This paper presents a new protograph-based LDPC code design framework that simultaneously achieves full diversity over block-fading channels (BFCs) and near-capacity performance over additive white Gaussian noise channels. By leveraging a Boolean approximation-based analysis-Diversity Evolution-we derive structural constraints with generalized rootchecks that guarantee full diversity. Building on these constraints, we propose a diversity-aligned protograph template tailored for the two-block BFC (M=2) that ensures full diversity under iterative belief propagation decoding. Furthermore, a genetic algorithm guided by density evolution is employed to optimize the protograph edges within this family for improved coding gain. The resulting codes, termed DA-GRP-LDPC codes, simultaneously achieve full diversity and enhanced coding gain, reaching a 0.8 dB gap to the outage limit for the two-block BFC at a block length of 16,896. This demonstrates that the proposed framework effectively bridges the gap between diversity optimality in non-ergodic channels and high coding gain in ergodic channels.

We propose a polar coding scheme for block fading channels, aiming to achieve maximum diversity while maintaining the performance under additive white Gaussian noise channels (AWGNC). The key idea isdiversity alignment, which aligns maximum diversity with information bits through proper codeword bit to fading block mapping. We first develop a low-complexity diversity analysis tool based on Boolean approximation under genie-aided successive cancellation decoding which can be used for arbitrary bit-to-block mapping. Second, we propose a tractable optimal block mapping forM= 2 fading blocks and develop fast search algorithms for generalM≥ 2, achieving optimal low-rate diversity coding (dc=MatR= 1/M) for a wide range ofM. Moreover, our scheme can be applied to achieve optimal high-rate diversity-2 coding (dc= 2 atR= (M−1)/M) with good AWGNC codes. We show that appropriate block-mapping can achieve both low-rate and high-rate optimal diversity simultaneously. Numerical results demonstrate that our framework provides accurate diversity analysis and the proposed DA scheme outperforms conventional interleavers under block fading channels while preserving AWGNC performance. The proposed can play a crucial role in supporting the URLLC communication in future systems, where channel is quickly changing but high reliability is required.

Error correcting codes (ECCs) are indispensable for reliable transmission in communication systems. Recent advancements in deep learning have catalyzed the exploration of ECC decoders based on neural networks. Among these, transformer-based neural decoders have achieved state-of-the-art decoding performance. In this paper, we propose a novel Cross-Attention Message-Passing Transformer (CrossMPT), which shares key operational principles with conventional message-passing decoders. While conventional transformer-based decoders employ a self-attention mechanism without distinguishing between magnitude and syndrome embeddings, CrossMPT updates these two types of embeddings separately and iteratively via two masked cross-attention blocks. The mask matrices are determined by the code's parity-check matrix, which explicitly captures and removes irrelevant relationships between the magnitude and syndrome embeddings. Our experimental results show that CrossMPT significantly outperforms existing neural network-based decoders for various code classes. Notably, CrossMPT achieves this decoding performance improvement while significantly reducing memory usage, computational complexity, inference time, and training time.

Ensuring extremely high reliability in channel coding is essential for 6G networks. The next-generation of ultra-reliable and low-latency communications (xURLLC) scenario within 6G networks requires frame error rate (FER) below 10-9. However, low-density parity-check (LDPC) codes, the standard in 5G new radio (NR), encounter a challenge known as the error floor phenomenon, which hinders to achieve such low frame error rates. To tackle this problem, we introduce an innovative solution: boosted neural min-sum (NMS) decoder. This decoder operates identically to conventional NMS decoders, but is trained by novel training methods including: i) boosting learning with uncorrected vectors, ii) block-wise training schedule to address the vanishing gradient issue, iii) dynamic weight sharing to minimize the number of trainable weights, iv) transfer learning to reduce the required sample count, and v) data augmentation to expedite the sampling process. Leveraging these training strategies, the boosted NMS decoder achieves the state-of-the art performance in reducing the error floor as well as superior waterfall performance. Remarkably, we fulfill the 6G xURLLC requirement for 5G LDPC codes without a severe error floor. Additionally, the boosted NMS decoder, once its weights are trained, can perform decoding without additional modules, making it highly practical for immediate application. The source code is available athttps://github.com/ghy1228/LDPC_Error_Floor.

With the broadening applications of deep learning, neural decoders have emerged as a key research focus, specifically aimed at improving the decoding performance of conventional decoding algorithms. In particular, error correction code transformer (ECCT), which utilizes the transformer architecture, has achieved state-of-the-art performance among neural network-based decoders. We present three technical contributions to significantly enhance the performance of ECCT. First, we propose a novel transformer architecture of ECCT, termed themultiple-masks ECCT (MM ECCT). We employ multiple masked self-attention blocks with different mask matrices in a parallel manner to learn diverse relationships among the codeword bits. Second, we discover that constructing mask matrices based on systematic parity check matrices (PCMs) can make the attention mapssparse, which not only enhances the decoding performance but also reduces computational complexity. Finally, we propose using complementary mask matrices derived from cyclic permutations of the systematic PCM. These complementary mask matrices are specifically designed to enhance the decoding of cyclic codes. Our extensive simulation results show that the proposed MM ECCT architecture with carefully designed mask matrices outperforms the original ECCT by a large margin, achieving state-of-the-art decoding performance among neural decoders. The source code is available at https://github.com/iil-postech/mm-ecct.

In the realm of mobile communications, the receiver often encounters undesired situations where it receives only noise, interference, or unintended signals. In such cases, it may incorrectly infer that the decoding result is valid, particularly when the error detection capability, mainly provided by a cyclic redundancy check (CR C) code, falls short. While bounded distance decoding techniques based on the employed error-correcting code have been introduced to address this issue, there is still room for improvement especially when dealing with unintended signals. In this paper, we present a formula to identify the situation of unintended signals and find it expressed in terms of a metric called discrepancy. Utilizing this discrepancy, we interpret the problem of determining the validity of decoding results as a binary classification task. Then, we propose suitable machine learning techniques to improve the accuracy of the binary classification process. Our experimental results, conducted for the 5G New Radio (NR) system, demonstrate significant performance improvement resulting from the application of the proposed methods.

DRAM technology has continually evolved to meet escalating demands for higher memory capacity and greater data bandwidth. This progression, however, has also led to increases in both storage and transfer errors, primarily due to the smaller transistors and higher transfer rates. To combat these errors, systems employ both Error Correcting Codes (ECC) and Cyclic Redundancy Check (CRC), despite their substantial performance and energy costs. This paper introduces a novel ECC, Dual-Axis ECC (DA-ECC), which provides unified protection against both storage and transfer errors. DA-ECC enhances traditional ECC approaches to correct one half-chipkill error, two DQ errors, or one transfer error on the Data Strobe (DQS) signal in × 8 DRAM chips. This comprehensive protection eliminates the need for additional CRC mechanisms. Our evaluations demonstrate that DA-ECC not only enhances system performance by up to 1.6% but also improves DRAM energy efficiency by up to 8.2% while providing a robust solution to the dual challenges of storage and transfer errors.

Low-density parity-check (LDPC) codes have been successfully commercialized in communication systems due to their strong error correction capabilities and simple decoding process. However, the error-floor phenomenon of LDPC codes, in which the error rate stops decreasing rapidly at a certain level, presents challenges for achieving extremely low error rates and deploying LDPC codes in scenarios demanding ultra-high reliability. In this work, we propose training methods for neural min-sum (NMS) decoders to eliminate the error-floor effect. First, by leveraging the boosting learning technique of ensemble networks, we divide the decoding network into two neural decoders and train the post decoder to be specialized for uncorrected words that the first decoder fails to correct. Secondly, to address the vanishing gradient issue in training, we introduce a block-wise training schedule that locally trains a block of weights while retraining the preceding block. Lastly, we show that assigning different weights to unsatisfied check nodes effectively lowers the error-floor with a minimal number of weights. By applying these training methods to standard LDPC codes, we achieve the best error-floor performance compared to other decoding methods. The proposed NMS decoder, optimized solely through novel training methods without additional modules, can be integrated into existing LDPC decoders without incurring extra hardware costs. The source code is available at https://github.com/ghy1228/LDPC_Error_Floor.

This paper presents an analytically designed layered decoding algorithm for quasi-cyclic low-density parity-check (QC-LDPC) codes in the 5th Generation (5G) New Radio (NR) mobile communication system. First, a layered density evolution (DE) based on reciprocal channel approximation (RCA) is newly developed to accurately reflect the layered decoding operation in the decoder design. Using this technique, a single nested sequence is optimized in a greedy way to configure the processing order for any given number of layers. The error-correction performance is improved by up to 0.15 dB, while the number of iterations is reduced by about one simultaneously.

This paper considers unmanned aerial vehicles (e.g., drones and quadcopters) that accomplish missions of transmitting a large number of progressive images over air-to-ground multiple-input multiple-output (MIMO) links for surveillance applications, and special missions of public safety or emergencies. For the transmission of progressive images, the joint optimization of source and channel coding of a series of numerous packets has been a challenging problem. Further, the problem is more complicated if the space-time coding is also involved with the optimization in a MIMO system. This is because the number of ways of jointly assigning channel codes and space-time codes to progressive packets is much larger than that of solely assigning channel codes to the packets. Recently, Chang et al. applied a parametric approach to address such a problem, and proposed an optimization algorithm that exponentially reduces the computational complexities of the conventional exhaustive search. For resource-constrained aerial equipments, complexity is of particular importance due to hardware power consumption and size issues. To address such issues, we propose a neural network-based optimization method to further reduce computational complexities. We demonstrate that the nonlinear distortion-rate characteristics of the images, which are combined with wireless channel fading effects, can be analyzed and learned by a neural network. It is shown that compared to the algorithm proposed by Chang et al., our approach significantly reduces the computational complexities, while offering nearly identical peak-signal-to-noise ratio (PSNR) performances.

This paper presents density evolution (DE) techniques based on reciprocal channel approximation (RCA) for general bit-interleaved coded modulation (BICM) systems. The original RCA-based DE (RCA-DE) technique is implemented under the assumption of binary-input additive white Gaussian noise channels (BI-AWGNCs). In BICM systems, however,$M$-ary modulation schemes are generally used, and they can be regarded as to be a parallel transmission of$\log _{2} M$bits. Thus,$\log _{2} M$separate bit-level channels, which are not Gaussian equivalent, need to be considered. In order to extend the conventional RCA-DE technique to BICM systems, we first establish a model of protograph BICM ensembles. Two methods are developed based on the bit error rate (BER) and the BICM capacity in order to find a corresponding BI-AWGNC that models each of the bit-level channels. Using these methods, we implement the protograph RCA-DE technique for BICM systems and show that it achieves an accurate estimation. As a practical application of the proposed RCA-DE method, we design bit interleavers in order to achieve better BICM performance in the 3GPP New Radio (NR) LDPC coding system. Numerical results show that performance gain of up to 0.3 dB is consistently achieved over a wide range of parameter values.

In the uplink transmission scenario, the base station needs to perform a hypothesis test on the existence of desired packets. However, despite the absence of the desired signal, a false alarm (FA) may occur if the hypothesis test is wrong and the cyclic redundancy check is passed. The FA should be avoided as they may incur system malfunctions or unnecessary resource consumption including buffer contaminations [14]. In this paper, we propose a pre-processing for CW detection to prescreen the FAs by investigating the energy of the received signal. Whereas the conventional solutions to mitigate the FA are basically in-decoder schemes, such as CRC or path-metric-based detection schemes [4], [5], the energy-based detection can be performed prior to the decoding trial. We develop a systematic threshold selection rule based on the finite-length performance of the employed channel code. We show that our energy-based detection scheme outperforms conventional FA mitigation methods for the additive white Gaussian noise channel, and even works efficiently for the Rayleigh fading channel.

Unlike conventional cyclic redundancy check concatenated polar codes, selectively applying the CRC protection only to the crucial information bits (CIBs), namely ‘partial protection’, has an effect of lowering the error floor by reducing the number of low Hamming-weight codewords. In the conventional partial protection scheme, CRC is partially concatenated to the information bits whose corresponding row weight of the generator matrix is minimal. However, we observed that the performance even degrades when the protection range (i.e. related to the number of protected information bits) is low compared to the conventional CRC-concatenated polar codes. Therefore, in this paper, we propose a modified partial protection scheme based on a new CIB selection rule. We not only consider the row weight of the generator matrix, but also utilize the polarization weight which is a tool for assessing the quality of the split-channels of polar codes. Simulation results show that the proposed scheme can recover the weak point of the conventional partial protection scheme, thereby obtaining similar or better error-rate performance over all code parameters compared to the standard concatenation schemes.

Concatenated polar codes under successive cancellation list (SCL) decoding have excellent error-correction performance. However, their expected error-detection capability becomes degraded, when we increase the list size of the SCL decoder in order to improve their error-correction performance. In this paper, we propose a configuration design scheme for the SCL decoder and a post-decoding validation check scheme in order to provide a better tradeoff between error-detection and error-correction performance. Firstly, a configuration of the SCL decoder is designed to improve its own error detection capability. Specifically, a part of dynamic frozen bits (also called parity-check bits) is used for path checking during SCL decoding rather than their original purpose of use, path pruning. Furthermore, the number of paths to be checked by the applied cyclic redundancy check (CRC) code is limited. Secondly, a new metric corresponding to the correlation between the received signal vector and the decoded one is presented to check the validity of the decoding result. These proposed schemes are analyzed to provide a proper configuration of the SCL decoder and determine a threshold for post-decoding validation check. Numerical results show that a better tradeoff between error correction and detection is achieved, compared with conventional schemes.

In blind detection, the user equipment attempts to decode a set of candidate groups to find its own control information. False alarm (FA) refers to an event in which decoding is successful even though a signal is not transmitted, and is one of several critical issues occurring in a blind detection problem. For CRC-aided polar code, with the limited number of CRC bits, FA occurs when the CRC check passes even though there is no signal. In this paper, we propose a technique to efficiently reduce FA events using two detection metrics which are specially suited to low rate and high rate codes. Simulation results show that the application of the proposed DMs outperform the conventional schemes. To be specific, at high rates, the proposed scheme reduces 90% of FA compared to the standard CRC-based detection.

The optimization of joint source and channel coding for a sequence of numerous progressive packets has been a challenging problem. Further, the problem becomes more complicated if the space-time coding is also involved with the optimization in a multiple-input multiple-output (MIMO) system. This is because the number of ways of jointly assigning channel codes and space-time codes to progressive packets is much larger than that of solely assigning channel codes to the packets. To our knowledge, there is no complete and feasible solution for the optimization of joint source, channel, and space-time coding of progressive packets. This paper applies a parametric approach to address such a highly nonlinear optimization problem in MIMO systems. We use the parametric methodology and derive some relevant properties, which are exploited to propose an efficient optimization method where the joint assignment of channel codes and space-time codes to the packets can be optimized in a packet-by-packet manner. As a result, the computational complexity of the proposed method linearly increases in the number of packets, whereas that of the exhaustive search exponentially increases in the number of packets. The numerical results show that the proposed method significantly improves the peak-signal-to-noise ratio performance of the conventional rate-based optimal solution in a MIMO system.

In this paper, we introduce a structural extension method of polar codes as a new code modification method. Structural extension is a systematic method of generating additional codeword bits from the mother code by selecting intermediate bits obtained in the middle of the polar encoding. We start by studying simplex-extension from a 2×2 local polarization kernel, and then, we generalize this method to construct polar codes of arbitrary lengths. This extension method does not change the original polar code structure, and thus, the conventional encoder and decoder can be employed with a slight modification. We present a code construction tool by modifying density evolution to design punctured, shortened, and extended polar codes. By analysis and numerical experiments, we show that the proposed structural extension method enables to achieve an excellent tradeoff between performance and implementation complexity.

In this paper, we propose a new construction of generalized root protograph (GRP) low-density parity-check (LDPC) codes which has a guaranteed diversity order. New hybrid-automatic request with incremental redundancy (H-ARQ-IR) is also proposed to ensure high diversity and rate-compatibility in wireless communication systems, where the GRP LDPC codes are employed along with a method called feedback encoding. The proposed H-ARQ-IR has advantages of low-complexity and near-optimal performance. In order to show its performance behavior, theoretical analysis for the proposed scheme is conducted for the block fading channel. Furthermore, numerical analysis shows that it achieves near maximum diversity order under the belief propagation (BP) decoding with binary phase shift keying (BPSK) modulation and high-order quadrature amplitude modulations (QAMs).

In this paper, we investigate the fundamentals of puncturing and shortening for polar codes, based on binary domination which plays a key role in polar code construction. We first prove that the orders of encoder input bits to be made incapable (by puncturing) or to be shortened are governed by binary domination. In particular, we show that binary domination completely determines incapable or shortened bit patterns for polar codes, and that all the possible incapable or shortened bit patterns can be identified. We then present the patterns of the corresponding encoder output bits to be punctured or fixed, when the incapable or shortened bits are given.

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.

A fractional frequency reuse (FFR) system is an inter-cell interference coordination scheme used in cellular networks. In FFR systems, the available bandwidth is partitioned into orthogonal subbands such that the users near the cell center adopt subbands of a frequency reuse (FR) factor equal to one (i.e., Full FR), and the users near the cell edge adopt the subbands of an FR factor greater than one (i.e., Partial FR). The proper design of Full FR coverage, which is used to distinguish Full FR regions from Partial FR regions, plays a critical role in FFR system performance. This paper studies the optimal Full FR coverage that maximizes system throughput in the downlink in multiple-input multiple-output (MIMO) cellular networks. For MIMO systems, orthogonal space-time block codes are considered. We analytically compare the outage probabilities of Full FR and Partial FR for a given user's location, where the outage probability is evaluated through small-scale multipath fading. By doing so, subject to the constraint that a given target outage probability (quality-of-service) is satisfied, the optimal Full FR coverage is analyzed as a function of base station (BS) power. We prove that the optimal Full FR coverage is a non-increasing function of BS power when the powers of all BSs in the network are scaled up or down at the same rate. This result offers insight into the design of Full FR coverage in relation to BS power; we gain insight into the complicated relationship between crucial FFR design parameters.

The optimization of joint source and channel coding for a sequence of numerous progressive packets is a challenging problem. Further, the problem becomes more complicated if the space- time coding is also involved with the optimization in a multiple-input multiple-output (MIMO) system. This is because the number of ways of jointly assigning channel codes and space-time codes to progressive packets is much larger than that of solely assigning channel codes to the packets. This paper applies a parametric approach to address that complex joint optimization problem in a MIMO system. Employing the parametric distortion-rate function, the joint assignment of channel codes and space-time codes to the packets can be optimized in a packet-by- packet manner. As a result, the computational complexity of the optimization is exponentially reduced, compared to the exhaustive search. The numerical results show that the proposed method significantly improves the peak-signal-to-noise ratio performance of the rate-based optimal solution in a MIMO system.

In this study, the performance of a dual‐hop amplify‐and‐forward relaying system with beamforming is analysed, where only the source and destination are equipped with multiple antennas and both hops are subject to κ – μ fading channels. The κ – μ fading model is a general fading model that can accurately model practical small scale fading in line‐of‐sight environments and accommodates Rician, Nakagami‐ m , and Rayleigh as special cases. New exact analytical expressions on the outage probability (OP), average symbol error rate (SER), and average capacity are derived. Moreover, asymptotic results for the OP, SER, and average capacity are also derived in simpler forms in terms of basic elementary functions which make it easy to understand the system behaviour and the impact of the channel parameters. These analytical results are general and can emulate different symmetric and asymmetric fading scenarios as special cases such as Rician/Rician, Nakagami‐ m /Nakagami‐ m , Rayleigh/Rayleigh, and mixed κ – μ , Rician, Nakagami‐ m , and Rayleigh fading links.

In this paper, the performance of a dual-hop variable-gain amplify-and-forward (AF) relay system with beamforming is analyzed for the recently proposed κ-μ shadowed fading model. The κ - μ shadowed fading model can emulate different types of empirical wireless channels that undergo shadowing, fading, or both and it includes the κ-μ, Rayleigh, Nakagami-m, Rician, and Rician shadowed channels as special cases. We consider that the source and destination are equipped with multiple-antennas and communication occurs through a single-antenna variable-gain relay. First, we derive the new exact analytical expressions for the outage probability (OP) and average capacity, then, we derive the asymptotic results for the OP and average capacity in terms of basic elementary functions to get useful intuition on the impact of the shaping parameters and multiple-antennas on the system performance. These results enable us to explicitly analyze the performance of relaying system under different environments arising from fading and shadowing occurring simultaneously as well as separately. Our results are general so as to be readily reduced to previously published results for classical fading channels as well as new additional ones.

New distributed link scheduling schemes based on a recently proposed device‐to‐device (D2D) communication technology, FlashLinQ are studied. FlashLinQ is an orthogonal frequency division multiplexing‐based synchronous D2D communication system, which achieves a high data rate at longer communication ranges over a licensed spectrum. In this method, some links are selected for data traffic for efficient frequency reuse to avoid interference in D2D links. Where every link is assigned a scheduling priority, so in TX (transmitter) and RX (receiver) yielding, the links which are highly interfered by higher priority links give up communication. However, this technique causes inefficiency in the resource reuse from the cascade yielding problem because link scheduling is performed individually by its RX and TX nodes. To deal with this problem, the authors propose two new link scheduling schemes based on a binary matrix called on‐off interference map (I‐Map), which indicates strong interference between links. In these schemes, each TX generates a binary I‐Map matrix with the collective information from TX and RX blocks. With the common I‐Map matrix that displays inter‐link interference between D2D links, the proposed schemes achieve better performance as compared to the conventional distributed FlashLinQ scheduling scheme.

The effect of imperfect channel state information (CSI) on rate adaptation in time-varying multi-antenna fading channels is studied. In the presence of feedback delay and channel estimation error, we analyze the outage probability (OP), defined as the average probability that the achievable rate in the current channel state is lower than data rate scheduled based on outdated feedback, for maximum ratio combining receivers in single-input multiple-output channels and zero-forcing (ZF) receivers in multiple-input multiple-output (MIMO) channels. In particular, for temporally correlated MIMO channels, the conditional distribution of SNR at the output of ZF detection in the current channel state is unknown; hence we apply a Gaussian approximation to obtain a closed-form expression for the average OP of the MIMO-ZF receiver. Simulation results show that our derivations are well-matched to the actual OP and throughput of multi-antenna rate adaptive systems. Also, based on our analysis results, we propose a simple rate adaptation scheme that maximizes the average throughput under a target OP constraint. The proposed schemes optimize the scheduled rate according to a given CSI condition, and effectively maximize the average outage-constrained throughput.

This paper deals with the randomness of depth-2 connectivity of LDPC ensembles. We study how the randomness of LDPC graphs affect asymptotic performance over binary erasure channel (BEC). First, a new attribute, degree-spectrum distribution, is defined to specify the connectivity of more detailed ensembles than those defined by degree distribution. With this, specified ensembles become subsets of conventional ensemble, and we develop a new density evolution method. Some extreme cases of specified ensembles are given, and we prove that the random specified ensemble is better than other regularized types.

In this paper, we propose a modified iterative pre-whitening projection statistics (MIPPS) method for multi-target detection in non-homogeneous clutters. MIPPS determines and excludes non-homogeneous data samples by iteratively updating a pre-whitening matrix and performing the PS algorithm. Numerical results show that MIPPS improves the average detection probability of weak target when multiple targets with different signal intensities are mixed at low signal-to-clutter ratios.

In this paper, we propose two low-complexity opportunistic user selection schemes in multiple-input multiple-output interference channels (MIMO ICs). First, an opportunistic maximum rate user selection (OMRUS) scheme is proposed. In the OMRUS scheme, a new criterion for user selection which simply approximates the maximum rate of each user is introduced, and by using the proposed selection criterion we achieve as good sum-rate as the conventional schemes with considerably low computational complexity. The OMRUS scheme also has the advantage of extendibility to any number of multiuser ICs though the conventional opportunistic interference aligned user selection (OIAUS) cannot be directly extended to more than three-user case. Second, a modified OIAUS is proposed to improve the sum-rate of the conventional one by modifying the OIAUS criterion to reflect the effects of both the desired signal power and the degree of interference alignment. Mathematical and numerical results show that the proposed user selection schemes both have low computational complexity, which is comparable with the conventional OIAUS, and improve the sum-rate compared with the conventional ones.

In this paper, we introduce new attributes of low-density parity-check graphs, degree-set and degree-sum, which explains the connectivity of a check node with more detail. Then, we consider more specified ensembles defined by degree-set/sum distribution of the graph than one defined by the degree distribution. As the degree set/sum distribution varies, tradeoff between the performance at the waterfall and that at the error-floor is observed. The trade-off point can be managed by controlling degree-set/sum distribution.

In this paper, we analyze the effects of imperfect channel state information (CSI) on the outage performance of linear zero-forcing (ZF) receiver in time-varying multiple-input multiple-output (MIMO) fading channels. Accurate CSI is an essential condition to improve the overall performance of the rate-adaptive MIMO system. However, acquiring perfect CSI at transceivers is impossible due to feedback delay and channel estimation error. To investigate imperfect CSI environments, therefore, the outage probability is approximated by deriving the probability density function of the output signal-to-noise ratio (SNR) of the ZF receiver, based on temporal MIMO channel correlation. Since the exact distribution of the ZF-output SNR is yet unknown, we apply a Gaussian approximation to obtain mathematical expressions for the outage probability with the assumption of a square MIMO channel. Simulation results shows that our approximation is close to the actual outage probability.

In this paper, we provides a coding theoretic construction of DNA codes. Previously, some works have been carried out on DNA codes with biologically motivated constraints such as minimum Hamming distance and constant GC-content. Therefore, for given code-length N, the number of GC-content w, and minimum hamming distance d, it is interesting to construct DNA codes with maximum size A4GC(N, w, d). In the previous works, the DNA codes from the quaternary constant weight codes have been proposed [5]. In this paper, we propose another approach based on the binary constant weight codes, not quaternary ones. It is found that the size of the new DNA codes from binary constant weight codes is greater than or equal to that from the quaternary ones. First a general approach to constructing DNA codes from a binary constant weight code is proposed. Second, a specific DNA code with parameters (2n- 1, 2n-1, 2n-1) from binary sequences with ideal autocorrelation property is constructed.

In this paper, a new generation method of quaternary sequences of period 2(2n-1) with ideal autocorrelation and balance property is proposed using the binary sequences of period 2n- 1 with ideal autocorrelation and reverse Gray mapping. The autocorrelation distribution of the proposed quaternary sequences is also derived.

In this paper, for an odd prime p, new quaternary sequences of even period 2p with ideal autocorrelation property are constructed using the Legendre sequences of period p. The distribution of autocorrelation function of the proposed quaternary sequences is also derived.

We propose a new construction of quaternary sequences using the reverse Gray mapping of a pair of binary Sidel'nikov sequences. The proposed construction provides sequences of even period N with the maximum nontrivial auto-correlation magnitude, Rmax= 2. For N ≡ 0 mod 4, the new quaternary sequences have the optimal Rmax= 2 and are almost-balanced in contrast to the only earlier optimal construction Sj[1].

In this paper, a new criterion for reordering of low-density parity-check (LDPC) coded orthogonal frequency division multiplexing (OFDM) subframes is proposed for type I hybrid automatic repeat request (H-ARQ) systems. It is verified from numerical analysis that a subframe reordering pattern having larger channel capacity shows better bit error rate (BER). Also, it is shown that the subframe reordering pattern achieving equal combined power allocation for each subframe maximizes the channel capacity and outperforms other subframe reordering patterns in terms of BER performance. Simulation results are provided to confirm that for a very slow varying fading channel, the proposed subframe reordering scheme for achieving equal combined power allocation gives better BER performance than the conventional Chase combining scheme without increasing the decoding complexity.

In this paper, a new demapper generating log-likelihood ratio (LLR) is proposed by using a linear approximation for the nonlinear factor of an exact LLR. The exact LLR is sufficient for the probability based decoding, but its calculation requires a large number of computations in the case of high order modulations such as 16 quadrature amplitude modulation (QAM) and 64QAM. To alleviate the computational complexity a piecewise-linear demapper was proposed by neglecting the nonlinear factor of the exact LLR. However, it is observed that the throughput performance of the piecewise-linear demapper in hybrid automatic repeat request (HARQ) system is deficient in low signal-to-noise ratio region. Therefore, the new demapper is proposed which has an equivalent throughput performance to the exact LLR in HARQ system, and at the same time, only needs a few elementary operations for calculating the simplified LLRs. Experimental evidences which show the viability of the proposed demapper are also provided.

In this paper, given a composite integer n, we propose a method of constructing quaternary low correlation zone (LCZ) sequences of period 2n$1 from binary sequences of the same length with ideal autocorrelation. These new sequences are optimal with respect to the bound by Tang, Fan, and Matsufuji. The correlation distributions of these new quaternary LCZ sequences constructed from m-sequences and GMW sequences are derived

In this paper, given a composite integer n, we propose a method of constructing quaternary low correlation zone (LCZ) sequences of period 2/sup n/-1 from binary sequences of the same length with ideal autocorrelation. These new sequences are optimal with respect to the bound by Tang, Fan, and Matsufuji. The correlation distributions of these new quaternary LCZ sequences constructed from m-sequences and Gordon-Mills-Welch (GMW) sequences are derived.

For a prime power q, we show that a cyclic relative difference set with parameters (q/sup n/-1/q-1,q-1,q/sup n-1/,q/sup n-2/) can be constructed from a d-homogeneous function from F/sub q//sup n//spl bsol/{0} onto F/sub q/ with difference-balanced property, where F/sub q//sup n/ is the finite field with q/sup n/ elements. This construction method enables us to construct several new cyclic relative difference sets with parameters (p/sup n/-1/p/sup l/-1,p/sup l/-1,p/sup n-l/,p/sup n-2l/) from p-ary sequences of period p/sup n/-1 with ideal autocorrelation property introduced by Helleseth and Gong. Using a lifting idea, other new cyclic relative difference sets can be constructed from the Helleseth-Gong (HG) sequences. Also, the 3-ranks and the trace representation of the characteristic sequences of cyclic relative difference sets from a specific class of ternary HG sequences and ternary Lin sequences are derived.

In this article, the linear complexity over F/sub p/ of Lempel-Cohn-Eastman (1977) sequences of period p/sup m/-1 for an odd prime p is determined. For p=3,5, and 7, the exact closed-form expressions for the linear complexity over F/sub p/ of LCE sequences of period p/sup m/-1 are derived. Further, the trace representations for LCE sequences of period p/sup m/-1 for p=3 and 5 are found by computing the values of all Fourier coefficients in F/sub p/ for the sequences.

For a positive integer, n, new families, S and U, of binary sequences of period 2/sup n/-1 with low correlations are proposed, where for some positive integer, e, S is defined for odd n/e and U for even n/e. The family S has four-valued correlations and is a generalization of the family of Gold-like sequences introduced by S. Boztas and P.V. Kumar (see ibid., vol.40, p.532-7, 1994). The family U, which is also a generalization of the sequence family defined by P. Udaya ("Polyphase and frequency hopping sequences obtained from finite rings", Ph.D. dissertation, Dept. Elec. Eng., Indian Inst. Technol., Kanpur, 1992), has six-valued correlations. The relationship between Gold-like sequences and Gold sequences is the same as the relationship between the family S and the family constructed from the binary sequences partially contributed by R. Gold (see ibid., vol.IT-14, p.154-6, 1968), T. Kasami (see Coordinated Sci. Lab., Univ. of Illinois,Urbana-Champaign, Tech. Rep. R-285, AD 632574, 1966), and Welch. Using a lifting idea (No, J.-S. and Kumar, P.V., ibid., vol.35, p.371-9, 1989) for the families S and U, families of binary sequences with the same correlation distributions and large linear span are also constructed.