This paper focuses on one of the key enabling technology that will compose future 5G network, the Direct-LTE communication underlying a cellular infrastructure, also commonly known as Device-to-Device (D2D). Energy efficiency algorithms are proposed for the communication between D2D users and cellular users (CUs) and, following the Lagrangian duality theory, an optimal power and rate control solution is given for D2D users, while satisfying the interference limits related to CUs. Finally, the new algorithm is used to achieve proportional fairness between D2D users and CUs and to show with numerical results that the interference to CUs can be limited to always be under a predefined threshold.

In this study, the authors discuss relay selection schemes with the objective to minimise outage probability for a network consisting of a single source, multiple relays and a single destination. The relays are powered by radio frequency signals from the source. For a successful transmission, at least one of the relay nodes should be able to decode the source signals and have enough energy to relay the information to the destination. The authors assume that a relay node cannot decode information and harvest energy from the source signals simultaneously. The authors formulate an optimisation problem to minimise outage probability for the system. The relay selection scheme and the outage performance depend on the availability of the channel state information (CSI) on the source-relay and the relay-destination links. Based on the availability of the CSI on the relay-destination link, the authors propose relay selection schemes for different scenarios and evaluate the performance numerically. The results show that the availability of the CSI on the relay-destination link at the relay node helps to improve the outage performance considerably. The authors characterise the outage probability for the schemes analytically; and numerically compute the optimal number of relays which provide the optimal outage performance for a given scheme.

In this study, the authors investigate the impact of channel estimation error (CEE) on the performance of a multiple-input–multiple-output (MIMO) two-way relay system under Rayleigh fading. Herein, transmit/receive zero-forcing (ZF) is employed at the two source nodes, whereas analogue network coding is used at the relay node. Fundamentally, for making use of transmit/receive ZF, all nodes must be aware of channel state information (CSI). As perfect CSI may not always be available in practical scenarios, the CEE does exist in the considered system. By taking the imperfect CSI into account, they enucleate that the residual self-interference and additional noise pertaining to the CEE have effect of reducing end-to-end signal-to-noise ratios (SNRs) at the two source nodes. Based on the statistical characterisations of these post-processing SNRs, they carry out the overall system outage probability analysis. Further, they investigate the asymptotic outage behaviour to deduce the achievable diversity order. They substantiate that the diversity order may reduce to zero under severe impact of CEE. In addition, they derive a closed-form expression of ergodic sum-rate of the considered system with CEE. Numerical and simulation investigations are conducted to support all the theoretical findings using various values of CEE and antenna configurations.

A hierarchy precoding approach is proposed in this study for multi-cell multiuser systems with any number of base stations and that of users, which is suitable for any number of data streams. The key feature of this approach is aligning the inter-user interferences within the same cell to the room spanned by the inter-cell interferences, by which both the inter-cell and inter-user interferences are cancelled simultaneously. Then, the inter-stream interference for each user can be easily tackled. It is found that the interference alignment-based hierarchy precoder achieves to the full freedom of degree. With interference-free transmissions achieved by the proposed precoder, the transmit power is optimised in an analytical expression by maximising the sum rate and minimising the sum weighted mean square error. Extensive simulations demonstrate the effectiveness of the proposed method.

The authors propose entropy minimisation-based matching pursuit algorithm which has the capability to reject noise even when the noise level is comparable to the signal level. The proposed algorithm can cater to compressible signals and sparse signals with unknown sparsity.

In this study, a group of wireless sensors are tasked to trace indoor obstacles without the need to sense them, directly. The authors introduce a novel framework based on compressed sensing theory that allows sensors to map two-dimensional spatial details, non-invasively. By exploiting an alternative projection method which reduces the randomness nature of previous works, the resulting measurement matrix can provide linear samples from an unknown environment more efficiently. It is shown that how sparse representation of the spatial parameters in some domains can be utilised in order to realise obstacle mapping with minimum number of wireless transmissions and receptions. In addition, theoretical analyses along with simulation results illustrate premier performance of their framework. Furthermore, they test their method in different circumstances and show how drawbacks such as walls, bulkheads, and environmental constraints can affect the reconstruction performance. Therefore, they proposed two algorithms (i.e. reducing wall effect and reducing bulkhead effect) in order to decrease the impression of walls and bulkheads which is supported theoretically. Finally, a well-applicable scenario based on their framework is defined and proposing the next best transmitter algorithm remarkable results are achieved.

This study proposes an iterative method to approximate an N-dimensional optimisation problem with a weighted Lp norm and L2 norm objective function by a sequence of N independent one-dimensional optimisation problems. This iterative method is inspired by the existing weighted L1 norm and L2 norm separable surrogate functional (SSF) iterative shrinkage algorithm. However, as these independent one-dimensional optimisation problems consist of weighted Lp norm and L2 norm objective functions, these optimisation problems are non-convex and they may have more than one locally optimal solutions. In general, it is very difficult to find their globally optimal solutions. To address this difficulty, this study proposes to partition the feasible set of each approximated problem into various regions such that the sign of the convexity of the objective function in each region remains unchanged. In this case, there is no more than one stationary point in each region. By finding the stationary point in each region, the globally optimal solution of each approximated optimisation problem can be found. Besides, this study also shows that the sequence of the globally optimal solutions of the approximated problems converge to the globally optimal solution of the original optimisation problem.

This study deals with a bit error rate (BER) floor performance analysis for orthogonal frequency division multiplexing (OFDM) systems using pilot-aided channel estimation with polynomial interpolations. Such a performance analysis has been previously undertaken in the literature, but is limited to binary phase shift keying and 4-quadrature amplitude modulation (4-QAM) constellations. The main contribution of this study is then to analyse the BER floor achieved by a 16-QAM OFDM signal in a Rayleigh channel. To achieve this, the binary error probability is obtained by carrying out the analysis on maximum significant bits (MSB) and least significant bits (LSB). The MSB leads to the similar results as those obtained in 4-QAM, but very specific developments are required to obtain the error probability of the LSB. Numerical results show that the proposed BER performance analysis is valid for the 16-QAM constellation.

This study presents a high-performance audio watermarking scheme using spread spectrum modulation. Unlike conventional extractors which use simple correlation, this watermarking scheme exploits the perceptual characteristic of the watermarked audio before correlation. It is noted that although the watermark extractor works blindly neither which the original audio signal nor the embedded watermark signal is available, however, the spectral power structure of embedded watermark can be estimated using perceptual analysis methods. With this information, the watermark performance is improved by introducing an estimation-equalisation-correlation based extraction mechanism. The pre-equaliser at the extractor is carefully designed to obtain optimised extraction performance. Moreover, the perceptual analysis and shaping method are improved to make sure the watermark estimation is accurate. The perceptual characteristic aware extraction-based watermarking scheme achieves high embedding capacity up to 43 bps/channels, with low perceptual distortion to the host audio. Experiments on real audio signals show that the proposed watermarking scheme achieves high performance and is robust against various types of attacks.

Worldwide interoperability for microwave access (WiMAX) is a wireless broadband technology, which supports point to multi-point (PMP) broadband wireless access. WiMAX is basically a new shorthand term for IEEE Standard 802.16. This standard determines the air interface, including the medium access control layer and physical layer (PHY), of consolidated fixed and mobile point to-multipoint broadband wireless access frameworks offering numerous services. WiMAX PHY incorporates orthogonal frequency division multiplexing/orthogonal frequency division multiple access (OFDM/OFDMA) as the modulation technique in uplink as well as downlink. Hence, this study addresses OFDMA basics, OFDMA frame structure, OFDMA symbol, OFDMA PHY as per IEEE 802.16e-2009 standard. It also explains OFDMA time-division duplexing frame which consists of partial usage of subchannels and adaptive modulation and coding zones in the downlink from base station to two mobile stations (MS). The author analysed the system performance by reconfiguring different channels such as additive white Gaussian noise (AWGN), flat fading channel and multipath fading or frequency-selective channels. The impact of each channel on received signals (MS 1 and MS 2) is shown in figures and the corresponding values are noted in a table.

Kernel density estimation (KDE) is widely-used for non-parametric estimation of an underlying density from data. The performance of KDE is mainly dependent on the bandwidth parameter of the kernel. This study presents an alternative method of estimating the bandwidth by incorporating sparsity priors in the Fourier transform domain. By using cross-validation (CV) together with an l ₁ constraint, the proposed method significantly reduces the under-smoothing effect of traditional CV methods. A solution for all free parameters in the minimisation is proposed, such that the algorithm does not need any additional parameter tuning. Simulation results indicate that the new approach is able to outperform classical and more recent approaches over a set of distributions of interest.

It is a well-known property in X-band maritime surveillance radar signal processing that the K-distribution limits to a Rayleigh as its shape parameter increases, justifying the Rayleigh approximation of the K-distribution in certain scenarios. In the analysis of real data, it has been observed that this approximation tends to be valid for shape parameters >20. Using Stein's method, it is possible to construct explicit bounds on the distributional differences to quantify this observation.

This study presents distributed conjugate gradient (CG) algorithms for distributed parameter estimation and spectrum estimation over wireless sensor networks. In particular, distributed conventional CG (CCG) and modified CG (MCG) algorithms are developed with incremental and diffusion adaptive cooperation strategies. The distributed CCG and MCG algorithms have an improved performance in terms of mean square error as compared with least-mean square-based algorithms and a performance that is close to recursive least-squares algorithms. In comparison with existing centralised or distributed estimation strategies, key features of the proposed algorithms are: (i) more accurate estimates and faster convergence speed can be obtained and (ii) the design of preconditioners for CG algorithms, which can improve the performance of the proposed CG algorithms is presented. Simulations show the performance of the proposed CG algorithms against previously reported techniques for distributed parameter estimation and distributed spectrum estimation applications.

To solve the problems of poor fixed distance precision and difficult engineering implementation of the pseudo-random frequency hopping fuze, a new signal processing method for the fuze based on signal reconstruction is proposed in this study. First, the transmitted signal is used to generate a set of local reference signals for the matched filter. Then all the local reference signals are applied to coherent integrate with the reflected echo, respectively. Finally, any channel of these correlation peak values exceeding the presupposed threshold can be taken as fixed distance successfully. Furthermore, the relative speed between the missile and target can be approximately estimated by the corresponding channel number. The simulation results show that the method can detect the target precisely, which means that the problem of mismatched filter has been solved. Moreover, the method is easy to be implemented, which can greatly improve real-time property of the fuze, thus it has practical value for engineering application.

This study considers the problem of waveform design for colocated multiple-input multiple-output (MIMO) radars for multiple targets in the presence of multiple interferences in white Gaussian noise. Here, the authors jointly design the transmit waveform and receive beamforming by a sequential algorithm. The proposed sequential algorithm maximises the minimum signal-to-interference-plus-noise ratio (SINR) to design both continuous and finite alphabet phase waveforms. In the case of continuous phase, all phases can be chosen in the waveform space, while in finite alphabet case, phases are only chosen from a confine set. Two important practical constraints of ‘constant envelope’ and ‘similarity’ are considered as well. The authors also have converted the waveform design problem into a quasi-convex optimisation problem which can be effectively solved by using convex optimisation toolbox (CVX). They have evaluated the performance of the matched filter output, beampattern and peak-to-average power ratio via numerical simulations and shown that the proposed sequential method achieves better SINR performance compared with existing MIMO radar transmit waveform design methods, for both single and multiple target scenarios.

In this study, a novel algorithm based on the linear canonical transform (LCT) is proposed for parameters estimation of a quadratic frequency modulated (QFM) signal. First, a new kind of generalised LCT (GLCT) is defined and the GLCT of the QFM signal will generate an impulse. The third-order phase coefficient of the QFM signal can be estimated in accordance to the position information of such impulse. After compensating off the third-order phase coefficient, the QFM signal can be approximated to linear frequency modulated (LFM) signal and the second-order, first-order phase coefficient and the amplitude can be estimated by algorithms for estimating the LFM signal. The proposed algorithm does not suffer a heavy computational burden because it only requires one dimensionality maximisation and the LCT has fast numerical algorithm as well. Moreover, the proposed algorithm has accurate estimation and low signal to noise ratio (SNR) threshold. Meanwhile, high-output SNR of the proposed algorithm can be gotten with a small number of sampling points. Comparisons with existing algorithms verify that the proposed algorithm has a good performance in the aspects of computational complexity, accuracy and output SNR in some cases.