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In this paper, we derive an upper bound on load-threshold of coded slotted ALOHA (CSA) for slot erasure channel (SEC) and that for packet erasure channel (PEC), respectively. In SEC, by exploiting the analogy between Gaussian elimination of solving linear equations and the iterative successive interference-cancellation (SIC) decoding procedure of CSA, we derive the upper performance bound for SEC. Subsequently, in PEC, utilizing density evolution to track the average probability of packet-decoded failure within the SIC decoding process, we obtain the upper bound for PEC. Moreover, we propose a numerical search algorithm of these bounds under a given calculating precision. The numerical results indicate that the asymptotic upper limit on load-threshold of CSA over SEC is always less than that over PEC with any given erasure probability and average transmission rate. [ABSTRACT FROM AUTHOR]

A novel permuted fast successive-cancellation list decoding algorithm with fast Hadamard transform (FHT-FSCL) is presented. The proposed decoder initializes $L$ $(L\geq 1)$ active decoding paths with $L$ random codeword permutations sampled from the full symmetry group of the codes. The path extension in the permutation domain is carried out until the first constituent RM code of order 1 is visited. Conventional path extension of the successive-cancellation list decoder is then utilized in the information bit domain. The simulation results show that for a RM code of length 512 with 46 information bits, by running 20 parallel permuted FHT-FSCL decoders with $L=4$ , we reduce 72% of the computational complexity, 22% of the decoding latency, and 84% of the memory consumption of the state-of-the-art simplified successive-cancellation decoder that uses 512 permutations sampled from the full symmetry group of the code, with similar error-correction performance at the target frame error rate of $10^{-4}$. [ABSTRACT FROM AUTHOR]

Soft-Input Soft-Output (SISO) polar decoding algorithms, such as Belief Propagation (BP) and Soft Cancellation (SCAN) polar decoding, offer iteration capability for facilitating turbo-style detection. However, at lower Signal-to-Noise Ratios (SNRs), the performance of the BP and SCAN decoders is about 1.5 dB and 0.5 dB worse than that of the state-of-the-art hard-decision Successive Cancellation List (SCL) decoding algorithm, respectively, despite iteratively exchanging information with a Multiple Input Multiple Output (MIMO) detector. Motivated by this gap, we conceive a novel G-SCAN polar decoder, which generates both soft-decision and hard-decision outputs. This is achieved by intrinsically amalgamating a list decoder with a novel SISO decoder. These soft-decision outputs may be used for turbo-detection, but they also support the hard-decision outputs of the SCL algorithm for achieving superior block error rate (BLER) performance. As a result of these benefits, the proposed G-SCAN algorithm using a list size of $L = 2$ offers around 1 dB BLER gain compared to the conventional hard-decision SCL decoder relying on $L = 32$. Furthermore, we have carried out its Extrinsic Information Transfer (EXIT) chart analysis, and characterized the performance vs. the complexity of the proposed G-SCAN algorithm, and compared it to various soft- and hard-decision output benchmarks for a wide variety of different rate-matching modes and block lengths. Furthermore, in order to reduce the complexity of the proposed algorithm, a novel Cyclic Redundancy Check (CRC)-aided G-SCAN algorithm is also proposed, which facilitates early termination and improves the BLER performance. [ABSTRACT FROM AUTHOR]

Considering orthogonal frequency division multiplexing (OFDM) system, we propose a joint channel estimation, noise precision estimation, symbol detection and bit decoding algorithm. In this algorithm, we incorporate the recently proposed vector approximate message passing (VAMP) with the belief propagation and mean field (BP-MF) framework, where BP is applied within subgraph of demodulation and decoding, and MF is used to handle nonlinear observations for estimating unknown noise precision, and VAMP is employed to estimate channels in densely connected factor graph. Furthermore, we use expectation propagation (EP) to demonstrate that the proposed approach converges after only one iteration. Compared to the state-of-the-art algorithm which exploits generalized approximate message passing (GAMP), the proposed scheme achieves the same bit error ratio (BER) performance, but lower per-iteration complexity and faster convergence speed. [ABSTRACT FROM AUTHOR]

In this paper, we propose clustering-based blind detection methods with the aid of systematic convolutional low density generator matrix (SC-LDGM) codes. Inspired by the fact that the received signals naturally fall into clusters in the block-fading channels, we develop a system constrained Gaussian mixture model (SCGMM) by taking into account the inherent characteristics of communication systems, in which the parameters can be estimated by the expectation-maximization (EM) algorithm. We also present an initialization method for the proposed SCGMM to accelerate convergence. After clustering, a decoding algorithm of SC-LDGM codes is designed to resolve the centroid ambiguity. To further improve the detection performance in the low signal-to-noise (SNR) and deep fading scenarios, we propose an improved label-assisted (ILA) method, which integrates the label-assisted (LA) information into the blind detection algorithm. Numerical results show that the performance of our methods can closely approach the performance with perfect channel state information (CSI). The simulation results also show that the performance can be improved by increasing the encoding memory. [ABSTRACT FROM AUTHOR]

When polar codes are decoded by the successive cancellation (SC) decoding algorithm, erroneously decoded non-frozen bits are caused by either channel noise or error propagation. SC-Flip algorithms aim to improve error performance by first identifying erroneous hard decisions due to channel noise and then flipping them during the decoding process to reduce error propagation. In existing SC-Flip algorithms, cyclic redundancy check (CRC) is used to check the decoded codeword to detect incorrect hard decisions. Differing from this detection approach based on CRC, we propose new SC-Flip decoders that take advantage of both the CRC and distributed parity checks (PCs) to detect, identify and flip erroneously decoded non-frozen bits. The proposed decoders terminate SC decoding early when a distributed PC is not satisfied. In addition, we propose a new metric to help locate the incorrect hard decisions. Finally, simulation results demonstrate that our SC-Flip decoders achieve better performance complexity tradeoffs than prior flipping algorithms, and approach the performance and complexity of the SC-Oracle algorithms. [ABSTRACT FROM AUTHOR]

This paper investigates unmanned aerial vehicle (UAV) data collection systems with different multiple access schemes, where a rotary-wing UAV is dispatched to collect data from multiple ground nodes (GNs). Our goal is to maximize the minimum UAV data collection throughput from GNs for both orthogonal multiple access (OMA) and non-orthogonal multiple access (NOMA) transmission, subject to the energy budgets at both the UAV and GNs, namely double energy limitations. 1) For OMA, we propose an efficient algorithm by invoking alternating optimization (AO) method, where each subproblem is alternately solved by applying successive convex approximation (SCA) technique. 2) For NOMA, we first handle subproblems with fixed decoding order using SCA technique. Then, we develop a penalty-based algorithm to solve the decoding order design subproblem. Numerical results show that: i) The proposed algorithms are capable of improving the max-min throughput performance compared with other benchmark schemes; and ii) NOMA yields a higher performance gain than OMA when GNs have sufficient energy. [ABSTRACT FROM AUTHOR]

With low-density parity-check (LDPC) codes and polar codes selected as the standard codes for the fifth generation (5 G) enhanced Mobile Broad Band scenario (eMBB), a decoding architecture that can simultaneously support the decoding of control and data plane becomes necessary at the terminal side to meet the raising requirement for 5 G network deployment. Due to the special structure of LDPC codes according to the Release 15 (R15) 5 G standard, a straight-forward extension of the existing reconfigurable scheme is in general difficult. Therefore in this paper, a unified decoding architecture is proposed that can be reconfigured to either LDPC codes or polar codes. Due to various differences between the two codes such as parity-check matrices, codeword lengths and iterative methods, a joint decoding algorithm is introduced by reordering basic decoding operations to the unified add-comparison-add pattern for both codes. Then, a pipelined structure of reconfigurable decoding unit (RDU) is presented correspondingly which is fully compatible with all decoding patterns of the R15 standard. And finally, a reconfigurable decoder is proposed with multiple levels of parallelism, and the reconfiguration scheme is introduced to improve the hardware utilization and decoding efficiency. The proposed decoder is implemented in FPGA and ASIC, respectively, and has achieved state-of-the-art performance in throughput and area efficiency compared to LDPC-only and polar-only decoders. [ABSTRACT FROM AUTHOR]

An efficient Fast logarithmic successive cancellation stack (Log-SCS) polar decoding algorithm is proposed along with its software implementation using single instruction multiple data (SIMD) style processing. Quantitatively, we reduce the decoding complexity by 50% on average, while simultaneously attaining a decoding latency that is only 21% of that of the state-of-the-art Fast successive cancellation list (SCL) polar decoder's software implementation. This is achieved without any loss of error correction performance by applying simplified path-metric (PM) computations for the rate-0, rate-1 and repetition sub-graphs of the proposed Fast Log-SCS decoder. Furthermore, a software implementation of the 32-bit fixed-point Fast Log-SCS polar decoder is conceived for x86 processors, which maintains the same block error ratio (BLER) as the floating-point Log-SCS polar decoder. Additionally, our software implementation is accelerated using SIMD instructions by relying on 512-bit Advanced Vector Extensions (AVX-512) and recursive template meta-programming for the first time, achieving a parallelism of 16, which makes it eminently suitable for the low-latency requirements of software-defined radio systems. [ABSTRACT FROM AUTHOR]

In this paper, we address the problem of detector design in the frequency-selective fading channels for unique-word-based single-carrier spatial modulation (UWSC-SM) systems. We propose to precede the conventional M-algorithm with an appropriately designed frequency-domain prefilter to condition the equivalent channel so that the number of the survivor paths needed for a satisfactory performance can be significantly reduced. By exploiting the block circulant channel induced by the UWSC-SM block format, the prefilter can be computed, and carried out efficiently using the fast Fourier transforms. Simulation results demonstrate that, compared to the conventional M-algorithm, the proposed algorithm achieves essentially the same error-rate performance with a considerably lower overall complexity in systems where the number of receive antennas is no smaller than that of transmit antennas. [ABSTRACT FROM AUTHOR]

Polar codes are known as the first capacity-achievable codes with low encoding and decoding complexity. The sequential decoding nature of traditional polar decoding algorithms such as successive cancellation (SC) results in high decoding latency, which is not suitable for services that require high reliability and low latency. Deep learning for decoding, referred to as neural network decoder (NND), has shown strong competitiveness because of its non-iterative and full-parallel feature. Whereas, the bit-error-rate (BER) performance of NND is still not satisfactory. In this paper, we first propose a residual learning denoiser (RLD) for polar codes. The RLD can remarkably improve the signal-to-noise ratio (SNR) and reduce the symbol-error-rate (SER) of received symbols. In order to decode polar codes more efficiently, we subsequently propose a residual neural network decoder (RNND) for polar codes. Different from the traditional pure-NND (PNND) which directly uses neural network for decoding received symbols, the proposed RNND concatenates a RLD used for denoising and a NND used for decoding. We provide a novel multi-task learning (MTL) strategy to jointly optimize the denoiser and decoder, and find that the denoising gain of Joint-RLD is more significant than the Independent-RLD. Numerical results show that the proposed RNND outperforms its counterpart PNND with regard to the BER performance. In addition, the optimal RNND(MLP-MLP) approaches the traditional SC decoding performance, while saving more than one hundred times of computation time. Eventually, scalability of the RNND to longer polar codes as well as LDPC codes further demonstrates the superiority of our proposed scheme. [ABSTRACT FROM AUTHOR]

An efficient pilot assignment scheme based on graph coloring is proposed to mitigate the severe pilot contamination effect in cell-free massive multiple-input multiple-output systems. By exploiting the large-scale fading coefficients between the access points (APs) and the user equipments, we first utilize an AP selection algorithm to construct an interference graph. Then, the optimal pilot assignment can be achieved by updating the interference graph. In addition, we consider a fair policy for pilot reuse to improve the system performance. Numerical results verify that, compared with conventional pilot assignment schemes, the proposed graph coloring based pilot assignment scheme can significantly increase the 95 $\%$ -likely per-user throughput and reduce the complexity of assigning pilot sequences. [ABSTRACT FROM AUTHOR]

Ultra-reliable and low-latency communications (URLLC) partakes a major role in 5 G networks for mission-critical applications. Sparse vector coding (SVC) appears as a strong candidate for future URLLC networks by enabling superior performance in terms of bit error rate (BER). SVC exploits the virtual digital domain (VDD) and compressed sensing (CS) algorithms to encode and decode its information through active symbol indices. In this paper, first, a clever encoding/decoding algorithm is proposed for the SVC scheme, which allows the use of all possible activation patterns (APs) resulting in increasing spectral efficiency. Second, a novel solution is proposed to convey additional information bits by further exploiting index modulation (IM) for the codebooks of the SVC scheme. Computer simulation results reveal that our low-complexity algorithm and novel IM solution provide not only a superior BER performance but also an increase in the number of bits conveyed by IM compared to the ordinary SVC approach. [ABSTRACT FROM AUTHOR]

As the first provably capacity-achieving codes, polar codes have been selected as the coding scheme for 5G enhanced mobile broadband (eMBB) control channels. Furthermore, if the bottleneck in decoding complexity is addressed, polar codes are still promising for long code length scenarios in the future with superior error-correcting performance. Considering the demand of cloud radio access network (C-RAN) in 5G system, the low-latency software polar decoder is studied in this paper. Two novel algorithms are proposed to reduce the latency of the successive cancellation list (SCL) decoding, including the segmented list-pruning (SLP) algorithm and the modified distributed sorting (MDS) algorithm. Moreover, the proposed SLP algorithm improves the decoding performance compared to existing segmentation schemes. In terms of the software implementation, our decoder is nearly $20\%$ faster than the state-of-the-art flexible software polar list decoder. [ABSTRACT FROM AUTHOR]

Proved to achieve the symmetric capacity of the binary-input discrete memoryless channels, polar codes have been chosen for the eMBB control channels in the 5th generation mobile communication systems. Besides the main decoding algorithms like successive cancellation (SC) decoding and CRC-aid SC list (CA-SCL) decoding, sphere decoder (SD) and list SD (LSD) are the alternatives for short codes with less required memory bits. Existing SD and LSD attain high calculation complexity, for SD requires a back-tracking process and LSD needs a large list size $L$ to achieve satisfying performance. To reduce complexity, an efficient software stack sphere decoder (ESSD) based on the synchronous determination is firstly proposed in this article. With the dynamic set-by-set decoding in the stack structure, it achieves the lowest complexity in SD-based decoders (SD/LSD/ESSD) while sharing the same performance on low-rate codes and high-rate codes. Compared with the CA-SCL decoder, the complexity and latency of the proposed ESSD are also competitive at high signal-to-noise-ratio on the displayed codes. Implemented on C++, the proposed ESSD reduces $\text{44.77}\%$ latency compared with CA-SCL-32 for $\mathcal {P}(128,120)$ at the BER of $10^{-5}$ with $E_b/N_0 = \text{7}$  dB. [ABSTRACT FROM AUTHOR]

In this paper, blind signal classification and detection in a non-orthogonal multiple access (NOMA) system are explored. Since a NOMA scheme superposes the multiple-user signals within nonorthogonal resources, classical modulation classification methods used in orthogonal multiple access (OMA) systems are not sufficient to process the superposed NOMA signal. NOMA receivers require information about the multiple access schemes such as modulation order and need interference cancellation of the co-scheduled user's signal; therefore, a NOMA system causes more high-layer signaling overheads than OMA during packet scheduling. Blind detection algorithms used for multiplexing information are considered to be possible solutions; however, they pose various challenges and could cause performance loss while performing blind modulation classification in the order of OMA/NOMA classification, co-scheduled user's modulation classification, and classification of the signal, due to the necessity for successive interference cancellation. To improve the performance of blind detection, we propose a NOMA transmission scheme that applies phase rotation to data or pilot symbols depending on the NOMA multiplexing format, as an aid to the blind detection. The proposed classification algorithm can implicitly provide essential information on NOMA multiplexing without the need for any extra high layer signaling or resources. The performance improvement is verified through simulation studies, and it is found that the proposed algorithm provides a gain of more than 1 dB compared to the existing blind signal classification methods and shows almost equivalent performance as the genie information scheme. [ABSTRACT FROM AUTHOR]

Of the wide palette of 5G features, ultra-wide bandwidth and large-scale antenna configuration are regarded as the essential enabling technology components for millimeter wave (mmWave) communication. Accurate knowledge of delay and angle information of multipath components is essential for many applications in mmWave systems. There is a strong need for a low computation-cost channel estimation algorithm for such systems, where typically adopted far-field and narrowband assumptions might be violated. In this paper, a generic yet novel beamspace uniform circular array (UCA) beamforming algorithm with successive cancellation scheme is proposed to jointly detect the impinging azimuth angle and delay of each multipath component. The proposed algorithm is computationally cheap and it works for ultra-wideband UCA systems in the near-field conditions as well as the traditional narrowband systems in the far-field conditions. Both numerical simulations and experimental validation results are provided to demonstrate the effectiveness and robustness of the proposed algorithm, compared to the state-of-art works. [ABSTRACT FROM AUTHOR]

Compared with the non-prediction algorithm, the prediction-based symbol flipping decoding algorithm of non-binary, low-density, parity-check codes over GF($q$) can significantly improve the error performance. To escape from undesirable local maximum, this paper proposes a self-adjustment strategy to redesign the flipping metric. Combined with the prediction mechanism, our proposed algorithm provides a good tradeoff between the complexity and the error correction performance. Simulation results for the additive white Gaussian noise channel and the binary symmetric channel verify the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

In this correspondence paper, a novel machine learning (clustering) based blind decoding method is proposed for the space–time line code (STLC) systems without the information of modulation size and channels. The number of clusters, which is equivalent to the modulation size, is estimated from the received signals by using a $k$ -mean cluster validation metrics, such as silhouette score and Davies–Bouldin index, and the cluster indices are directly mapped to the transmitted binary information bits. To improve the clustering performance, received signal normalization and the initial centroids of the clusters are designed by exploiting the combined STLC signal structure. From the numerical results, it is verified that the proposed blind decoding method can achieve near-coherent decoding performance with either small-size modulation, low noise at the receiver, or a large number of transmit antennas. [ABSTRACT FROM AUTHOR]

In this paper, we propose an enhanced low-complexity binary physical-layer network coding (PNC) based decoding scheme for random access systems with binary phase-shift keying modulation to improve the system throughput. In the proposed scheme, the linear combinations of collided users’ messages in each time slot are first obtained by exploiting a low-complexity PNC decoding scheme. Based on the decoded linear combinations within a MAC frame, we then propose an enhanced message-level successive interference cancellation algorithm to recover more users’ messages. We propose an analytical framework for the PNC-based decoding scheme and derive a tight approximation of the system throughput for the proposed scheme. Subsequently, the number of repeated transmissions of a message, i.e., the number of replicas transmitted by each user, is optimized to further improve the system throughput and energy efficiency. Interestingly, the optimization results show that the optimal number of replicas for maximizing the energy efficiency is a constant for all offered loads. On the other hand, the optimal number of replicas that maximizes the system throughput decreases as the offered load increases. Numerical results show that the derived analytical results closely match with the simulation results. Furthermore, the proposed scheme achieves a considerable throughput improvement, compared to the CRDSA++ scheme. [ABSTRACT FROM AUTHOR]

We focus on the two-user Gaussian interference channel (IC) with fading and study implementation of different encoding/decoding schemes with low-density parity-check (LDPC) codes for both quasi-static and fast fading scenarios. We adopt Han–Kobayashi encoding, derive stability conditions on the degree distributions of LDPC code ensembles, and obtain explicit and practical code designs. In order to estimate the decoding thresholds, a modified form of the extrinsic information transfer chart analysis based on binary erasure channel approximation for the incoming messages from the component LDPC decoders to state nodes is developed. The proposed code design is employed in several examples for both fast and quasi-static fading cases. Comprehensive set of examples demonstrate that the designed codes perform close to the achievable information theoretic limits. Furthermore, multiple antenna transmissions employing the Alamouti scheme for fading ICs are studied, a special receiver structure is developed, and specific codes are explored. Finally, advantages of the designed codes over point-to-point optimal ones are demonstrated via both asymptotic and finite block length simulations. [ABSTRACT FROM AUTHOR]

Small-cell network is a promising solution to high video traffic. However, with the increasing number of devices, it cannot meet the requirements from all users. Thus, we propose a caching device-to-device (D2D) scheme for small-cell networks, in which caching placement and D2D establishment are combined. In this scheme, a limited cache is equipped at each user, and the popular files can be prefetched at the local cache during off-peak period. Thus, dense D2D connections can be established during peak time aided by these cached users, which will reduce the backhaul pressure significantly. To do this, first, an optimal caching scheme is formulated according to the popularity to maximize the total offloading probability of the D2D system. Thus, most edge users can obtain their required video files from the caches at users nearby, instead from the small-cell base station. Then, the sum rate of D2D links is analyzed in different signal-to-noise ratio (SNR) regions. Furthermore, to maximize the throughput of D2D links with low complexity, three D2D-link scheduling schemes are proposed with the help of bipartite graph theory and Kuhn-Munkres algorithm for low, high, and medium SNRs, respectively. Simulation results are presented to show the effectiveness of the proposed scheme. [ABSTRACT FROM AUTHOR]

The traditional degree distribution framework is a useful tool to analyze irregular low density parity check (LDPC) code. However, it cannot be used to analyze raptor-like LDPC code as it cannot describe the most important structural feature of raptor-like LDPC code, which is that any check node is connected to at most one degree-one variable node. In this paper, we propose a two-type degree distribution framework for raptor-like LDPC code. The proposed framework can describe the special structural feature of raptor-like LDPC code by dividing the check nodes into two different sets. One is the set of check nodes connected to those degree-one variable nodes, the other is the set of check nodes unconnected to those degree-one variable nodes. Furthermore, we propose a two-type discrete density evolution algorithm and a two-type Gaussian approximation density evolution algorithm based on the proposed two-type degree distribution framework to estimate the threshold of raptor-like LDPC code. During the decoding analysis, the proposed algorithms treat the check nodes belonging the two separate sets differently. Compared with the traditional multi-edge type (MET) algorithm, the proposed algorithms allow us to calculate the threshold more quickly without much sacrifice in accuracy. For some raptor-like LDPC codes adopted by the Advanced Television Systems Committee 3.0 (ATSC3.0) standard, the thresholds estimated by the proposed algorithms can be very close to the thresholds estimated by the traditional MET algorithm. The deviations are less than 0.07 dB. Meanwhile, the proposed algorithms can tremendously reduce the computation complexity because of the two-type degree distribution framework and the Gaussian approximation. [ABSTRACT FROM AUTHOR]

The full duplex (FD) two-way relay channel (TWRC) has recently been shown to be a feasible way to improve the network throughput in practical communications. In this correspondence, we consider the convolutionally coded physical-layer network coding over the TWRC in which two sources work in the FD mode and there exists a direct link between them. Every source receives two packets, one packet from the other source and one network coded packet from the relay. A near-maximum-likelihood decoding algorithm for the sources is proposed. A salient feature of the proposed algorithm is that it exploits the code structure to mitigate the error propagation induced by the relay. Furthermore, we derive the near maximum-likelihood decoding bound on end-to-end BER for the system. Simulation results indicate that the performance of the proposed algorithm matches well the bound. [ABSTRACT FROM AUTHOR]

In this correspondence, an uplink nonorthogonal multiple access (NOMA) system where the base station (BS) trends to decode the independent information of users occupying the same radio resource simultaneously is considered. Different from the traditional successive interference cancellation (SIC) decoding scheme where the later decoding can only be processed after the successful decoding of the previous users, an advanced SIC decoding strategy is proposed to achieve outage balancing for the later decoded users. Under the proposed SIC decoding mechanism, the BS regards the unsuccessfully decoded users’ information as the interference on the following users, i.e., even the outage occurs for any of the previous decoded users, the BS will still try to decode the following users’ information. The outage performance with the new decoding strategy is theoretically analyzed. The closed-form expressions of the outage probability for each user are derived for an uplink 2-user NOMA system. The accuracy of the theoretical results is verified by the simulations. [ABSTRACT FROM AUTHOR]

The problem of identifying digital amplitude-phase modulations under additive noise is addressed within the theory of empirical Bayes deconvolution. The presented methods employ parametric models in the observation and signal constellation spaces. The model parameters are estimated using the received samples and then substituted into the respective models to obtain the estimate for the signal constellation, from which the decoding of the received samples can be accomplished. The proposed framework can be used to construct a modulation dictionary for an unknown transmitter prior to employing any hypothesis testing-based classification algorithm. [ABSTRACT FROM AUTHOR]

Symbol-based iterative decoding is proposed for the transmission of classical Markov source signals over a quantum channel using a three-stage serial concatenation of a convolutional code (CC), a unity-rate code and a two-qubit superdense (SD) protocol. A modified symbol-based maximum a posteriori algorithm is employed for CC decoding to exploit the Markov source statistics during the iterative decoding process. Extrinsic information transfer chart analysis is performed to evaluate the benefit of the extrinsic mutual information gleaned from the CC decoder for sources with different correlations. We evaluate the bit error rate performance of the proposed coding scheme and compare it with the relevant benchmark schemes, including the turbo coding-based SD scheme. We demonstrate that a near-capacity performance can be achieved using the proposed scheme and when utilizing sources having a high correlation coefficient of $\rho =0.9$, the proposed coding scheme performs within 0.53 dB from the entanglement-assisted classical capacity. [ABSTRACT FROM PUBLISHER]

A precoding design is proposed for multiple-input multiple-output (MIMO) systems utilizing nonbinary low-density parity check (NB-LDPC) codes and many-to-one mapping. When a high-order modulation scheme is used, many-to-one mapping converts a group of low-order Galois field (GF) coded symbols into one modulated MIMO symbol vector. In contrast, one-to-one mapping maps a high-order modulation symbol directly from one high-order GF coded symbol. With the help of an interleaver between the NB-LDPC encoder and the GF to MIMO symbol mapper, the many-to-one mapping enables turbo receiver and reduces the computational complexity by more than 95%. The proposed MIMO precoders enhance the error-rate performance of the many-to-one NB-LDPC MIMO system, especially in terms of reducing the error floor and improving the waterfall region. The proposed precoder design modifies the approach that suboptimally maximizes the minimal Euclidean distance between the received MIMO symbols. Simulation results show that the proposed precoders enhance the robustness of the precoder design and reduce the inner and outer iterations of the turbo receiver. [ABSTRACT FROM PUBLISHER]

High-speed and low-latency communications are one of the major requirements for connected vehicle environments. Safety messages in vehicular networks must arrive on time for each vehicle, and the optimization of driving paths also strongly depends on low-latency traffic information. To comply with the demands, a base station take important roles to provide a short service delay for the vehicles, even at the expense of performance. The relationship between delay time and decoding performance at receiver sides in physical layers can be explained by the performance/complexity tradeoff as follows. To achieve better performance in terms of the minimization of word error rates in decoding, the receiver usually requires higher complexity, which results in larger delays. We analyze this tradeoff based on the receiver queue model. This paper proposes a novel algorithm to adaptively select one of receiver candidates under the constraint of queue stability so as not to degrade low-latency communications. Based on the configurable architecture for multi-input multioutput (MIMO) detectors, this paper shows that the proposed algorithm works well on adaptive MIMO detector selection. [ABSTRACT FROM PUBLISHER]

This paper presents the first network-coded multiple access (NCMA) system prototype operated on high-order modulations up to 16-QAM. NCMA jointly exploits physical-layer network coding (PNC) and multiuser decoding (MUD) to boost throughput of multipacket reception systems. Direct generalization of the existing NCMA decoding algorithm, originally designed for BPSK, to high-order modulations, will lead to huge performance degradation. The throughput degradation is caused by the relative phase offset between received signals from different nodes. To circumvent the phase offset problem, this paper investigates an NCMA system with multiple receive antennas at the access point, referred to as MIMO-NCMA. We put forth a low-complexity symbol-level NCMA decoder that, together with MIMO, can substantially alleviate the performance degradation induced by relative phase offset. To demonstrate the feasibility and advantage of MIMO-NCMA for high-order modulations, we implemented our designs on software-defined radio. Our experimental results show that the throughput of QPSK MIMO-NCMA is double that of both BPSK NCMA and QPSK MUD at SNR = 10 dB. For higher signal-to-noise ratios at which 16-QAM can be supported, the throughput of MIMO-NCMA can be as high as 3.5 times that of BPSK NCMA. Overall, this paper provides an implementable framework for high-order modulated NCMA. [ABSTRACT FROM PUBLISHER]

This paper studies the effectiveness and relay efficiency of using opportunistic multipoint relaying and distributed space-time coding (ODSTC) for cooperative Automatic Repeat reQuest (ARQ). According to the complexities for diversity exploration in retransmissions, three types of ARQ protocols are studied herein, allowing us to examine the effectiveness of the protocols and the efficiencies of using ODSTC relaying for ARQ. The efficiency is studied from the viewpoint of the signal quality enhancement per active relay, while the effectiveness is investigated from the perspectives of diversity and throughput improvements with the different protocols. The results show that both are closely related to the link qualities of the forwarding channels. When the link quality between the source and relays is considerably higher than the quality between the relays and the destination, a simple protocol that opportunistically chooses two active relays for ODSTC (ODSTC2) at the beginning of retransmissions is good enough to yield a significant throughput improvement. Otherwise, when the performance is limited by the number of successfully decoding relays, then having relays of unsuccessful decoding to overhear the signals sent by active relays plays a crucial role in resolving the limitation. By having the new successfully decoding relays to participate in the subsequent retransmissions, both diversity and throughput can be significantly improved. According to our analysis and simulation studies, an appropriate protocol with ODSTC2 in general can provide effective throughput improvements in two times retransmissions. [ABSTRACT FROM AUTHOR]

We present a new design approach to construct generalized concatenated codes (GCCs) based on polar codes (PCs). It is already known that PCs can be considered as a special class of the GCCs with polar outer and inner codes. We show how density evolution (DE) can be used to develop a channel-specific method to design outer codes of length $L$ under maximum-likelihood (ML) decoding. Once a bank of outer codes of length L$ and different rates have been designed, we develop a rate-allocation algorithm to allocate rates to the outer codes of the GCC with the goal of minimizing the overall block error rate for a given overall rate of K/N$. To maintain the low complexity of the SC decoder, we only design very short outer codes . We show that, at this outer code length, it is possible to design GCC-PCs that can result in up to 0.5-dB coding gain while reducing decoding complexity. [ABSTRACT FROM PUBLISHER]

For several years, the completion time and the decoding delay problems in instantly decodable network coding (IDNC) were considered separately and were thought to act completely against each other. Recently, some works have aimed to balance the effects of these two important IDNC metrics, but none of them studied a further optimization of one by controlling the other. This paper investigates the effect of controlling the decoding delay to reduce the completion time below its currently best known solution in both perfect and imperfect feedback with persistent erasure channels. To solve the problem, the decoding-delay-dependent expressions of the users' and overall completion times are derived in the complete feedback scenario. Although using such expressions to find the optimal overall completion time is NP-hard, this paper proposes two novel heuristics that minimize the probability of increasing the maximum of these decoding-delay-dependent completion time expressions after each transmission through a layered control of their decoding delays. Afterward, this paper extends the study to the imperfect feedback scenario, in which uncertainties at the sender affect its ability to anticipate accurately the decoding delay increase at each user. This paper formulates the problem in such an environment and derives the expression of the minimum increase in the completion time. Simulation results show the performance of the proposed solutions and suggest that both heuristics achieve a lower mean completion time, as compared with the best known heuristics for completion time reduction in perfect and imperfect feedback. The gap in performance becomes more significant as the erasure of the channel increases. [ABSTRACT FROM PUBLISHER]

We propose a low-complexity, complex-valued sphere decoding (CV-SD) algorithm, which is referred to as circular sphere decoding (CSD) and is applicable to multiple-input–multiple-output (MIMO) systems with arbitrary 2-D constellations. CSD provides a new constraint test. This constraint test is carefully designed so that the elementwise dependence is removed in the metric computation for the test. As a result, the constraint test becomes simple to perform without restriction on its constellation structure. By additionally employing this simple test as a prescreening test, CSD reduces the complexity of the CV-SD search. We show that the complexity reduction is significant, while its maximum-likelihood (ML) performance is not compromised. We also provide a powerful tool to estimate the pruning capacity of any particular search tree. Using this tool, we propose the predict-and-change strategy, which leads to a further complexity reduction in CSD. Extension of the proposed methods to soft output sphere decoding (SD) is also presented. [ABSTRACT FROM PUBLISHER]

This paper investigates distributed linear constellation precoding (DLCP) for two-way relaying communication systems in conjunction with the techniques of bit-interleaved coded modulation (BICM) and BICM with iterative decoding (BICM-ID). First, a decoding strategy for the relay node that is based on quaternary code representation is developed. Then, the union bounds (for the case of BICM) and error-free feedback bounds (for the case of BICM-ID) on the quaternary digit error probability and bit error probability under network coding in the multiple-access (MA) phase are obtained. Based on the obtained bounds, the impact of DLCP on the error performance is analyzed by considering three error types in the MA phase. It is shown that type-3 errors need to be carefully taken into account in the design of a DLCP scheme. By developing a performance metric related to type-3 errors, the design parameter of DLCP is optimized when BICM is used, whereas it is shown that DLCP is not needed when BICM-ID is used. Extensive simulation results are provided to corroborate the analysis and demonstrate the performance superiority of the proposed decoding strategy over the one that directly decodes the exclusive-OR (xor) code. For the case of BICM, the performance advantage achieved by properly designing DLCP is also illustrated. [ABSTRACT FROM AUTHOR]

Motivated by the structure of basic sensor networks, we study an optimal joint decoding problem in which the real-valued outputs of two correlated Gaussian sources are scalar quantized, bit assigned, and transmitted, without applying channel coding or interleaving, over a multiple-access channel that consists of two orthogonal point-to-point time-correlated Rayleigh fading subchannels used with soft-decision demodulation. Each fading subchannel is modeled by a nonbinary Markov noise discrete channel that was recently shown to effectively represent it. The correlated sources have memory captured by a time-varying correlation coefficient governed by a two-state first-order Markov process. At the receiver side, we design a joint sequence maximum a posteriori (MAP) decoder to exploit the correlation between the two sources, their temporal memory, and the redundancy left in the quantizers' indexes, the channels' soft-decision outputs, and noise memory. Under the simple practical case of using two-level source quantization, we propose a Markov model to estimate the joint behavior of the quantized sources. We then establish necessary and sufficient conditions under which the delay-prone joint sequence MAP decoder can be reduced to a simple instantaneous symbol-by-symbol decoder. We illustrate our analytical results by system simulation and demonstrate that joint MAP decoding can appropriately harness source and channel characteristics to achieve improved signal-to-distortion ratio performance for a wide range of system conditions. [ABSTRACT FROM PUBLISHER]

To achieve an excellent error-correcting capability, the Third-Generation Partnership Project (3GPP) Long-Term Evolution (LTE) employs turbo codes as its forward error correction (FEC) standard. In addition, to achieve higher throughput, the LTE also implements multiple-input–multiple-output (MIMO) systems. Although a conventional turbo decoding scheme gives satisfactory performance in ideal MIMO systems, significant performance degradation occurs in an overloaded MIMO system when the number of transmit antennas is larger than that of receive antennas. In this paper, a joint decoding scheme for turbo codes, i.e., so-called joint turbo decoding, is proposed. In joint turbo decoding, calculations of soft information are conducted for each combination of bits from all streams instead of separately between each stream. In addition, to combine the trellis diagrams from all the streams, a super-trellis diagram is employed. The numerical results obtained through computer simulation show that the proposed scheme performs better than the conventional scheme, particularly in the case of an overloaded MIMO system. In the MIMO system with four transmit and two receive antennas, up to 2-dB performance enhancement can be attained at a bit error rate (BER) of 10−5. The proposed scheme also obtains improved throughput with a throughput/(SNR/stream) ratio close to the theoretical capacity of overloaded MIMO systems. [ABSTRACT FROM PUBLISHER]

In a massive multiple-input–multiple-output (MIMO) uplink system, the pilot sequence reuse in neighboring cells causes pilot contamination, causing the decoding performance to degrade significantly. In this paper, a blind decoding method based on independent component analysis (ICA) is proposed without using pilot sequences. The proposed blind decoding method uses ICA to separate the received signals (from in-cell and neighboring cells) and estimate channels. The energy levels of the estimated channels are used to differentiate an in-cell signal from neighboring cell signals. The analytical performance results of the blind decoding method are derived. Numerical results show that the proposed blind decoding scheme outperforms minimum-mean-square-error (MMSE) decoding and zero-forcing (ZF) decoding with imperfect channel state information (CSI). The proposed scheme has only a negligible performance loss compared with MMSE decoding and ZF decoding with perfect CSI. [ABSTRACT FROM PUBLISHER]

This paper proposes a bidirectional soft-decision feedback turbo equalizer for severe triply selective fading channels. The proposed bidirectional soft-decision feedback equalizer (Bi-SDFE) uses a time reversed SDFE in conjunction with a normal SDFE to harvest time-reverse diversity and mitigate error propagation. A simple and effective linear combining scheme is derived for combining the extrinsic information on the two SDFEs for multiple-input–multiple-output (MIMO) systems with multilevel modulation. The bit-error-rate (BER) simulation results show that the proposed Bi-SDFE exhibits a lower signal-to-noise-ratio (SNR) threshold than the original SDFE and outperforms the well-known exact turbo minimum mean square error (MMSE) linear equalizers (LEs) at medium-to-high SNRs. Moreover, both extrinsic information transfer (EXIT) chart analysis and BER simulation results show that the Bi-SDFE achieves better performance than the original SDFE, whereas the Bi-SDFE uses only half the number of iterations of the SDFE. Therefore, the total computational complexity of the Bi-SDFE is similar to that of the original SDFE, which is a linear function of the channel length, MIMO size, and modulation constellation size. The performance gain of the proposed Bi-SDFE is also verified through an underwater acoustic (UWA) communication experiment with tough channel conditions. [ABSTRACT FROM AUTHOR]

This paper proposes a relay selection (RS) scheme that aims to improve the end-to-end symbol error rate (SER) performance of a two-way relay network (TWRN). The TWRN consists of two single-antenna sources and multiple relays employing a decode-and-forward (DF) protocol. It is shown that the SER performance is determined by the minimum decision distance (DD) observed in the TWRN. However, the minimum DD is likely to be made arbitrarily small by channel fading. To tackle this problem, a phase rotation (PR)-aided RS scheme is proposed to enlarge the minimum DD, which, in turn, improves the SER performance. The proposed PR-based scheme rotates the phases of the transmitted symbols of one source and of the selected relay according to the channel state information (CSI), aiming for increasing all DDs to be above a desired bound. The lower bound is further optimized by using a MaxMin-RS criterion associated with the channel gains. It is demonstrated that the PR-aided MaxMin-RS approach achieves full diversity gain and improved array gain. Furthermore, compared with the existing DF-based schemes, the proposed scheme allows more flexible relay antenna configurations. [ABSTRACT FROM AUTHOR]

We propose iterative detection and decoding (IDD) algorithms with low-density parity-check (LDPC) codes for multiple-input multiple-output (MIMO) systems operating in block-fading and fast Rayleigh fading channels. Soft-input–soft-output minimum-mean-square-error (MMSE) receivers with successive interference cancelation are considered. In particular, we devise a novel strategy to improve the bit error rate (BER) performance of IDD schemes, which takes into account the soft a posteriori output of the decoder in a block-fading channel when root-check LDPC codes are used. A MIMO IDD receiver with soft information processing that exploits the code structure and the behavior of the log-likelihood ratios is also developed. Moreover, we present a scheduling algorithm for decoding LDPC codes in block-fading channels. Simulations show that the proposed techniques result in significant gains in terms of BER for both block-fading and fast-fading channels. [ABSTRACT FROM AUTHOR]

This paper introduces a novel transmission design for antenna beam pattern modulation (ABPM) with a low-complexity decoding method. The concept of ABPM was first presented with optimal maximum-likelihood (ML) decoding. However, an ML detector may not be viable for practical systems when the constellation size or the number of antennas is large, such as in massive multiple-input–multiple-output (MIMO) systems. Linear detectors, on the other hand, have lower complexity but inferior performance. In this paper, we present the antenna pattern selection with a lattice-reduction-aided linear detector for ABPM to reduce the detection complexity with the bit error rate (BER) performance approaching that of ML while conserving low complexity. Simulation results show that even with this suboptimal detection, performance gain is achieved by the proposed scheme compared with different spatial modulation techniques using ML detection. In addition, to validate the results, an upper bound expression for the BER is provided for ABPM with ML detection. [ABSTRACT FROM AUTHOR]

This paper investigates the tradeoff between the energy efficiency (EE) and the effective throughput (ET) of fading channels. In particular, we consider the case of zero channel state information (CSI) at the transmitter, and thus, the receiver can only successfully decode the source messages with certain probability. Accordingly, the ET, which is defined as the rate of the successfully decoded information, is adopted to measure the spectrum efficiency of the considered channels. We characterize the EE–ET region by exploiting its structure, and each boundary point is obtained by solving a quasi-concave problem. As a special case, we also obtain the maximum ET per unit energy in closed form. Finally, we generalize our results to the case of multihop relay channels. [ABSTRACT FROM AUTHOR]

Energy harvesting (EH) from background radio-frequency signals has recently started to be considered as a promising means of mitigating energy deficiencies in wireless sensors that have limited battery power. In this paper, to deal with the problem of energy shortage, we consider EH and energy efficiency, which is the ratio of the amount of data transferred to the energy dissipated within the system, at the same time. We formulate a nonconvex optimization problem for determining the training interval for channel estimation, user scheduling, and power allocation strategies to maximize the energy efficiency and transform the problem into a tractable convex problem. Based on the convexity of the problem, we propose an energy-efficient resource allocation strategy using an iterative method and provide the convergence of the proposed algorithm based on nonlinear fractional programming. The simulation results show that the proposed algorithm operates in an energy-efficient way, thereby achieving maximum energy efficiency while ensuring the data rate and harvested energy requirements. [ABSTRACT FROM AUTHOR]

Interlayer forward error correction (IL-FEC) coding constitutes an effective unequal error protection (UEP) scheme conceived for transmitting layered video over wireless channels. In contrast to traditional UEP schemes, it operates by embedding extra information concerning the base layer (BL) into the enhancement layers (ELs) without requiring extra transmission resources. The received EL packets assist in the decoding of the BL to reduce the distortion of the reconstructed video. The optimum scheduling of the IL-FEC coded layered video streaming in a truncated hybrid automatic repeat request (THARQ)-aided system is an open problem. Hence, in this paper, we conceive an adaptive THARQ (ATHARQ) algorithm for finding the most appropriate scheduling of the IL-FEC coded layered video packets for the sake of minimizing the video distortion under the constraint of a given total number of transmission time slots (TSs). Furthermore, we develop a method of online coding-rate optimization algorithm for our IL-ATHARQ transmission scheme to find the best FEC code rate distribution among the video layers that results in the lowest possible video distortion. When using a recursive systematic convolutional (RSC) code, our simulation results show that the proposed rate-optimized (RO) IL-ATHARQ system outperforms the traditional THARQ transmission scheme by about 5.3 dB of Eb/N0 at a peak signal-to-noise ratio (PSNR) of 38.5 dB. Viewing the improvements in terms of the video quality, 2.5 dB of PSNR improvement is attained at an Eb/N0 of 15 dB. [ABSTRACT FROM AUTHOR]

An adaptive dynamic network coding (ADNC) scheme conceived for cooperative cognitive radio (CCR) is proposed for devising a novel ADNC-CCR system. The system is designed for supporting communications between multiple primary users (PUs) and a common base station (BS), where the independent source information is transmitted from the PUs to the BS with the aid of multiple cognitive users (CUs) acting as relay nodes (RNs). To facilitate the recovery of the source information at the BS, the CUs invoke the ADNC technique, which is assisted by our cooperative protocol operating by exchanging the CCR-based control information between near-instantaneously adaptive turbo trellis coded modulation (ATTCM) and network coding (NC) codec, as well as between the CUs and the BS. More particularly, near-instantaneous ATTCM is employed for appropriately adjusting both the modulation mode and the code rate of the channel coding itself and of the NC, according to the near-instantaneous channel conditions. As a result, our novel ADNC-CCR system constructed on the basis of our holistic approach is capable of providing an increased throughput, despite reducing the transmission period of the PU. This reduced transmission period can also be directly translated into an increased duration for secondary communications of the CUs. In our proposed ADNC-CCR scheme, both the PUs and CUs employ our ATTCM scheme. As an additional novelty, the network encoder may also be activated in its adaptive mode for supporting the CUs, depending on the Boolean value of the feedback flags generated based on the success/failure of the ATTCM decoder and of the network decoder, which is evaluated and fed back by the BS. Quantitatively, it was found that the joint holistic design of our ATTCM-ADNC-CCR scheme is either capable of freeing up an approximately 40% of the PU's bandwidth in comparison to its noncooperative counterpart or increasing the attainable throughput by 2 bits/symbol. [ABSTRACT FROM AUTHOR]

This paper proposes a method of implementing analog eigenmode transmission for a short-range multiple-input–multiple-output (SR-MIMO) system that uses only 180° hybrid couplers. If the short-range MIMO system places transmitting and receiving arrays in line-of-sight (LOS) and symmetrically with respect to specific reference planes, the channel matrix in the system also becomes symmetrical. This allows the channel matrix to be diagonalized by connecting 180° hybrid couplers to both ports at the transmitter and receiver sides, i.e., eigenmode transmission can be realized. In this paper, first, the theory of the proposed technique is explained by taking a 2 $\times$ 2 MIMO as an example, based on the characteristics of 180° hybrid coupler and the theory of the cascade-connected network. Moreover, an extension to the method that offers 4 $\times$ 4 MIMO is also proposed. This paper clarifies that this proposed technique can diagonalize the channel matrix, regardless of array configuration, such as type of antennas and antenna spacing, as long as the symmetry of the system configuration is assured. Furthermore, numerical results verify that the distance between the transmitter and the receiver has no effect on channel orthogonality. As a result, this technique partially avoids the performance degradation caused by array displacement, which is a major disadvantage of the conventional analog-beamforming-based decoding technique for short-range MIMO systems. Thus, the superiority of the proposed technique is clear. [ABSTRACT FROM PUBLISHER]

Hierarchical modulation (HM), which is also known as layered modulation, has been widely adopted across the telecommunication industry. Its strict backward compatibility with single-layer modems and its low complexity facilitate the seamless upgrading of wireless communication services. The potential employment of HM in cooperative communications has the promise of increasing the achievable throughput at low power consumption. In this paper, we propose a single-relay-aided hierarchical-modulation-based cooperative communication system. The source employs a pair of turbo trellis-coded modulation (TTCM) schemes relying on specially designed HM, whereas the relay invokes the decode-and-forward (DAF) protocol. We have analyzed the system's achievable rate, as well as its bit error ratio (BER), using Monte Carlo simulations. The results demonstrate that the power consumption of the entire system is reduced to 3.62 dB per time slot (TS) by our scheme. [ABSTRACT FROM PUBLISHER]

In this paper, we propose a channel transformation technique for joint decoding of desired and interfering signals in an interference alignment scenario consisting of $K$ users with multiple antennas. Our technique, i.e., pseudo-lattice treatment, is based on the compute-and-forward framework. Our technique can be implemented to provide decoding gains with low complexity for subspace aligned interference signals. We evaluate the performance of the system through simulations that show the performance gain attained by using our pseudo-lattice method over subspace decoding techniques for interference alignment in low- and medium-SNR conditions. [ABSTRACT FROM AUTHOR]

Communication systems are susceptible to impulse noise, particularly when the impulse statistics are not time invariant and are difficult to model accurately. To address the challenge of impulse noise, a robust and efficient decoding scheme was devised for single-carrier convolutionally coded transmissions over memory impulse noise channels. By accommodating channel states but without relying on statistical knowledge of impulses, the Viterbi algorithm (VA) based on an expanded set of trellis states was employed to perform maximum-likelihood decoding. A detailed analysis of complexity was offered; the analytical results reinforced the efficiency of the proposed scheme compared with the traditional VA. The simulation results indicated that the proposed decoding scheme is compellingly robust: The bit error probability performance level attained using the proposed decoder is remarkably close to that of an optimal decoder, which uses impulse statistics; furthermore, the proposed decoder was superior to the alpha-penalty function decoder, which neglects the channel memory property and experiences an error floor under fairly general circumstances. [ABSTRACT FROM AUTHOR]