Cooperative spectrum sensing (CSS) is a technique where multiple cognitive radio users cooperate among themselves to make binary decisions about the presence of a primary user. The single cognitive user often faces the hidden terminal problem. However, CSS tackles this problem by sending local sensing-based decisions to the fusion centre. A major drawback of conventional energy detection is the poor performance at low SNR regime. In this work, likelihood ratio statistics is considered as a test-statistic due to its highest statistical power. An improved likelihood ratio statistic-based CSS scheme is proposed by considering several past sensing events. The proposed scheme mitigates the poor detection at low SNR regime and misdetections arising due to sudden drops in signal energy. Furthermore, the generalised Byzantine attack is taken into account considering a security aspect. The proposed scheme is also shown to outperform Anderson Darling-based malicious user detection in CSS at a low SNR regime. The proposed scheme is verified and validated over empirical spectrum data. The performance improvement is at the cost of computational time, which in practice is very low and is justified by the significant performance improvements of the proposed scheme at low SNR regime.

The wireless local area network indoor localisation method based on fingerprints has been widely researched and applied due to its higher positioning accuracy and lower cost. However, its engineering is limited because of the large offline workload and time-varying signal. To address these problems, an indoor localisation algorithm based on Markov state iterative analysis (MSIA) and fingerprint clustering structural optimisation (FCSO) is proposed in this study. First, the received signal strength time variation can be solved using the MSIA algorithm, which is based on the correlation of the memory source. Then, the offline workload can be considerably reduced and positioning accuracy can be improved with the FCSO algorithm, which contains fingerprint structural and clustering optimisation stages. In the structural optimisation stage, about half of the fingerprints can be omitted. In the clustering optimisation stage, high errors can be avoided. Finally, the locations of the positioning point can be obtained through the combination of MSIA and FCSO. Experimental results show the proposed algorithm can reduce the offline workload by about 50%, and the positioning accuracy can be increased when using MSIA and FCSO algorithms compared with other algorithms.

In the 5G system, different units probably do cooperation to satisfy the communication requirements. However, when network configuration is limited, these units may be difficult to adopt the globally cooperative style. In this case, local cooperation is considered. This study focuses on local cooperation, and mainly aims at interference mitigation between different units and receiving performance improvement for each unit. Generally, a two-step scheme is proposed. First, channel decomposition is acted on interference mitigation through the design of first-step transmitters and receivers. Second, channel diagonalisation with symbol processing and selection principle is executed for receiving performance improvement, and the second-step transmitters and receivers are generated. The authors' contributions are: (i) they present the general scenario of local cooperation, and propose the corresponding strategies of interference mitigation and receiving performance improvement; (ii) they do not apply any iterative algorithm, and can adjust the quantity of information interaction between multiple units; (iii) they can make the symbol processing rule, modulation mode and signal-to-noise ratio metric flexible for each data stream. Numerical results illustrate the proposed scheme efficiently reduces the bit error rate, which means the proposed scheme can achieve the satisfactory effect in the locally cooperative network.

A new estimator for sparse time dispersive channels in pilot aided orthogonal frequency division multiplexing (OFDM) systems is developed by considering prior knowledge on channel time dispersions. The authors propose a weighted atomic norm minimisation (WANM) in order to incorporate the prior information into the estimator. The dual of the WANM is then converted to a tractable semidefinite programming using positive trigonometric polynomial theory. After solving the dual problem, the channel response is identified by solving a least squares approach. In this work, they assume that time dispersions associated delays can take any value with a mild minimum separation condition on the normalised interval . The performance of the new estimator is compared with conventional approaches. With respect to the pilot number and signal to noise ratio (SNR), simulation results reveal that the proposed estimator performs superior to that of traditional methods. It is shown that both a lower SNR and number of pilots are required to achieve the same mean square error reported in previous works.

Besides promotion in the spectrum efficiency, orbital angular momentum (OAM) can bring additional benefits to physical layer security. In this study, the authors will highlight the benefit of covert transmissions to deal with the contradiction between transmission rate and security in the traditional direct sequence spread spectrum (DSSS) system. Based on OAM, a secure high-speed spread spectrum (SS) transmission system is proposed. Specifically, the system architecture and mathematical models are established. Afterwards, the detection method for the proposed OAM SS system is investigated. Meanwhile, the corresponding bit error rate (BER) and performance of anti-interception are analysed. The performance of data anti-interception is evaluated based on computational complexity, while the performance of signal anti-interception is studied by Neyman–Pearson criterion. Furthermore, Monte–Carlo simulations are also implemented to show the effectiveness of the proposed system. Compared with the traditional DSSS system, the higher security can be achieved by the proposed system. Besides, the transmission rates and BERs are the same for the traditional DSSS system and proposed system. Therefore, the proposed OAM SS transmission system successfully handles the contradiction of the transmission rate and security. In other words, the secure high-speed transmission can be achieved by the proposed OAM SS system.

Recently, polar codes were proposed by Arikan to achieve optimum channel capacity given by Shannon theorem with low encoding and decoding complexity. Polar code construction depends on two main foundation criteria which are kernel matrix and Bhattacharyya parameter. They are related to each other, therefore the selection method for both affects the performance of polar code. Firstly, in this study, the derivations of the bounds for Bhattacharyya parameter are proved and generalised together with a proposed method to select the best kernel matrix to achieve the optimum capacity. Then, recursive channel transformations and successive cancellation decoding of the selected 3 × 3 best kernel matrix are proved. Furthermore, a general formula for polar code complexity and hardware implementation has been discussed. Simulation results show that the achievable bit error rate for the proposed methodology of selection is the same as some existing methods with the same order of complexity, which indicates its effectiveness. Polar code performance for the selected 3 × 3 best kernel matrix is improved as the code length increases. Moreover, this proposed method is general to be for higher dimension kernel matrices.

Time-varying connectivity is one of main challenges faced by controlling a team of unmanned aerial vehicles (UAVs) in the multipath fading channel, incurring low accuracy and significant convergence time of formation control law. To address this issue, in this study, a topology optimised based decentralised consensus is developed for controlling a multi-UAV system in a multipath fading channel, in which a formation structure reconfiguration scheme is proposed as well as a transmission power allocating algorithm to guarantee the control accuracy in a limited convergence time. In particular, the objective function for topology optimisation is well-designed by considering the second eigenvalue of Laplacian matrix of topology as a feasible index of connectivity degree. To improve the efficiency of information transmission, a specified consensus protocol is proposed with well-tailored packet format and signalling procedure for control messages. Through the comparative simulation results, the proposed consensus can achieve high convergence accuracy and less convergence time in a multipath fading channel, indicating high resilience of the proposed protocol under a multipath fading channel.

This study investigates information and secrecy capacity over broadcast channels through the use of directional modulation. The authors develop and demonstrate the utility of an antenna array control technique that provides communication devices with enhanced information and secrecy capacity by time-varying the array steering vectors using a novel beam control method. They show that an increase in the achievable capacity in a broadcast communication system beyond the currently-accepted Sato bound is possible by using the time domain of array steering vectors as an additional degree of freedom. Furthermore, they increase the overall secrecy capacity of the system by spatially restricting the successful reception of signals. In practical terms, this results in higher-rate, confidential messages for multiple devices for a given power constraint. They present simulation results of the array steering technique showing that direction-dependent modulation can provide broadcast channel capacity and secrecy capacity exceeding theoretical bounds for conventional, static coding techniques. They further describe an experiment and share measured results that corroborate the simulated results at the physical layer and provide insight into the proposed method.

This study analyses in-phase and quadrature-phase imbalance (IQI) in large-scale multiple antenna systems and Rayleigh fading channel. Specifically, the authors compare between different approaches (using pilot-based or blind channel estimation processes) to remove the IQI effect at a base station equipped with massive number of antennas. They obtain closed-form expression for the asymptotic achievable rate when using IQI removal algorithm and zero-forcing data detection. They also provide complexity analysis for the proposed solutions and show, by means of Monte Carlo simulations, that the proposed algorithm improves the system performance even for small number of antennas.

Video streaming has become increasingly popular in the Internet. Frequently, video transmissions are based on peer-to-peer networks, in which peers running on end-user hosts transmit data among themselves. An important security vulnerability of this strategy is that content can be easily altered by malicious users. Thus, it becomes essential to diagnose and fight content pollution in these systems. In this work, the authors present a novel strategy that relies on comparison-based diagnosis to mitigate content pollution in live video streaming peer-to-peer networks. This strategy is fully distributed and effectively combats the dissemination of content pollution. In the strategy, peers independently identify and avoid polluters. The solution works on top of the scalable overlay network Fireflies. Experimental results are presented showing the effectiveness and the low overhead of the solution. In particular, the strategy was able to significantly reduce content pollution propagation in diverse network configurations.

Peak-to-average power ratio (PAPR) is the main parameter affecting the implementation cost of wireless transmitters utilising carrier aggregation in the end-users' channels. In each frequency band, single-carrier frequency division multiple access (SC-FDMA) is exploited as the interface from the transmitter to the receiver, and carrier aggregation is implemented by SC-FDMA on each band. Hence, the power amplifier simultaneously amplifies signals of multiple bands, meaning that its PAPR is affected by the use of multiple SC-FDMA channels. In this study, a novel method has been proposed for the delay and PAPR reduction in carrier aggregation systems. Also, a novel recursive method is proposed to reduce the computational complexity of the proposed partial transmit sequence (PTS) algorithm. Utilising computer simulations, it has been shown that the PAPR can be reduced by 3.5 dB for the time-domain PTS method in mapping for the three-band SC-FDMA comparing to existing methods.

This study investigates the uplink performance of offset quadrature amplitude modulation (OQAM)-based orthogonal frequency division multiplexing (OFDM) waveform in single-cell multi-user massive multiple-input multiple-output (MIMO) systems over Ricean fading. An uplink training-based minimum mean square error (MMSE) channel estimation by exploiting the inherent characteristics of OFDM/OQAM waveform is briefly presented. By leveraging the second-order statistical characteristics of the intrinsic interference, the achievable uplink sum rates and corresponding closed-form approximations are derived in the presence of MMSE channel estimate at the base station with zero-forcing (ZF) and maximum-ratio combining (MRC) receivers. Based on the above analytical results for the uplink rates, power scaling laws are also investigated. The effect of Ricean-K factor on the achievable uplink sum rate is also examined analytically for both the MRC and ZF receivers. Numerical results compare the performance of OFDM/OQAM and classic cyclic-prefix OFDM-based massive MIMO systems and also validate the various analytical expressions derived in this work.

With the emergence of a large number of multi-core systems, many 3D routing schemes have been developed for network-on-chips (NoCs) in order to obtain low overhead and high-performance. Nevertheless, it is difficult to possess these characteristics for contemporary 3D routing algorithms. This study presents a new routing algorithm for 3D stacked NoCs based on the repetitive turn concept. The authors propose the high-performance minimum pressure turn model (MPTM) routing algorithm that can be applied to a 3D case. Repetitive prohibited turns are spread in the row and column of the planes and vertical direction in the MPTM routing algorithm with no virtual channels. Besides, the MPTM routing algorithm has minimum routing pressure by exploring the whole 3D space. Considering network average latency and throughput, the results acquired show that the MPTM scheme improves performance over existing work.

The rth relative generalised Hamming weight (RGHW) of an linear code C and an subcode , a generalisation of generalised Hamming weight (GHW), characterises code performances of wiretap channel of type II, secure network coding, linear ramp secret sharing scheme, trellis complexity etc. In this study, the authors investigate non-asymptotic and asymptotic bounds on RGHW. In the non-asymptotic setting, they present a new proof of the Griesmer bound on RGHW by residue code and introduce the new concept of relative chain condition. They show that code pairs meeting the Griesmer, Singleton, and weak Plotkin bounds satisfy this condition. The notion of relative chain condition and these results provide a new perspective on researches including evaluating trellis complexity and determining the weight hierarchy of code pairs etc. In the asymptotic setting, they improve previous work by introducing two new metrics, respectively, for the cases r is fixed and r is proportionally increasing with n. They show the asymptotic Singleton, Plotkin, and Gilbert–Varshamov bounds on the first metric and determine the value of the second metric, which is helpful for characterising the optimal asymptotic performances of applications and constructing the optimal coding schemes.

From practical and theoretical viewpoints, performance analysis of communications with correlated fading channels is important. In this study, the authors exploit a novel approach based on Copula function concept to investigate the impact of correlation of Rayleigh fading channels on communication performances. One of the most convenient ways to describe the dependence between several variables is using Copula functions. For this purpose, by applying the Farlie–Gumbel–Morgenstern Copula function, they derive closed-form expressions for outage probability as well as coverage region in a wireless multiple access channel. It is shown that the fading correlation improves the outage probability and coverage region for negative dependence structure. Specifically, whenever the dependence structure tends to negative values, the outage and coverage region performance improvement is increased. Finally, the efficiency of the analytical results is illustrated numerically.

In this study, the sum throughput maximisation problem for cognitive radio networks (CRNs) based on the multiple-input multiple-output orthogonal frequency division multiple access (MIMO-OFDMA) structure has been investigated. Hence, the intention is to maximise the downlink sum throughput of the CRN in a way that the sum power of the cognitive base station (CBS) remains below the given power limit and the induced interference on each subcarrier guarantees the interference threshold level predefined by primary users. Here, due to combinatorial constraints, the complex problem should be resolved. Hence, the core purpose of this study is to prepare a novel resource assignment algorithm that tries to fulfil these combinatorial constraints simultaneously. Therefore, this study makes progress towards solving the problem theoretically based on convex optimisation framework. An optimal solution has been implemented by proposing the iterative algorithm in which an optimal level of Lagrangian coefficients is obtained. Then, because of the optimal algorithm intricacy, the two low complicated algorithms are further suggested based on the solutions of two simplified versions of the original problem. Numerical results demonstrate that the suggested algorithms improve sum throughput considerably in comparison with classical algorithm. The proposed simplified algorithms converge to the optimal solutions’ performance while their complexities are desirable for practical implementation.

In this study, the authors propose a new time-of-arrival (ToA) algorithm for positioning in the physical layer of narrowband Internet-of-Things (NB-IoT) technology. This algorithm estimates the ToA of transmitted narrowband positioning reference signals (NPRSs) by detecting the first valid tap of estimated power delay profile (PDP). They estimate the PDP as well as the noise power in the time domain via inverse Fast Fourier transformation of received frequency-domain NPRSs. The accuracy of the estimated noise power is crucial in the ToA estimation since the SNR is extremely low in typical NB-IoT scenarios. The simulations show that the proposed ToA estimation method outperforms the conventional method and performs well in various scenarios.

This study addresses the problems of energy and delay in wireless sensor networks equipped with mobile sinks. The authors jointly consider the compressive sensing (CS) theory, cluster-based routing, and sink mobility to propose a data collection method named ‘weighted data aggregation trees with optimal mobile sink(s) (WDAT-OMS)’. The proposed scheme relies on a two-level architecture in which sensors are clustered at the first level. WDAT-OMS uses the CS theory along with load-balanced data aggregation trees to route packets from sensors to the corresponding cluster heads (CHs). In this regard, they present an efficient metric named ‘energy-and distance-aware CH selection’ to fairly distribute the energy consumption among different sensors. At the second level, one or more sinks traverse the network to collect the aggregated data of CHs. As an advantage, WDAT-OMS not only balances the energy consumption among different sensors but also increases the network scalability. Numerical results demonstrate that the proposed algorithm reduces energy consumption in comparison with ‘centralised clustering algorithm’, ‘energy-aware CS-based data aggregation’, and ‘energy-balanced high-level data aggregation tree ‘by 66%, 62%, and 63% for an average number of clusters, respectively. It also decreases the sink delay in comparison with the ‘single-hop data-gathering problem’ by 10%.