously derived false length probability bounds beyond this SNR, thereby facilitating the selection of the system parameters, such as the number of CRC bits and the memory order of the convolutional code.

In this work, we analyze the performance of a wireless sensor network with distributed classification codes, where independence across sensors, including local observations, local classifications and sensor-fusion link noises, is assumed. In terms of large deviations technique, we establish the necessary and sufficient condition under which the minimum Hamming distance fusion error vanishes as the number of sensors tends to infinity. With the necessary and sufficient condition and the upper performance bounds, the relation between the fault-tolerance capability of a distributed classification code and its pair-wise Hamming distances is characterized

Reed-Solomon (RS) codes are practically the most frequently used error correction codes with applications ranging from the compact disc, communications, to the exploration of the solar system. In communication systems, RS codes are often punctured and/or shortened to provide different levels of error-correction capability for different services. Previously, standard RS decoding algorithms are also used to decode the shortened/punctured codes, and that results in a undue decoding latency. In this paper, a low-latency decoder is proposed for the punctured/shortened RS codes. The decoding latency matches up to that with the shortened code length rather than the original code length. Therefore, the saving in decoding latency can be significant, if the code length of the shortened/punctured codes is much smaller than the original one. As an example, the proposed decoder is designed for the IEEE 802.16a WiMAX system, where six shortened/punctured RS codes are specified. Numerical results of decoding latency are also provided in this work.

Cyclic redundancy check (CRC) bits that are conventionally used for error detection have recently found a new application in UMTS WCDMA standard (specifically, "blind transport format detection") for message length detection of variable-length message communications. Co-worked with the inner convolutional code, it was demonstrated that the CRC bits can simultaneously detect the receiver-unaware length of a message block without much degradation in its error detection capability. In this work, we introduce two novel decoding strategies for joint decoding of the convolutional and the CRC code. Two previous strategies are also quoted for comparison. Simulation results on their error performance and computational complexity are given.