Massive multiple-input multiple-output (MIMO) is currently entering the practical implementation phase, and key implementation issues for this technology have yet to be fully addressed. Crucial among these is the practical problem of frequency synchronisation, which refers to the adjustment of the clock frequency of local nodes to the clock frequency of a reference node by estimating and compensating carrier frequency offset. Existing theoretical studies on massive MIMO generally assume perfect frequency synchronisation; however, the potentially very high complexity of this process poses a major challenge for massive MIMO systems. Therefore, new frequency synchronisation techniques are urgently needed to make the practical implementation of massive MIMO feasible. In this study, the authors provide a comprehensive classification of the existing research efforts along this line, considering different antenna architectures and modulation schemes. They also highlight the key challenges in frequency synchronisation for massive MIMO, and they outline future research directions on this topic.

Fog computing (FC) with a distributed architecture plays an essential role in Internet-of-Things (IoT). This paradigm utilises the processing abilities of Fog devices (FDs) and decreases latency. The large volume of data and its process in IoT can cause network failures. Researchers tend to consider communication reliability to reduce fault effects and achieve high performance. Fault tolerance becomes a necessary matter to enhance the reliability of the Fog. Notably, fault tolerance studies have been performed mostly on the Cloud system. To counter this issue, the authors propose a novel fault-tolerant scheduling algorithm of modules in FC and optimise it. The main idea of this approach is a classification method for different modules alongside of computing the energy consumption of all FDs and finding minimal FDs' energy consumption. To distribute modules between FDs, they present an energy-efficient checkpointing and load balancing technique based on the Bayesian classification and call it by ECLB. The performance of the proposed method is evaluated by comparing it with the state-of-the-art algorithms in terms of delay, energy consumption, execution cost, network usage, and total executed modules. Analysis and simulation results indicate that the authors' methods are efficient and superior to others.

Goal-oriented Luby transform (LT) codes are required in different scenarios. Based on the random walk model, analysis of ripple size evolution provides an effective method to design LT codes. However, the ripple addition in each step depends on both the number of symbols released in the current step and the ripple size in the last step, leading to distortion. Therefore, the authors propose a random walk algorithm with barrier (RWA-B) to model the ripple addition directly. To evaluate the performance of ripple size evolution, they utilise generalised degree distribution algorithm to generate corresponding degree distribution. Through analysing the relationship between the performance of generated ripple size evolution and the parameters of RWA-B, they design an iterator greedy algorithm to search the optimal ripple size evolution for desired goals. As a result, they compare three goal-oriented degree distributions with others through numerical simulations. In binary erasure channel, both the memory usage oriented and block error rate (BER) oriented degree distributions outperform others with lowest average overhead, and the overhead oriented degree distribution outperforms others in terms of average overhead and average degree. In additive white Gaussian noise channel, the BER-oriented degree distribution outperforms others in terms of BER and average overhead.

In this article, we have employed an energy detector (ED)-based cooperative spectrum sensing (CSS) with multi-antenna for cognitive radio network (CRN). The spectrum sensing error and energy efficiency (EE) are the key performance parameters in CRN which are affected by the threshold selection method, number of antennas employed at each cognitive user (CU), reporting error probability and cooperative fusion-rule applied at fusion center (FC). Therefore, we have derived the expression for sensing error by considering the effect of all these parameters and have optimized the cooperative fusion-rule at FC by formulating mathematical expression for optimal K in k-out-of-M rule to minimize the sensing error. Since CSS improves the sensing performance of CRN at the cost of increased overhead bits due to more CUs reporting to FC, results reduced EE. We have employed censoring approach to reduce the energy consumption and hence increase the EE of CSS technique. Further, we have illustrated the sensing error and EE improvement achieved under the censoring approach when different threshold selection approaches are employed at each CU. The percentage EE enhancement in censoring approach are 19.53% and 19.9% with constant false-alarm rate (CFAR) and minimized-error probability (MEP) approaches, respectively in comparison to that of the non-censoring approach.

This paper has collectively exploited cognitive radio (CR), non-orthogonal multiple access (NOMA) and multiple-input-multiple-output (MIMO) communication systems in order to propose a spectral-and interference-efficient framework which is named as MIMO-based CR–NOMA communication system. The proposed framework is analysed for the uplink and downlink scenarios. Further, the closed-form expressions for throughput at each user due to the number of transmitting-and receiving-antennas are derived numerically for the downlink-and uplink-scenarios. In addition to this, the total/sum throughput for different frameworks such as CR–NOMA, CR–MIMO and MIMO-based CR–NOMA systems is derived for both the downlink and uplink scenarios. Moreover, in order to satisfy the interference constraints at the primary user due to cell-edge/far-user [cognitive user (CU)-4] transmission in the uplink scenario, a new metric known as interference efficiency is derived. Furthermore, the proposed frameworks are simulated for downlink and uplink scenarios and the relationship between throughput of cell-centred/near-user (CU-1) and CU-4 are presented. Moreover, the total throughput for different frameworks and interference efficiency is also illustrated with the simulation results. The simulation results reveal that the proposed MIMO-based CR–NOMA system outperforms the existing MIMO–NOMA, CR–NOMA and CR–OMA systems in terms of the CUs' individual throughput, total throughput and interference efficiency of the system.

The authors incorporate Alamouti space-time block coded orthogonal frequency division multiplexing (OFDM) with signal space diversity (SSD) in order to significantly strengthen the physical layer security of the communication network. The coordinate interleaving step of SSD is performed amongst OFDM subcarriers, according to distinct strategies that make the correlation coefficients between the subcarrier channel gains equal to zero. The proposed system model can improve the security by enabling a legitimate user to have much less error than an eavesdropper, even under the worst-case scenario where the unauthorised receiver somehow captures the interleaving strategy compromised by the transmitter and legitimate receiver. It is shown that a legitimate user with the introduced scheme can provide up to 14% more performance gain as compared to an unauthorised receiver for a bit error rate (BER) of 10⁻⁴ under worst-case scenarios with different parameters. An exact closed-form expression of the BER is derived for the legitimate user and shown to match with the simulation results. Finally, it is demonstrated that the system is also capable of enhancing the resistance against channel estimation errors at the receiver. The proposed system does not require high complexity or additional bandwidth or time resources.

In this study, the authors consider the user rate optimisation for wireless powered communication networks (WPCNs). To improve the user rate, a novel minimum mean square error (MMSE)-based transmission method is proposed for WPCNs. For maximising the user rate, a user rate optimisation problem with MMSE constraints in the uplink transmission is formulated, which is considered as a convex optimisation problem. Considering the uplink power allocation, downlink energy beamforming, and the time ratio between uplink and downlink durations, a novel Newton iterative algorithm is proposed to obtain the optimal solution of the optimisation problem. Furthermore, the computational complexity of the MMSE-based method is illustrated by theoretical analysis. Simulation results show that the MMSE-based method can effectively improve the user rate compared to the zero-forcing suboptimal method and time division multiple access-energy harvesting method. Moreover, simulation results also show that the experimental runtime tends to coincide with the theoretical runtime in the MMSE-based method.

Relay-assisted device-to-device (D2D) communications have been proposed as a supplement for direct D2D communications to enhance traffic offloading capacity. In this study, the authors propose a joint mode selection, relay selection and resource allocation for relay-assisted D2D communications. They aim at maximising the overall system throughput while guaranteeing the power limitation and signal-to-noise-and-interference ratios of all cellular and active D2D links. Since this optimisation is NP-hard, they then propose a graph colour-based resource allocation algorithm to effectively solve it. Simulation results show that the proposed algorithm can produce close-to-optimal performance with acceptable computational complexity.

Unmanned aerial vehicle (UAV)-assisted communications have been regarded as a promising technology, which can be used in dynamic heterogeneous networks, since the UAVs can be applied as mobile base stations (MBSs). It is more efficient to set the UAVs as MBSs in different layers according to their functions. Due to the ability in communicating with other vehicles or facilities, vehicle-to-everything (V2X) makes the information required by the vehicles be efficiently transmitted and processed, so as to increase the safety of driving. However, because of the rapid change of topology and the huge demand of data transmission, it is hard to guarantee the efficient coverage of all the vehicles only by the support of terrestrial wireless communication networks. Considering this, this study combines UAV and V2X communications together, and proposes a multi-layer aerial-road vehicular (MLARV) architecture. The UAVs in the higher layer are in charge of overall monitoring, while the UAVs in the lower layer are responsible for hot-spot area coverage. To solve the throughput maximisation problem, the authors further propose a density-aware deployment (DAD) scheme with an iterative three-dimensional matching resource allocation algorithm. Simulation results show that the proposed DAD scheme with the MLARV architecture outperforms the traditional UAV-assisted V2X communications with single layer architecture.

With self-interference cancellation (SIC), a wireless full-duplex terminal is allowed to transmit and receive signal simultaneously in the same frequency band. In this study, the authors first briefly described the impact on the conventional analogue SIC method from the interested signal. To solve this problem, they propose a new practical analogue SIC scheme for full-duplex systems, which is then mathematically analysed in terms of SIC capacity. Simulation results show that the analogue SIC performance obtained by the proposed method outperform the existing analogue SIC method.

This study presents a mobile edge computing (MEC)-enabled UAV communication system, where a number of UAVs are served by terrestrial base stations (TBSs) equipped with computation resource in the non-orthogonal multiple access manner. Each UAV has to offload its computing tasks to the proper TBS due to the limited energy supply. For this, the authors aim at minimising the sum of transmission energy of UAVs and computation energy of TBSs through jointly optimising the UAV transmit power, computation resource allocation, and UAV grouping. Considering the non-convexity of this optimisation problem, they obtain the optimal solution in the coupled steps: the convex resource allocation optimisation and the combinatorial UAV grouping optimisation. By exploiting the convex nature of the resource allocation optimisation problem, they obtain the optimal transmit power and computation allocation based on the KKT conditions and the idea of gradient descent method when considering a single TBS. Then, they adopt the simulated annealing to obtain the optimal UAV grouping and TBS selection based on the proposed resource allocation optimisation algorithm. Finally, simulation results show that the proposed joint optimisation of transmit power, computation resource allocation, and UAV grouping can effectively reduce the energy consumption of MEC-aware UAV communication system.

The cooperative device-to-device (D2D) network employing non-orthogonal multiple access (NOMA) is expected to play an important role in the next-generation wireless networks. In this work, the authors derive outage probability expressions of a cooperative NOMA D2D network which employs decode-and-forward relaying. A wireless link experiencing Nakagami-m fading is considered which is further assisted in the communication network by a wired link which is a powerline communication link and experiences Rayleigh fading. The outage analysis, shown for both the strong user and the weak user, is derived assuming that at the receiver there is perfect successive interference cancellation. Employing power division NOMA, optimum value for the coefficient of power allocation is obtained corresponding to the minimum probability of outage of the strong user. Furthermore, a range of the NOMA power allocation coefficient is provided for the communication link at the weak user which is between the wireless and the powerline link. Symbol error probability expressions are also derived for the strong and the weak users for the scenario when: i) both the wireless and the wired links are available for communication and ii) only the wireless link is available for communication.

VANETs are so-called vehicular ad hoc networks, they enable cost-effective, scalable solutions, and hence, they can be applicable in entertainment and transportation platforms with the assistance of multi-hop wireless communications from vehicle-to-vehicle. Conversely, in VANET circumstance, the multi-hop communication development is still a challenging one because of the quick change in topology and regular disconnection of a network. This directs to inefficiency or routing failure in existing mobile ad hoc routing protocols. To resolve routing issues, the number of research studies is going on to attain the multi-constrained Quality of Service (QoS) metrics in VANET. This study intends to propose a cost model as the solution for vehicle routing problem by considering the network quality metrics, including congestion, travel, collision, and QoS awareness cost. Fuzzification of the QoS factor is also included in this entire routing cost. Further, the primary objective of this work focuses on the minimisation of the routing cost model by finding the optimal route. To find an optimal route, this study introduces a new algorithm, namely Mean Computing Jaya Algorithm. At last, the performance of the proposed model is compared with existing work in the literature in terms of cost analysis and convergence analysis, and proves the betterment of the proposed model with reduced routing cost.

Coprime array exhibits many advantages over the uniform linear array (ULA) with the same number of physical sensors in resolution performance and interference suppression capability. In this study, the authors take the advantages of coprime array to improve the robustness of adaptive beamformer. In the coprime virtual ULA (CV-ULA), they prove that a constructed Toeplitz matrix can be taken as the sample covariance matrix from the perspective of virtual signal characteristics. The CV-ULA Capon spectrum estimator is modified to obtain the directions and powers of all impinging signals. Since the real directions of all impinging signals are located at different angular sectors, they form independent signal subspace for each impinging signal. They also assign independent steering vector mismatches for different impinging signals to obtain their real steering vectors. The steering vector mismatch of each impinging signal is independently obtained by solving its own convex optimisation problem. They reconstruct the interference-plus-noise covariance matrix (INCM) with precise steering vectors and powers of interference signals. The proposed weight vector is computed by combining the desired signal steering vector and the reconstructed INCM. Extensive simulations show that the proposed algorithm provides robustness against many types of model mismatches.

The heterogeneous network structure is a promising paradigm to improve the quality of service across the entire network. Nevertheless, such a structure is challenging due to the presence of multiple-tier secondary users (SUs). In this study, the authors investigated the effect of spectrum allocation in heterogeneous cognitive radio networks with a primary network and two-tier secondary networks, and proposed a two-tier spectrum trading strategy which includes two trading processes. In Process One, they model the spectrum trading as a monopoly market, where the primary spectrum owner (PO) acts as the monopolist and the first-tier secondary users (FSUs) act as the buyers. They design an optimal quality-price contract to maximise the utility of PO, and the FSUs will choose the spectrum with appropriate quality and price to enhance their satisfaction. In Process Two, spectrum trading is modelled as a multi-seller, multi-buyer market. The dynamic behaviour of second-tier SUs is studied using the theory of evolution game, while the competition among FSUs is analysed via a non-cooperative game where the Nash equilibrium is considered as the solution. The existences of the optimal contract, evolutionary equilibrium and Nash equilibrium are demonstrated in the performance evaluation.

Contention-based carrier sense multiple access (CSMA) and contention-free time division multiple access (TDMA) protocol are two typical access protocols of media access control in vehicular ad hoc network (VANET). They all show their unique advantages under specific conditions. TDMA has high transmission reliability, CSMA has a low transmission delay in the communication environment with low packet arrival rate. However, when the arrival rate of information packets increases rapidly, the throughput of CSMA will decrease rapidly and approach zero, which is not suitable for data transmission in the communication environment with a high arrival rate of information packets; while data transmission through a single TDMA protocol will cause high system overhead due to strict synchronous information. Aiming at the defects of the two protocols and the multi-channel communication environment, this study proposes the optimised protocol model multi-priority time division-CSMA (MPTD-CSMA). The optimised protocol model not only ensures the reliability of data communication but also reduces the transmission delay of the system. At the same time, the multi-priority mechanism is added to increase the channel utilisation of the protocol model.

Presently, the single-carrier frequency division multiplexing (SCFDM)-based visible light communication (VLC) system is extensively implemented for secure and high-speed data transmission. However, the effect of additive white Gaussian noise in VLC with white light-emitting diode is high, due to a high peak to average power ratio (PAPR). To address this difficulty in 5G networks, two objectives were carried out in this research article. Initially, selective mapping (SLM) scheme was applied for PAPR reduction, because it considerably selects the effective phase rotation factors that help in the reduction of system complexity. Besides, binary crow search algorithm was used for sub-block partition optimisation in SLM for enhancing the convergence speed of the proposed SCFDM-based VLC system. In the experimental investigation, the proposed SCFDM-based VLC system was analysed in terms of complementary cumulative distribution function, bit error rate and signal-to-noise ratio by varying the equalisation techniques for 5G networks.

In this study, the authors consider the problem of secure and reliable communication with uncertain channel state information (CSI) and present a new solution named active secure coding which combines the machine-learning methods with the traditional physical-layer secure coding scheme. First, the authors build a detectable wiretap channel model by combining the hidden Markov model with the compound wiretap channel model, in which the varying of channel block CSI is a Markov process and the detected information is a stochastic emission from the current CSI. Next, the authors present a CSI-learning scheme to learn the CSI from the detected information by the Baum–Welch and Viterbi algorithms. Then the authors construct explicit secure polar codes based on the learned CSI, and combine it with the CSI-learning scheme to form the active secure polar coding scheme. Simulation results show that an acceptable level of reliability and security can be achieved by the proposed active secure polar coding scheme.

As the standard specification for substation, IEC61850 utilises the abstract communication service interface to map to the manufacturing message specification (MMS) to communicate between the substation level and the bay level. The conventional MMS adopts the client/server model, which results in a relatively large transmission delay. In order to solve this problem, the data distribution service (DDS) is used to replace MMS for its excellent reliability and timeliness. However, the communication law and mechanism of DDS have not been known which result in the insufficient application of DDS. An end-to-end (ETE) delay method is proposed to divide the communication process into different parts according to the sequence in time and analyse the ETE delay of each part. By this method, the delay law and difference of DDS and MMS are analysed and summarised. The simulation results by the optimised network engineering tool software validate that DDS has a smaller delay than MMS. Therefore, DDS can better meet the timeliness of intelligent substation.

This study considers the Gaussian cognitive interference channel (IC), in which one of the two users operates in cognitive mode. In addition, to transmit its signal, the cognitive sender can cooperatively forward the primary signal to its destination, the primary receiver. Moreover, the transmission over this IC also experiences interference from a third source, which is commonly known as the common interferer source. To reduce the effect of both the primary signal and the common interference signal at the secondary destination, both the cognitive transmitter and its destination may have noisy complete (non-causal) or partial (causal) knowledge of these signals. For this channel model, the achievable rate region is computed in which the availability of both the primary signal and the common interference signal at the cognitive transmitter and its destination can be (i) noisy non-causal and (ii) causally estimated. The authors numerical results confirm that knowing both the primary signal and the common interference signal can significantly increase the achievable rate region. Indeed, the obtained achievable rate region is larger than the available bounds in the literature. Furthermore, representative numerical examples are also shown to demonstrate the value of the power allocation at the cognitive source.

Due to the time-varying property of the underwater acoustic (UWA) channel, the significant Doppler spread will severely degrade the performance of direct-sequence spread-spectrum (DSSS) communications. The relative velocity variation between the transmitter and the receiver will cause both the phase rotation and the magnitude loss of correlation peak, during the long transmission of the DSSS packet. To solve this problem, the authors propose a novel transceiver design for the UWA DSSS communications. At the transmitter, the triple differential phase shift keying (DPSK) modulation is adopted to overcome the phase rotation, whereas the phase noise will be amplified resulting in the signal-to-noise ratio (SNR) loss. At the receiver, the improved bit-interleaved coded modulation with iterative decoding algorithm for DPSK is used to recover the SNR loss, in which the DPSK demodulator is treated as the convolutional decoder, and the linear prediction is adopted to track the channel variation. Furthermore, an adaptive selection of local reference signal is also applied to recover the correlation loss. Theoretical simulation shows that the proposed transceiver can effectively mitigate the performance loss caused by the motion acceleration, and the performance gain is significant over the conventional.

Ambient backscatter which utiliees the ambient radio-frequency signals to enable transmissions between battery-less devices has attracted considerable attention in academia and industry. This study addresses the questions of full-duplex (FD) and self-interference cancellation (SIC) for ambient backscatter which adopts dual-antenna structure to achieve persistent information transmission and energy harvesting. The authors construct the physical-layer network coding (PNC) mapping principle of on–off keying in the dual-antenna structure and propose the PNC-based FD algorithm to eliminate the self-interference in the information domain. Furthermore, the bit-error-ratio and throughput performances are analysed under conventional half-duplex mode and the proposed FD mode, respectively. In order to facilitate system complexity and reduce power consumption, they design a hardware prototype to achieve SIC which consists of low-power passive analogue components. Numerical results are provided to confirm the theoretical studies. Circuit simulations demonstrate that the circuit is commendably consistent with the design concept.

The non-orthogonal multiple access (NOMA) approach enables a number of users to share the same resource via superposition coding in the transmitter and successive detection in the receiver. In this study a power allocation (PA) approach based on the proportional fair division technique is proposed. In this regard, power is assigned to users such that it ensures the fairness of NOMA follows that of orthogonal multiple access. A straight forward approach that achieves this objective is stated and is followed by proposing three different algorithms. These algorithms loosen the strict proportionality criterion to fulfil the data rate of a specific user. Also, a new fairness index for NOMA based on data rate ratios is defined. Afterwards, a low-complexity strategy based on water filling (WF) for PA amongst resources is proposed. This second PA stage aims at improving the data rate of users. The proposed approaches are applied to NOMA systems with different pairing strategies and results are compared. Results show that the proposed approaches improve the fairness of NOMA and WF increases the total system rate.

The widely acceptable problem in wireless sensor networks (WSNs) is to develop a practical scheme for data aggregation in the massive range of sensor nodes that are randomly distributed over a network region. The essential operation of cluster heads (CHs) in such a network is to transmit the aggregated data to the sink node through multi-hop communication, thus the energy to be used in a better way during the period of aggregation and transmission. Therefore, this study presents a scheme based on grid clustering and fuzzy reinforcement-learning to maximise network lifetime as well as energy-efficient data aggregation for distributed WSN. Initially, grid clustering is employed for cluster formation and CH selection. Further, a fuzzy rule system-based reinforcement learning algorithm is used to select the data aggregator node based on the parameters, such as distance, neighbourhood overlap, and algebraic connectivity. Finally, the dynamic relocation of the mobile sink is performed within a grid-based clustered network region using a fruit fly optimisation algorithm. The experimental outcomes revealed that the proposed data aggregation scheme provides superior performance in terms of energy consumption and network lifetime compared to earlier systems.

Exact expressions for the probability density function (PDF) and cumulative distribution function (CDF) of cascaded Rayleigh fading channels with arbitrary correlation but not necessarily identically distributed are derived. Furthermore, the PDF and CDF of the instantaneous signal-to-noise ratio are obtained. The cascaded channels are assumed to have slow frequency non-selective arbitrarily correlated Rayleigh fading with arbitrarily values of fading parameters. Indeed, the expressions of the outage probability and average normalised channel capacity for this channel model are derived. The average bit error probability for coherently detected binary signals in additive white Gaussian noise channel as well as in arbitrarily correlated cascaded Rayleigh fading channels is obtained. Numerical results are also provided and authenticated by Monte Carlo simulation. To the best of the authors' knowledge, the derived expressions for this channel model are new and have not been reported in the literature.