Neural networks are shown to be a viable implementation for joint channel equalisation and symbol detection in a vehicular network. Experimental results using a hardware-in-the-loop approach at 5.9GHz validate the efficacy of the proposed implementation following the 802.11p parameters using orthogonal frequency division multiplexing (OFDM). Further results are obtained using a more spectrally efficient waveform, namely spectrally efficient frequency division multiplexing (SEFDM), to show a trade-off between loss of orthogonality, and therefore bit-error rate (BER) performance, versus increased spectral efficiency to enable higher data rates or the ability to service more users. SEFDM is tested with compression factors ranging from 20% up to 60% bandwidth compression. The results show the neural network is able to achieve an acceptable BER performance in a highway non-line-of-sight (NLOS) channel which is a well established harsh and dynamic vehicular channel. This is further validated via measurements of the error vector magnitude.

In this paper, a low-complexity cell-edge-aware Antenna Selection (AS) algorithm is proposed for a Multi-User (MU) Massive Multiple-Input Multiple-Output (M-MIMO) downlink system with Matched Filter (MF) precoding. We assume that the users are uniformly distributed in the cell, and therefore, have different Signal-to-Interference plus Noise Ratios (SINRs). At each iteration, the proposed algorithm selects one antenna to reduce the highest interference term between any two users to its minimum value. Furthermore, we utilize a Max-Min Power Allocation (MMPA) scheme to further enhance the performance of cell-edge users and achieve higher fairness. In addition, the complexity of the proposed AS algorithm is evaluated in terms of number of floating-point operations (FLOPs) required for its implementation. Finally, our proposed AS method is compared with other low-complexity AS schemes found in the literature and shown to demonstrate an impressive performance-complexity trade-off.

In this study, the performance analyses of the proposed turbo‐coded orthogonal frequency division multiplexing (T‐COFDM) are investigated over the power‐line communication with lognormal channel gain based on derived effective complex‐valued ratio distributions of the individual and combined noise samples at the zero‐forcing equaliser output. The effective noise samples are derived in the presence of Nakagami‐m background interference (BI) noise, Middleton class A impulsive noise (MCAIN) and their combination. The performance of the turbo code has been improved by computing the exact log‐likelihood ratio using derived distributions, with the derivation of pairwise error probability and the average upper‐bounds (AUBs). Moreover, the bit error rate (BER) degradation in the conventional T‐COFDM system has been improved by deriving two clipping thresholds to combat the effect of the non‐Gaussian noise, the first one has been derived in the presence of the impulsive noise only modelled by MCAIN model and the second one in the presence of combined Nakagami‐m BI noise and MCAIN model. Monte Carlo simulations demonstrate the significant BER improvements of the proposed T‐COFDM system compared to the improved conventional T‐COFDM system with a close agreement to the AUBs derivation and analytical BER expression.

This study proposes a novel physical layer authentication scheme, which uses the channel to generate a tagged signal and determine random partial padding. The scheme utilises the random wireless channel gain between communication entities to generate tag and decide a padding sequence for each symbol. Simulations for different padding percentages using the randomness provided by the channel are carried out to compare against a traditional full padding scheme, which shows improvement in error rate under the same security performance. The second layer of referee verification is introduced to increase the difficulty of compromising the authenticity of the scheme. A mathematical analysis is carried out to find an optimal size of selected time slots for the authentication scheme is also discussed.

Massive Multiple-Input Multiple-Output (MIMO) systems can significantly improve the system performance and capacity by using a large number of antenna elements at the base station (BS). However, having a massive number of radio-frequency (RF) chains at the BS can be costly and energy inefficient. One way to achieve the diversity gain of massive MIMO systems is to employ a massive number of antennas with limited number of RF chains. Thus, antenna selection techniques can be applied to reduce the system complexity and hardware cost. In this paper, a Quantum-inspired Tabu Search (QTS) algorithm is applied to antenna selection in Massive MIMO systems and compared with two well known algorithms; namely, a Classical Tabu Search (CTS) algorithm and a Genetic Algorithm (GA). The QTS algorithm has a great advantage over CTS, since it only requires finding the optimum rotation angle to evolve the system towards a better solution. In contrast, in CTS, the dimensions of the tabu matrix are dynamic and need to be optimized. Moreover, to achieve maximum performance, these dimensions need to be reconfigured when changing the number of antennas or the number of iterations, while no such a problem occurs in the QTS. The QTS algorithm also shows better results in terms of the system capacity compared to CTS and GA. Furthermore, the classical and quantum inspired TS algorithms require much lower complexity than the GA.

Algebraic-geometric (AG) codes have good error-correction capability due to their generally large code word length. However, their decoding remains complex, preventing practical applications. Addressing the challenge, this paper proposes two interpolation-based low-complexity Chase (LCC) decoding algorithms for one of the most popular AG codes-Hermitian codes. By choosing η unreliable symbols and realizing them with the two most likely decisions, 2ηdecoding test-vectors can be formulated. The first LCC algorithm performs interpolation for the common elements of the test-vectors, producing an intermediate outcome that will be shared by the uncommon element interpolation. It eliminates the redundant computation for decoding each test-vector, resulting in a low-complexity. With an interpolation multiplicity of one, the decoding is further facilitated by removing the requirement of pre-calculating the Hermitian curve's corresponding coefficients. The second LCC algorithm is an adaptive variant of the first algorithm, where the number of test-vectors is determined by the reliability of received information. When the channel condition improves, it can reduce the complexity without compromising the decoding performance. Simulation results show that the both LCC algorithms outperform a number of existing algebraic decoding algorithms for Hermitian codes. Finally, our complexity analysis will reveal the proposals' low-complexity feature.

We discuss the design rules of an energy-efficient wireless wiretap channel in this paper. On the transmitter side, we investigate the optimal power control policy for secrecy rate maximization over wiretap channels with the bit-interleaved coded modulation scheme. On the receiver side, an energy harvesting algorithm is used to collect wireless signal energy without degrading the secrecy rate performance. These objectives are challenging as the closed-form solution to the mutual information of finite-alphabet input schemes remains unknown. In this paper, we derive a closed-form relationship between the secrecy rate and the signal-to-noise ratio (SNR) by transforming the SNR from the linear domain to the logarithm domain. The optimal power control policy (PCP) can be easily obtained by exhaustive search in a small interval, whereas the traditional search is performed over the entire SNR range. We also propose a sub-optimal PCP algorithm that significantly reduces the search complexity with only a minor performance loss. The optimal power splitting ratio is studied to save energy while achieving the target secrecy rate. We show that if the transmission power is too high, the receiver is unable to simultaneously harvest energy from the wireless signals and achieve the target secrecy rate.

In this study, the performance of irregular low‐density parity check (LDPC) coded orthogonal frequency division multiplexing (COFDM) utilising 4096 quadrature amplitude modulation (4096‐QAM) is investigated over multipath power‐line communication (PLC) channel. The effective complex‐valued ratio distributions of the noise samples at the zero‐forcing equaliser output considering both frequency‐selective multipath PLCs, background and impulsive noise are derived, in addition to the condition for optimum detection of 4096‐QAM and the bit error rate (BER). Moreover, the performance of the LDPC decoder is improved by computing the log‐likelihood ratios (LLRs) required for soft decoding based on the derived probability density functions. Numerical results obtained using the newly derived LLRs demonstrate a significant performance improvement compared to the conventional receiver that uses blanking impulsive noise mitigation method and LLR computed based on the Gaussian distribution. Furthermore, EXtrinsic Information Transfer chart analysis demonstrates that the proposed approach requires fewer iterations for convergence compared to the conventional receiver. Finally, utilising channel bandwidth of 22.4 MHz, the proposed system offers an improvement of 111 Mbps over the conventional system to reach a maximum data throughput of 256 Mbps for a signal‐to‐noise ratio of 39 dB and BER of .

Spatial diversity is an effective method to mitigate the effects of fading, and when used in conjunction with low-density parity-check (LDPC) codes, it can achieve excellent error-correcting performance. Noise added at each branch of the diversity combiner is generally assumed to be additive white Gaussian noise, but there are many applications where the received signal is impaired by noise with a non-Gaussian distribution. In this paper, we derive the exact bit-error probability of different linear combining techniques on Rayleigh fading channels with impulsive noise, which is modeled using symmetric alpha-stable distributions. The relationship for the signal-to-noise ratios of these linear combiners is derived and then different non-linear detectors are presented. A detector based on the bi-parameter Cauchy-Gaussian mixture model is used and shows near-optimal performance with a significant reduction in complexity when compared with the optimal detector. Furthermore, the threshold signal-to-noise ratio of LDPC codes for different combining techniques on these channels is derived using density evolution and an estimation of the waterfall performance of LDPC codes is derived that reduces the gap between simulated and asymptotic performance.

This paper proposes an interpolation based progressive algebraic Chase decoding (PACD) algorithm for Reed-Solomon (RS) codes. Based on the received information, 2η (η > 0) interpolation test-vectors are constructed. They are ordered using a reliability function, assessing their potential of yielding the intended message. The decoding is performed progressively granting priority to decode the test-vectors that are more likely to yield the intended message, and it will be terminated once the intended message is found. In the proposal, the decoding of a later test-vector utilizes the interpolation information that is generated during the decoding of the earlier ones. It results in the binary tree that represents the evolution of the interpolated polynomial sets growing in a depth-first-search manner. The PACD algorithm has the advantage of adapting its decoding computation to the channel condition, leveraging the average decoding complexity. This channel dependent feature will be validated by our simulation results which show that the PACD algorithm is less complex than various interpolation based algebraic decoding algorithms. We will also demonstrate that it can achieve a high RS decoding performance.

Algebraic-geometric (AG) codes have long been considered as a possible candidate to replace Reed-Solomon (RS) codes. However, their decoding remains complex and infeasible to implement. Addressing this challenge, our paper proposes a low-complexity Chase (LCC) decoding algorithm for the most popular class of AG codes - Hermitian codes. The LCC decoding is realised by formulating decoding test-vectors, which allows Koetter's interpolation to be performed for common and uncommon elements. This reduces redundant computations and also removes the need to calculate the corresponding coefficients of a Hermitian curve, thus facilitating message recovery. Our simulation results show that significant coding gains can be achieved over the conventional Koetter-Vardy (KV) soft decoding algorithm, but with a much lower computational cost. Moreover, we also show that in comparison with RS codes of a similar length, Chase decoding has a more significant impact on enhancing the performance of Hermitian codes.

This study proposes a progressive algebraic Chase decoding (PACD) algorithm for Reed–Solomon (RS) codes. On the basis of the received information, 2 η ( η > 0) interpolation test‐vectors are constructed for the interpolation‐based algebraic Chase decoding. A test‐vector reliability function is defined to assess their potential for yielding the intended message. The algebraic Chase decoding will then be performed progressively granting priority to decode the test‐vectors that are more likely to yield the message, and is then terminated once it is found. Consequently, the decoding complexity can be adapted to the quality of the received information. An enhanced‐PACD (E‐PACD) algorithm is further proposed by coupling the PACD algorithm with the adaptive belief propagation (ABP) decoding. The ABP decoding generates new test‐vectors for the PACD algorithm by enhancing the received information. It improves the Chase decoding performance without increasing the decoding complexity exponentially. It is shown that the E‐PACD algorithm's complexity can be significantly reduced by utilising the existing interpolation information of the previous Chase decodings’. Our performance evaluations show that the two proposed decoders outperform a number of existing algebraic decoding approaches. Complexity and memory analyses of the PACD algorithm are also presented, demonstrating that this is an efficient RS decoding strategy.

This paper investigates secrecy rate optimization problems for a multiple-input-single-output (MISO) secrecy channel in the presence of multiple multiantenna eavesdroppers. Specifically, we consider power minimization and secrecy rate maximization problems for this secrecy network. First, we formulate the power minimization problem based on the assumption that the legitimate transmitter has perfect channel state information (CSI) of the legitimate user and the eavesdroppers, where this problem can be reformulated into a second-order cone program (SOCP). In addition, we provide a closed-form solution of transmit beamforming for the scenario of an eavesdropper. Next, we consider robust secrecy rate optimization problems by incorporating two probabilistic channel uncertainties with CSI feedback. By exploiting the Bernstein-type inequality and S-Procedure to convert the probabilistic secrecy rate constraint into the determined constraint, we formulate this secrecy rate optimization problem into a convex optimization framework. Furthermore, we provide analyses to show the optimal transmit covariance matrix is rank-one for the proposed schemes. Numerical results are provided to validate the performance of these two conservative approximation methods, where it is shown that the Bernstein-type inequality-based approach outperforms the S-Procedure approach in terms of the achievable secrecy rates.

Cognitive Radio (CR) technology enables unlicensed users to opportunistically use the vacant spectrum bands assigned to licensed users, thereby enhancing the spectrum utilization. In the last decade, Cognitive Radio Networks (CRNs) have been well studied and many important works have been proposed. However, the broadcast problem, which is one of the most fundamental operations in CRNs, has not been well studied. In this paper, a distributed reliable Cognitive Radio Broadcast Protocol (CRBP) for cognitive radio ad hoc networks is proposed that makes the following contributions: (i) reliable data dissemination, (ii) joint transmitter-receiver channel selection, (iii) protection of primary users' communication and (iv) coordinating the broadcast process without the need for a common channel. A key novelty of the proposed CRBP is the formulation of the broadcast problem from the viewpoint of connecting different local topologies, which is a unique feature in cognitive radio networks. We jointly map the network topologies and the spectrum observations as a bipartite graph which allows the channel selection undertaken at each node to capture the spectrum information and the environmental topologies of all the neighbouring nodes.

This paper proposes an alternating optimization algorithm for addressing the secrecy rate optimization problem for a multi-input-multi- output (MIMO) secrecy channel in the presence of a multiantenna eavesdropper, where a multiantenna cooperative jammer will be employed to confuse the eavesdropper by introducing jamming signal. We investigate the secrecy rate maximization problem, which is a non-convex problem in terms of transmit covariance matrices of the legitimate transmitter and the cooperative jammer. In order to circumvent this issue, we develop an optimization algorithm by alternating optimizing the transmit covariance matrices of the legitimate transmitter and the cooperative jammer where each transmit covariance matrix is optimized while other is fixed. Based on this algorithm, we develop a robust scheme by incorporating channel uncertainties associated with the eavesdropper. By exploiting S-Procedure, we show that these robust optimization problems can be formulated into semidefinite programming (SDP). Simulation results have been provided to validate the convergence and the performance of the alternating algorithm.

This paper investigates robust beamforming techniques for a multiple-input-single-output (MISO) secrecy transmission with a cooperative jammer by incorporating two different types of channel uncertainties. We solve the worst-case signal-to-interference-plus-noise ratio (SINR) maximization of the legitimate user with the worst-case SINR constraint of the eavesdropper and the transmit power constraint. The original problems are not convex in terms of transmit covariance matrices, and cannot be solved directly. Thus, we present two approaches to convert these problems into semidefinite programmings (SDPs) by exploiting S-Procedure and deriving the corresponding Lagrangian dual problem. Numerical results are provided to validate the performance of the proposed robust schemes.

In this paper, a new receiver structure is proposed for uplink interleaved division multiple access (IDMA) on multipath fading channels. In a conventional IDMA rake detector, jointly removing inter symbol interference (ISI) and multiple access interference (MAI) is achieved by exchanging extrinsic log-likelihood ratio (LLR) chips between an elementary signal estimator (ESE) and a posteriori probability decoders (DEC)s in a turbo-like manner. The same exchanging principle takes place between a centralized decision feedback equalizer (CDFE) and the DECs in CDFE-IDMA systems. However, the proposed IDMA receiver can be considered a mixture between the two mentioned receivers as it employs an adaptive DFE for each user to remove the ISI effects while MAI is eliminated by a parallel interference canceller (PIC). The PIC utilizes the same ESE principles in removing MAI effects from received symbols which is more efficient than cross-over filters in a CDFE-IDMA system. Moreover, the ISI abstraction in DFE is more active in removing ISI than ESE. Simulation results demonstrate the superiority of DFE-IDMA over the other systems' performances found in the literature for both optimal and adaptive algorithms (AA).

Traditionally, Reed-Solomon (RS) codes have been employed in magnetic data storage devices due to their effectiveness in correcting random errors and burst errors caused by thermal asperities and inter-symbol interference (ISI). However, as storage densities increase the effect of ISI becomes more severe and much longer RS codes are needed, but this requires significantly increasing the size of the finite field. A possible replacement for RS codes are the one-point Hermitian codes, which are a class of algebraic-geometric (AG) code that have larger block sizes and minimum Hamming distances over the same finite field. In this paper, we present a novel iterative soft detection-decoding algorithm for interleaved Hermitian codes. The soft decoding employs a joint adaptive belief propagation (ABP) algorithm and Koetter-Vardy (KV) list decoding algorithm. It is combined with a maximum a posteriori (MAP) partial response (PR) equalizer and likelihoods from the output of the KV or the ABP algorithm are fed back to the equalizer. The proposed scheme's iterative detection-decoding behavior will be analyzed by utilizing the Extrinsic Information Transfer (ExIT) chart. Our simulation results demonstrate the performance gains achieved by iterations and Hermitian codes' performance advantage over RS codes.

In this letter, a Sum-Product algorithm (SPA) utilizing soft distances is shown to be more resilient to impulsive noise than conventional likelihood-based SPAs, when the noise distribution is unknown. An efficient version of the soft distance SPA is also developed but with half the storage requirements and running time.

Two adaptive receivers for jointly detecting active users in an interleave division multiple access (IDMA) system are considered for highly dispersive underwater acoustic channels (UACs) using a continuous pilot approach. A direct adaptive interference cancellation (IC) IDMA receiver is proposed and compared with the standard Rake-IDMA receiver that performs adaptive semi-blind channel estimation developed by the authors. Both iterative decoding receivers incorporate a phase locked loop (PLL) and are optimized based on the minimum mean square error (MMSE) criterion. The theoretical basis of both receivers is presented along with experimental results obtained by processing data from actual underwater communication experiments. The transmission results of 3 active users at a data rate of 441.3 b/s per user within 4 kHz bandwidth demonstrate that the IC-IDMA receiver has better performance and significantly mitigates the bit errors associated with Rake-based IDMA receiver.

This paper proposes the first complete soft-decision list decoding algorithm for Hermitian codes based on the Koetter-Vardy's Reed-Solomon code decoding algorithm. For Hermitian codes, interpolation processes trivariate polynomials which are defined over the pole basis of a Hermitian curve. In this paper, the interpolated zero condition of a trivariate polynomial with respect to a multiplicity matrix M is redefined followed by a proof of the validity of the soft-decision scheme. This paper also introduces a new stopping criterion for the algorithm that tranforms the reliability matrix Pi to the multiplicity matrix M. Geometric characterisation of the trivariate monomial decoding region is investigated, resulting in an asymptotic optimal performance bound for the soft-decision decoder. By defining the weighted degree upper bound of the interpolated polynomial, two complexity reducing modifications are introduced for the soft-decision scheme: elimination of unnecessary interpolated polynomials and pre-calculation of the coefficients that relate the pole basis monomials to the zero basis functions of a Hermitian curve. Our simulation results and analyses show that soft-decision list decoding of Hermitian code can outperform Koetter-Vardy decoding of Reed-Solomon code which is defined in a larger finite field, but with less decoding complexity.

List decoding Hermitian codes using the Guruswami-Sudan (GS) algorithm can correct errors beyond half the designed minimum distance. It consists of two processes: interpolation and factorisation. By first defining a Hermitian curve, these processes can be implemented with an iterative polynomial construction algorithm and a recursive coefficient search algorithm respectively. To improve the efficiency of list decoding Hermitian codes, this paper presents two contributions to reduce the interpolation complexity. First, in order to simplify the calculation of a polynomialiquests zero condition during the iterative interpolation, we propose an algorithm to determine the corresponding coefficients between the pole basis monomials and zero basis functions of a Hermitian curve. Second, we propose a modified complexity reducing interpolation algorithm. This scheme identifies any unnecessary polynomials during iterations and eliminates them to improve the interpolation efficiency. Due to the above complexity reducing modifications, list decoding long Hermitian codes with higher interpolation multiplicity becomes feasible. This paper shows list decoding algorithm can achieve significant coding gain over the conventional unique decoding algorithm.

The list decoding algorithm can outperform the conventional unique decoding algorithm by producing a list of candidate decoded messages. An efficient list decoding algorithm for algebraic-geometric (AG) codes and Reed-Solomon (RS) codes has been developed by Guruswami and Sudan, called the Guruswami-Sudan (GS) algorithm. The algorithm includes two steps: Interpolation and Factorisation. To implement interpolation, Koetter proposed an iterative polynomial construction algorithm for RS codes. By redefining a polynomial over algebraic function fields, Koetter's algorithm can also be applied to AG codes. To implement factorisation, Roth and Ruckenstein proposed an efficient algorithm for RS codes and later Wu and Siegel extended it to AG codes. Following on from their previous work, we propose a more general factorisation algorithm which can be applied to both AG and RS codes. This algorithm avoids rational function quotient calculations required by Wu and SiegePs algorithm, making it more efficient to implement. As well as employing this algorithm to list decode AG and RS codes this paper also presents the first simulation results evaluating the list decoding performance comparison between AG and RS codes of a similar code rate defined over the same finite field.