Ever since the idea of buffers was incorporated in wireless communications, buffer-aided relaying has become an emerging breakthrough in the world of transmitting and receiving signals. Equipping the relays with buffers adds a new degree of freedom capable of enhancing numerous quality-of-service (QoS) metrics including throughput, outage probability, power efficiency and physical-layer security. The QoS enhancement is achieved by compromising the end-to-end delay that is inflicted by storing the packets in the relays' buffers until a suitable source–relay or relay–destination link is selected. In this context, the selection of a relay for transmission/reception is important since it governs the QoS-delay trade-off that can be contemplated. In this survey, the authors review and analyse various link selection protocols in buffer-aided relaying systems. These relaying strategies are categorised and contrasted according to their performance levels, limitations, applications, system model assumptions and complexity. Finally, they discuss current challenges, and highlight future research directions.

Securing wireless communication, being inherently vulnerable to eavesdropping and jamming attacks, becomes more challenging in resource-constrained networks such as internet-of-things. Towards this, physical layer security (PLS) has gained significant attention due to its low complexity. The authors address the issue of random inter-node distances in secrecy analysis and develop a comprehensive quality-of-service (QoS) aware PLS framework for the analysis of both eavesdropping and jamming capabilities of the attacker. The proposed solution covers the spatially stochastic deployment of nodes. The secrecy performance is characterised against both attacks using inter-node distance-based probabilistic distribution functions. The model takes into account the practical limits arising out of underlying QoS requirements, which include the maximum distance between legitimate users driven by transmit power and receiver sensitivity. A novel concept of eavesdropping zone is introduced, and the relative impact of jamming power is investigated. Closed-form expressions for asymptotic secrecy outage probability are derived offering insights into the design of optimal system parameters for desired security level against the attacker's capability of both attacks. The analytical framework, validated by numerical results, establishes that the proposed solution offers a potentially accurate characterisation of the PLS performance and key design perspective from point-of-view of both legitimate user and attacker.

The exponential rise in the demands of the wireless communication system has alarmed industries to achieve more efficient and quality-of-service (QoS) centric wireless communication networks. The decentralised and infrastructure-less nature of wireless sensor networks (WSNs) enable it to be one of the most sought and used wireless network globally. Its cost-efficiency and functional robustness towards low-power lossy networks make it suitable for internet-of-things (IoT) applications. In recent years, IoT technologies have been used in diverse applications, including Smart City Planning and Management (SCPM). Although, mobile-WSN has played a decisive role in IoT enabled SCPM, its routing optimality and power transmission have always remained challenging. Noticeably, major existing researches address mainly on routing optimisation and very few efforts are made towards dynamic power management (DPM) under non-linear network conditions. With this motive, in this study, a highly robust and efficient QoS – centric reinforcement learning-based DPM model has been developed for mobile-WSN to be used in SCPM. Unlike classical reinforcement learning methods, the authors’ proposed advanced reinforcement learning-based DPM model exploits both known and unknown network parameters and state-activity values, including bit-error probability, channel state information, holding time, buffer cost etc. to perform dynamic switching decision. The key objective of the proposed model is to ensure optimal QoS oriented DPM and adaptive switching control to yield reliable transmission with the maximum possible resource utilisation. To achieve it, they proposed model has been developed as a controlled-Markov decision problem by applying hidden Markov model it obtains known and unknown parameters, which are subsequently learnt using an enhanced reinforcement learning to yield maximum resource utilisation while maintaining low buffer cost, holding cost and bit-error probability to retain the QoS provision.

In the military battlefield, maintaining high survivability of energy constraint wireless sensor network (WSN) when some nodes are destroyed by the foe troops is one of the prominent issues for the researchers. This study proposes the fuzzy and neuro-fuzzy based relay selection schemes for cooperative WSN which reduce the bit error rate (BER) while improving the network lifetime. Meanwhile, the proposed model maintains the uninterrupted communication between military nodes in a warfare situation. The proposed proposed strategies are compared with the maximum residual energy-based relay selection (MRERS), minimum energy consumption-based relay selection (MECRS), and random relay selection (RRS) strategies. The performance of the proposed and existing strategies is evaluated on the basis of BER, network lifetime, number of dead nodes, and average energy of nodes in the network. The simulation results demonstrate that proposed schemes has 13.19–19.28% improvement in BER than the existing strategies. Moreover, 76.00–90.88% network lifetime improves when compared with the MECRS and RRS strategies. However, 6–7.76% is less than MRERS strategy. Furthermore, the results show that network survivability and average network energy is also better when the number of dead nodes in the network increases.

In this study, the performance of downlink simultaneous wireless information and power transfer (SWIPT) networks over Nakagami-m fading is analysed. The SWIPT network is modelled as a two-tier heterogeneous network, where one tier is the information transmission network and the other is the power transmission network. The seamless integration enables both data and energy to be transferred from access points to the users. Using the stochastic geometry theory, the expressions for outage probability at the information receiver are derived in decoupled and integrated SWIPT networks. Also, the average harvested energy at the power receiver is derived assuming a non-linear energy harvesting model. Simulation results validate the analytical expressions and the impacts of various system parameters on the SWITP performance are investigated.

The extensive use of Internet of things (IoT) devices demonstrates an increasing demand for secure frameworks. Position altering attacks are amongst the most severe vulnerabilities in two-way time of arrival distance measurement technique, which is the most common in distance measurements by IoT devices. The overshadowing attack as a distance enlargement attack replays the authentic signal with a certain amount of delay and sensible power amplification. Therefore, the attack detection is difficult and requires a precise model to estimate its behaviour. The contribution of this study is a location estimation method based on the overshadowing attack probabilistic model that estimates the attack outcome delay and corrects the erroneous measurements. The overshadow delay, which is the delay between the authentic signal and the attacked one, plays a key role in this process. The method has been evaluated by three attack scenarios and compared to the conventional maximum likelihood (CML) and mixture secure location of things (M-SLOT) methods. The results of the proposed method demonstrate root mean squared error (RMSE) of 0.48 in position estimation. With the same dataset, RMSEs of M-SLOT and CML methods are 4.69 and 9.84, respectively, which confirm the better performance of the proposed method.

This study proposes three-node cooperative computing schemes for wireless sensor networks (WSNs), including parallel offload cooperative computing (POCC) and serial offload cooperative computing (SOCC). The cooperation system includes a task node with execution tasks and two peer help nodes. Specifically, the authors fully mobilise the computing and communication resources in the network by means of cooperative computing to minimise the energy consumption of processing tasks in the WSN while satisfying the delay constraints. The authors characterise these problems as optimal problems and find the optimal solutions using corresponding iterative algorithms, respectively. The simulation results show the superior performance of the proposed schemes in terms of energy consumption and node fairness. For different cases the superiority of POCC and SOCC is verified separately, and the SOCC is more suitable for the case where task node is located at the edge of WSN. Furthermore, the authors introduce a trade-off scheme between POCC and SOCC, which can always achieve the optimal scheme in different cases.

Large-scale multi-user multiple-input multiple-output (MU-MIMO) systems and cloud radio access networks (C-RANs) are promising technologies for the fifth generation (5G) of wireless networks. In this context, the use of low-resolution analogue-to-digital converters (ADCs) is key for energy efficiency and for complying with constrained fronthaul links. Processing signals with a few bits implies performance loss and, therefore, techniques that can compensate for quantisation distortion are fundamental. In wireless systems, an automatic gain control (AGC) precedes the ADCs to adjust the input signal level in order to reduce the impact of quantisation. In this work, the authors propose the joint optimisation of the AGC, which works in the remote radio heads (RRHs), and a low-resolution aware (LRA) linear receive filter based on the minimum mean square error (MMSE), which works in the cloud unit (CU), for large-scale MU-MIMO systems with coarsely quantised signals. They develop linear and successive interference cancellation receivers based on the proposed joint AGC and LRA MMSE (AGC-LRA-MMSE) approach. An analysis of the achievable sum rates along with a computational complexity study is also carried out. Simulations show that the proposed AGC-LRA-MMSE design obtains substantial gains in bit error rates and achievable information rates over existing techniques.

In this study, a simple two-user multiple-input multiple-output (MIMO) relaying scenario is considered. To efficiently exploit the spectrum resources, a generalised singular value decomposition (GSVD) based precoding scheme with non-orthogonal multiple access (NOMA) is proposed, which converts the multiple channels into several parallel single channels. The performance of the proposed GSVD-MIMO relaying scheme is evaluated by using the distribution characteristics of squared generalised singular values of two users' channel matrices and the eigenvalues of the relay's channel matrix to obtain the expressions of the average data rate and outage probabilities. Both the asymptotic case and a practical scenario with nodes equipped with finite numbers of antennas are analysed because the distribution characteristics of squared generalised singular values in the two cases are different. Two special cases, single-input multiple-output and multiple-input single-output are considered. Simulation experiments are carried out to verify the effectiveness and accuracy of the obtained analytical results.

In this study, secure communications in a two-way relaying wiretap system with a silent eavesdropper are studied. Under the assumption that the channel state information relating to the eavesdropper is unknown at legitimate nodes, the precoding vectors at the two source nodes are jointly designed to decrease the wiretap capacity at the eavesdropper. The derived relationship between the two precoding vectors is partially similar in nature to the linear minimum mean squared error (MMSE) equaliser. An iterative process is proposed to jointly achieve two precoding vectors, and its convergence is proved. Simulation results are presented to demonstrate that the proposed MMSE-based precoding algorithm can be used for source nodes with any number of antennas, and outperforms its conventional zero-forcing- and matched-filter-based counterparts. Signal leakage from the relay node to the eavesdropper is nearly completely suppressed by the proposed precoding design.

To meet the requirement of constrained delay and computation resource of the future vehicular networks, it is imperative to develop efficient content caching strategy and computation resource allocation strategy in mobile edge computing (MEC) servers. In the proposed network framework, since the caching capacity and computing resource of each MEC are limited, and the coverage areas of MECs are overlapped, the vehicular networks have to decide what contents to cache, how to offload tasks and how much computing resource needs to be allocated for each task. In this study, in order to jointly tackle these issues, we formulate caching strategy, offloading decision and computing resource allocation coordinately as a mixed integer non-linear programming (MINLP) problem. To solve the MINLP problem, we divide it into two subproblems. Firstly, we investigate a balanced and efficient caching strategy based on similarity in vehicular networks. Secondly, we apply McCormick Envelopes to convert MINLP problem into LP problem, and then adopt improved branch and bound algorithm to obtain the optimal offloading decision and computing resource allocation strategy. Simulation results indicate that the proposed schemes have a good performance in reducing economic cost under the deadline of each task.

Energy efficiency (EE) maximisation is one of the most important necessities of the fifth-generation (5G) wireless networks. In this study, both power allocation and channel assignment issues for the cellular network underlaid with device to device (D2D) communication are introduced. The main objective is to assign the users’ resources in order to maximise the total EE of the network. The distributions of both the D2D users (DUs) and the cellular users (CUs) are based on the stochastic geometry theory. Hence, the mathematical formula for the optimisation problem is demonstrated. Additionally, the resource allocation link admission (RALA) algorithm is proposed to achieve the maximum EE. Moreover, it assigns the optimal powers for each CU and DU in the system. Furthermore, the best channel assignment for each new D2D link request is determined. The optimisation problem in the RALA scheme is solved by utilising a proposed modified Cuckoo search algorithm. Furthermore, the complexity analysis for the proposed scheme is introduced. From simulation results, the proposed RALA scheme is efficient to assign the resource allocation for the users to achieve the near-optimal EE.

A communication void is one of the most serious issues in any routing techniques. This issue occurs when a node does not have any forwarder node to forward the data packets towards the sink node or surface station. The presence of a void node affects the overall performance of routing techniques in terms of end-to-end delay, data loss, energy consumption, and so on. The primary objective of this work is to avoid the void region in underwater sensor networks (UWSNs). For the same purpose, this work introduces the void-hole avoidance routing algorithm for UWSNs. This work avoids horizontal transmission, which further reduces the end-to-end delay. The residual energy, depth, holding time, and distance from the sending node to the forwarding node and forwarding node to the surface station are used as a matrix to select the best forwarder node. The simulation has been done on MATLAB to analyse the performance of the proposed algorithm. The proposed routing algorithm attained better performance using the metrics, namely packet delivery delay, number of dead nodes, and energy tax with the values of 0.9147, 48, and 72.14 by varying the transmission range, and 0.9184, 38, and 71.12 by varying the network size, respectively.

The achievable secrecy rate regions of various multi-user channels with Gaussian inputs are well-known in the literature. To gain more practical insights into the achievable rates, it is more useful to consider channels with inputs from finite constellations, such as M-ary quadrature amplitude modulation (M-QAM), M-ary phaseshift keying (MPSK), M-ary amplitude phase-shift keying (M-APSK) etc. The authors study the achievable secrecy rates with a constrained constellation input for a multiple access wiretap channel with an eavesdropper. They also show that if the constellation points are rotated relatively for the two users then the secrecy sum-rate can be improved. They perform Monte–Carlo simulations for computing these secrecy rates for classical modulation schemes including BPSK, quadrature phase-shift keying, M-QAM, M-PSK, M-PAM, and M-APSK. They also derived an approximate function, whose argument of supremum provides an approximately optimal rotation angle for obtaining a maximum secrecy sum-rate. they also show, via simulations, that rotation of constellation is helpful for some range of signal-to-noise ratio only, which is contrary to the results of multiple access channel without security constraint. Finally, they consider a more realistic scenario, where the channel from transmitters to receivers and eavesdroppers is time-varying. They consider the case of complex circularly symmetric Gaussian random channel gains and compute the optimal rotation angle, which will maximise the expected value of an upper bound of the secrecy sum-rate.

This study investigates the impact of co-channel interference caused by external terminals on multi-user bi-directional amplify-and-forward based wireless relaying network. The investigation considers multi-user pair and a single bi-directional relay terminal and a finite number of co-channel interference in the system model. A lower bound on the end-to-end outage probability is derived for the simultaneous transmission and the opportunistic source-pair selection strategy. According to analytical, asymptotic, and Monte-Carlo based computer simulation results, the opportunistic source-pair selection strategy achieves a near-optimal performance for the inter-cell interference caused by other user-pairs within the system. Results also show that the opportunistic source-pair selection strategy also achieves optimal diversity order, which is equal to N, in high signal-to-noise ratio regimes. Results also show that the co-channel interference degrades the achievable diversity order from N to 0 while also affecting the system coding gain.

This study presents the performance evaluation of a data-offloading algorithm developed and implemented in the framework of a software-defined network (SDN). The algorithm senses the network congestion and takes into account the constraints imposed to the throughput and delay in order to command a data offloading operation from the current active interface to another one available in a given host. Both, emulation and experimental demonstration of the approach were implemented in the open network operating systems in which multimedia services were transported within the SDN environment and assessed in terms of the algorithm parameters configuration. The experimental demonstration confirms the feasibility of the proposed algorithm to offload the traffic of a given data stream to a less congested available interface or network.

A symbol-asynchronous uplink non-orthogonal multiple access (NOMA) model is considered, where K users transmit codewords to a common receiver according to their local clocks. As the complicated user location and the dynamic transmission environment, the exact time offsets of users are not always available at the base station (BS). To ensure the efficiency of the system, linear minimum mean square error algorithm and partial message passing (P-MP) algorithm are designed based on iterative detection. The signal to interference plus noise ratio is also applied to analysis the effect of estimated time offsets on the P-MP algorithm. Then simulation results show that when the variance of estimation error is , the symbol-asynchronous NOMA systems with imperfect time offsets can achieve the same or even better bit error rate performance than the NOMA system.

Due to the tremendous propagation loss of millimeter wave (mmWave) communication, device-to-device (D2D) communications are widely used over directional mmWave networks to improve network throughput. Most of existing works are mainly focused on concurrent transmission among D2D pairs that have no mutual interference. However, considering the propagation loss and directional interference features, the D2D pairs that interfere with each other can be used to improve network throughput. In this paper, we propose a time resource sharing scheme based on Stackelberg game for D2D pairs to further enhance network throughput. The interference D2D pairs can access to the time resource through paying the price for the interference caused by them. At the same time, the non-interference D2D pairs can be scheduled. Concurrent transmission scheduling among interference D2D pairs is formulated as a non-cooperative game, which enables a distributed transmission power control for interference D2D pairs. Moreover, the price strategy can be adjusted by setting interference threshold such that the transmission quality can be guaranteed. Simulation results show that the proposed scheme can achieve significant performance gains compared with classical concurrent transmission in terms of network throughput and energy efficiency. In addition, the convergence and utility of the game are also verified.

In this study, the authors demonstrate that transmission rate in white phosphorescent light emitting diode (LED) transmitter communication-illumination system can be increased significantly by simultaneous transmission of an additional infrared (IR) channel. Unlike in typical colour multiplexing, the IR channel does not require a dedicated receiver filter as the channel crosstalk can be removed using digital signal processing. Both channels can operate in synchronous or asynchronous mode. The experimental results in this study demonstrate a significant increase in the data rate.

The emergence of computation offloading can meet the real-time requirements of computing tasks with intensive computing demands. In this study, the authors use opportunistic communication to construct a network framework for opportunistic edge computing (OEC) to perform computation offloading. Specifically, OEC forms a computing resource pool near the edge servers in the edge layer by gathering idle computing resources. Firstly, the state of the system is defined by the attributes of the computing task, the execution location of the computing task and the location of the terminal device in OEC. Then the computation offloading time is calculated and learned by selecting different offloading nodes. Finally, an optimal offloading node selection strategy based on the Q-learning algorithm is obtained. Extensive simulations show that the proposed strategy consumes the minimum computation offloading time compared with benchmark algorithms in aspects of the amount of uploaded data, the total number of CPU cycles of the task and the number of computing tasks.

Mobile edge computing (MEC) is concerned with moving complex tasks from data sources to nearby computing resources, which can reduce computing latency and remote cloud workload. Although there has been significant research in the field of MEC, research on edge server placement in wireless metropolitan area networks (WMANs) is overlooked, and the load balancing problem of edge servers is seldom discussed. From a practical perspective, how to place edge servers efficiently in WMANs while considering load balancing between edge servers is studied. A greedy algorithm is proposed that can balance the workload of edge servers more effectively. However, the performance of the greedy algorithm as the number of servers placed increases is not ideal. Therefore, the authors combine the greedy algorithm with a genetic algorithm (GA) to minimise the number of edge servers while ensuring load balancing between edge servers and quality of service (QoS) requirements for mobile users. Finally, they conduct simulation experiments and compare the proposed algorithms with other algorithms. The improved GA proposed is superior to the greedy algorithm in terms of load balancing and the number of servers. The experimental results demonstrate that the algorithm has excellent performance.

Fast session transfer (FST) is introduced by wireless gigabit (WiGig) standards to transfer the data communication session among wireless fidelity (Wi-Fi) and WiGig channels based on the availability. In the conventional Wi-Fi/WiGig FST decision-making, the session of data transmission is transferred from Wi-Fi to WiGig whenever it is possible regardless of the traffic loads on both bands and the expected WiGig blocking probability. Also, WiGig to Wi-Fi FST occurs whenever the WiGig signal is lost even if the WiGig link is undergoing an instant path blocking. This results in Wi-Fi/WiGig load imbalance as well as large average delay in user data delivery. In this study, a novel Wi-Fi/WiGig FST decision-making algorithm is proposed utilising fuzzy logic while considering the coverage probability of the WiGig link, the sizes of the users' remaining messages relative to the available data rates of both bands, and the probability of WiGig path blocking. Furthermore, a WiGig interruption-classification methodology is proposed to detect the occurrence of the WiGig instant path blocking and then decide if it is better to wait for WiGig signal recovery or immediately transfer to Wi-Fi. Simulation analysis demonstrates the effectiveness of the proposed Wi-Fi/WiGig FST decision-making algorithm, over the conventional one.

Fast frequency hopping code division multiple access (FH-CDMA) is a low complexity option for multiuser communication in fast, frequency selective fading channels such as in mobile mmWave communications. The original, orthogonal FH-CDMA has low spectral efficiency and up to now lacks a non-orthogonal version. In this work, a soft input soft output, non-orthogonal multiuser detector is designed using factor graphs. Extrinsic Information Transfer (EXIT) chart analysis of this detector allows determination of which multiple access code length maximises system spectral efficiency. Results show that when the access code length is reduced to an ideal length, spectral efficiency is maximised. Another conclusion is that maximum spectral efficiency is similar in value to a system with no multiple access method.

Achieving high quality of service (QOS) at the end-users while maintaining the low interference power at the primary users is the main goal in underlay cognitive radio networks. This goal becomes a more difficult task in the designing of beamforming vectors where all channels state information (CSIs) in the secondary network, as well as the interference CSIs, are uncertain. This task is addressed in this study using an iterative optimization technique. In this technique, the original CSI problem, which is difficult to solve as a single optimization problem, is instead separated into two sub-problems. The first subproblem is the interference power problem, which can be solved either sub-optimally or optimally using Lagrange duality. The second sub-problem is the QOS problem, which can be solved either sub-optimally or robustly using non-monotone spectral projected gradient method. The two sub-problem solutions are then recombined into a single problem to extract beamforming vectors. Two methods are invoked to extract the beamforming vectors: either the successive convex approximation (SCA) method or the bisection search method. Theoretical analysis and simulation results indicate that the two methods can offer a tradeoff between better QOS (using bisection search method) or less computational complexity (using SCA method)