This survey article discusses the revolutions of wireless communication technologies right from the prehistoric man's fire signals to today's space optical communications. A brief description of evaluations of communication technologies from the ancient Greece to today's mature telecommunication fields is discussed in this review paper. Principle, significance, demonstration and development of free space optical (FSO) communication technology over different decades are discussed. Major FSO channel limitations, temporal and spatial challenges of FSO communication system and their state-of-art mitigation techniques are presented. Classical quantitative analysis of reliability of FSO communication, developments on radio over FSO (RoFSO) and hybrid FSO/RF systems are also explained. Advanced developments of FSO communication techniques such as optical free space wavelength division multiplexing (WDM), sub-carrier multiplexing (SCM), worldwide interoperability for microwave access (WiMAX), visible light communications (VLC) and vehicular visible light communications (VVLC) are reported. Deep space optical communication systems and next generation FSO wireless terrestrial/global network architecture are summarised. Research challenges of FSO systems for internet of things/everything (IoT/IoE), 5G communication, mobile-network, terahertz spectrum, quantum communication and underwater optical applications are presented. Based on the review, we outlined the challenges that need to be addressed in near-future researches to realize full potential FSO communication systems.

Invisibility of alpha-stable (α-stable) noise as carrier signals, in the presence of additive white Gaussian noise (AWGN) as channel noise, is a key factor to ensure covert transmission by employing random communication systems (RCSs). This study introduces a novel blind recognition method for an eavesdropper to detect the presence of real-valued symmetric and skewed α-stable random carrier signals in the presence of AWGN. The introduced method is based on the proposed random carrier signal recogniser (RCSR), which consists of fractional lower-order auto-covariance block, threshold control block and the random carrier signal recognition indicator. The proposed RCSR first detects the possible presence of α-stable random carrier signals and then recognises the impulsiveness and skewness parameters, exploited by the transmitter and the intended receiver, to extract covertly conveyed binary information. However, the determined covert range can be adopted to perform secure transmission by RCSs. The simulation results reflect the simplicity of the proposed method as it is capable of performing effectively in real time by utilising extremely less number of observed samples.

In this study, the performances of commonly used precoding schemes are evaluated based on channel measurements carried out at 28 GHz in a railway station for a massive antenna system configuration. And a hybrid precoding algorithm for a fifth generation (5G) multi-user antenna system is proposed and its performance is evaluated based on real measured channels. Specifically, An upper bound for achievable sum-rate of phased zero forcing (PZF) algorithm is derived and a precoding technique by reduction of phase shifters (PSs) named reduced-PZF (RPZF) is proposed, which can obviously reduce power consumption in hybrid precoding systems. In addition, the authors give the closed-form expression for achievable sum-rate when RPZF is used. There are no requirements in the authors’ proposed scheme with complicated matrix decomposition and optimisation techniques. The simulation results show that it is possible to reduce 30 and 50% of the PSs by using the proposed hybrid precoder with better system performance in the line-of-sight (LoS) and non-LoS scenarios, respectively. In addition, the digital PSs with 3 bits low resolution can achieve the similar performance when using analogue ones.

Identification of modulation and space-time block code (STBC) is an important task of receivers in applications such as military, civilian, and commercial communications. Here, we consider multiple-input multiple-output (MIMO) systems. We propose two methods for STBC identification when the modulation is known. We also introduce a method for joint identification of code and modulation. Additionally, we present an enhanced zero-forcing (ZF) equaliser to improve the separation between the features of different classes. Higher order cumulants are used as the statistical features. In the first method of STBC identification, after the proposed equalisation, received data samples are segmented, and then using the mean and Frobenius norm of the covariance matrix of extracted cumulants as threshold values, the STBCs are detected. This method requires the knowledge of the threshold values for each modulation type and noise power. In the second method, the knowledge of noise power and the type of modulation are not needed. After the proposed ZF equalisation, feature vector based on the cumulants is calculated, and then support vector machine (SVM) classifier is used to classify different STBCs. In the third method, joint detection of STBC and modulation type is performed using the proposed ZF equaliser and mapping the received samples. This method deals with the theoretical values calculated from the cumulants of four STBCs and four modulations, where there is no need to know the noise power. The results indicate that the proposed methods perform well even at low signal-to-noise ratios (SNRs).

Different from conventional proper Gaussian signalling (PGS), whose achievable rate depends on the input signals' covariances only, the capacity of channels with improper Gaussian signalling (IGS) is a function with the signals' covariances and pseudo-covariances. Thus, the additional degree of freedom provided by pseudo-covariance is available to improve the achievable rate. In this study, the authors investigate the achievable rate region of two-users X-interference channel (IC) in the condition of applying IGS. By treating the interference as additive Gaussian noise, the authors analyze the mathematical expression of capacity based on Shannon's theorem. Specifically, for the two-users simple input, simple output (SISO)-IC, they propose two optimal signalling schemes to achieve the Pareto boundary in situations of employing PGS and IGS, respectively. In these optimal signalling schemes, the transparent geometric model which takes less computational complexity is applied to calculate the optimal transmission parameters for the Pareto boundary. Numerical simulation results show that the proposed IGS strategies can achieve larger achievable rate region and a greater sum rate. Finally, the authors give an in-depth discussion about the structure of the Pareto boundary, which is characterised by the degree of impropriety measured by the covariance and the pseudo-covariance of signals.

The multi-radio–multi-channel wireless mesh networks (MRMC WMNs) have attracted much attention due to their low cost, reliable coverage, stable topology, and so forth. Load balancing among gateways (GWs) is a challenging task in MRMC WMNs. The GW nodes with higher loads will lead to disconnected network. GW and shortest path selection may increase traffic concentration which leads to congestion and collision in network. In this study, a multi-objective competitive swarm optimiser (MO-CSO) with analytic hierarchy process-based (AHP) load-balancing technique is proposed among the multiple GW nodes that provide communication between server and user to select the lightly loaded GWs, so that more packets will be delivered to the fixed host in Internet. The proposed method selects four GW parameters that are GW connecting degree, GW capacity indicator, traffic in collision domain, and path cost. The objective functions are minimisation of delay and maximising the channel utilisation, network throughput, and balancing network traffic. The MO-CSO with AHP method is utilised to select the best GW and path which combines all four parameters. Simulation results show that the proposed MO-CSO improves the network performance by maximum throughput while compared with the existing routing strategies such as SBR, ETX, LG, NG, and IR.

This study focuses on an efficient fairness aware beam allocation strategy which is based on user position approach. The proposed algorithm is efficient to cope with the effects of user position uncertainties and imperfect channel state information (CSI). It allocates beam to individual users based on directivity and user position with the objective of serving many users simultaneously. On the basis of the user position, individual data rate requirements are also considered in the proposed scheme which is very much important for practical systems thereby considering the fairness issue amongst the users. The proposed scheme is best suited for a system with covariance-based beamforming, where statistical CSI is highly preferred under high dense deployments and the channel coherence time is short. It also requires low average feedback load with less multiuser interference and is of low complexity compared with the searching-based beam allocation strategy. The simulation results are given to show the advantage of the proposed beam allocation on comparing with the prevailing schemes.

Interleaver design has been an intense research area since the invention of turbo codes, both from theoretical and technological perspectives, still receiving the attention of engineers. This work is a theoretical treatment on the subject of interleaver design, bringing into focus the odd-even constraint. Odd-even interleavers constrain information symbols at odd (even) positions to remain at odd (even) positions after interleaving. Having been adopted in a range of operational communication standards as parts of turbo codes on the one hand, and having raised scepticism about their gain in the literature of turbo trellis-coded modulation on the other hand, these interleavers have motivated the present article. Concretely, the authors perform a bit-error analysis of turbo-code ensembles generated by the odd–even uniform interleaver, following the union-bound approach by Benedetto et al. for the analysis of the uniform interleaver. They find that the odd–even constraint does not affect the interleaver gain of uniform-interleaver ensembles; rather, it triggers a redistribution of multiplicities that leads to slightly worse performance mainly in the error-floor region. The authors' findings are corroborated by bit-error-rate simulations.

In the era of internet-of-things (IoT), many applications utilise wireless sensor networks (WSNs) including smart grids (SGs). Designing WSNs to fulfill the SGs requirements imposes some challenges such as limited power and signal propagation impairments, especially, in harsh environments. Consequently, saving power consumption in WSNs-based SGs is among the most significant challenges. The total power required at a certain sensor depends on two main parameters: the packet length and inter-node distance. This paper investigates the optimal packet length and inter-node distance to be utilised in a SG over six different environments aiming at maximising the network lifetime. The investigation is based on a link-layer model using Tmote Sky nodes taking into consideration the six environments impact. A mixed-integer programming (MIP) model is utilised to determine the best packet length and number of nodes for maximising the network lifetime. This model analyses the performance of maximum SG network lifetime over those environments and addresses the inter-node distance effect on the network lifetime maximisation. Simulation results show that decreasing the number of nodes covering a certain area is preferable to prolonging the network lifetime. Furthermore, for the considered models, the longer the packet length is, the longer the network lifetime will be.

Beam hopping (BH) is the key technology to improve the system throughput and decrease the transmission delay in multibeam satellite systems. The objective of this study is to find a policy to maximise the expected long-term resource utilisation. The BH illumination plan (BHIP) optimisation problem aimed at minimising the transmission delay is formulated and modelled as a partially observable Markov decision process. To tackle the issue of unknown dynamics and prohibitive computation, an artificial intelligence method named deep reinforcement learning (DRL) is first proposed to solve the BHIP problem in multibeam satellite systems. The proposed DRL-BHIP algorithm considers a series of realistic conditions, including the traffic demands in spatial distribution and temporal variation, ModCod constraints, antenna radiation pattern and inter-beam interference. The state reformulation concept is adopted to characterise the traffic spatial and temporal features. Simulation results show that the proposed DRL-BHIP algorithm can decrease the transmission delay and improve the system throughput compared with existing algorithms.

The authors consider a content-centric two-tier heterogeneous cellular network where the macro base stations (MBSs) and small base stations (SBSs) are spread based on two independent Poisson point processes. The set of contents are stored in the MBSs while a subset of the contents which are the most popular are cached in the SBSs. We assume that there is no direct link between the MBSs and the users, and users send their content requests to their nearest SBS. If the SBS has not the requested content, the nearest MBS to the serving SBS serves the user through that SBS. Furthermore, the authors incorporated the automatic repeat request (ARQ)-based transmission with a fixed number of the ARQ rounds, and analyse the delay experienced by users. The authors obtained closed-form expressions for the average outage probability and the average delay in case of successful ARQ transmission. It is shown that the content distribution based on popularity decreases the average outage probability and average delay. Also, it is shown that the transmission from MBS to the user through SBS improves the performance in terms of average outage probability and average delay. Finally, using simulations the authors study the proposed schemes for different network parameters.

The addition of analogue processing to the digital precoding, known as hybrid beamforming (HB), is an efficient solution for massive multiple-input multiple-output (MIMO) systems. The design of a phase shifter (PS) network plays an important role in the complete precoder operation because it necessitates accurate components for realising precise phases, and that can be costly. Finite resolution PSs are good alternatives because they need simpler hardware implementation than those with infinite resolution. However, the degradation of performance of a MIMO system with very low-resolution PSs is significant. Although recent studies suggest adding extra radio frequency (RF) chains to substitute for the accuracy of the PSs, it is complex, expensive and not energy efficient. This study demonstrates that HB with low-resolution PSs can realise a high performance without increasing the number of RF chains. The authors proposed solution relies on a proper selection of the weights of the RF beamformer, hence exploiting the structure of the multipath propagation channel to maximise the system capacity. They also show that separating antennas from each other by sufficient distance, results in a less correlated channel, and thus, a minimal loss in the capacity and the antenna gains are assured.

Mobile crowdsourcing-based applications, widely popular, exploit the sensing data crowdsourced from smartphone users without putting any burden on the extra cost of data sensing and collection. However, user participation in crowdsourcing incurs resource cost, such as battery, bandwidth, thus it is critical to design incentive mechanisms for propelling user's participation. Previous diverse incentive mechanisms designed for crowdsourcing applications only focus on users' contribution for reward allocation, while ignore another important property, i.e. fairness, users' reward should be corresponding with their cost. In this study, the authors first introduce a new concept called rate of return (RoR), defined as the ratio of received reward and incurred cost for each user, to demonstrate the property of fairness. With the goal of guarantee, the fairness of reward allocation for each user in a multiple-task system, three algorithms, consensus-based reward allocation, consensus-based balanced topology reward allocation and Gossip-based reward allocation are proposed for the demands of various scenarios, in which the RoR values are synchronised by optimising the fairness function in either centralised or decentralised manner. Through rigorous theoretical analysis and extensive simulations, it is finally demonstrated that the proposed reward allocation algorithms have the good property of fairness with quick convergence.

Low-density parity-check (LDPC) codes and compressed sensing (CS) share many common environments. In this study, a novel approach for constructing a new class of deterministic sparse sensing matrices based on array quasi-cyclic (QC) LDPC codes via Singer perfect difference sets is proposed. In contrast to random and the other deterministic matrices, the proposed framework would be highly desirable as it is generated based on circulant permutation matrices, which requires less memory for storage and lower computational cost for sensing. Since the restricted isometric property is very difficult to verify, then the mutual coherence and the girth are two computationally tractable criteria that the authors used to assess the CS recovery capabilities of sensing matrices. In addition, inspired by LDPC codes, they extract a necessary condition for the proposed measurement matrix to have effective values for girth as large as . Comprehensive one-dimensional (1D) and 2D simulations verify that their proposed sensing matrix has minimum coherence and superior CS recovery abilities in comparison with the corresponding random Gaussian, Bernoulli, and the other deterministically generated matrices. Furthermore, the required physical storage space and the complexity of the hardware implementation are greatly reduced due to being sparse and QC in structure.

A system for the correlated Gaussian sources to perform compression forwarding via the multi-relay network in the additive white Gaussian noise channel is proposed in this study. The characteristic of the newly proposed system is that it is composed of two parts: an analogue sensor network from the sources to multiple relay nodes and a digital communication network from multiple relay nodes to the destination node. The sensors can only perform simple analogue signal transmission, but the encoder set up at each relay can carry out complex distributed source coding DSC and then send the coded digital signals to the destination node. In this study, the authors establish the rate–distortion function of DSC based on the Chief Executive Officer problem. Combined with the channel capacity theorem, an optimal power allocation scheme is first proposed. The quantisation signal-to-noise ratio (SNR) at the destination node is used to evaluate the performance of the system under different correlations between sources. For the case of independent sources, a closed-form expression for the quantisation SNR is derived and they compare the optimised agent compress-and-forward system with the traditional amplify-and-forward system to verify that the proposed system can achieve better SNR performance.

The large demand for smart metering and control, asset tracking, remote monitoring, and other applications has resulted in the emergence of innovative new internet of things (IoT) low-power wide-area networks (LPWANs) featuring low power consumption, low cost, high scalability and low data rate transmissions. This article compares the performance of LoRaWAN, Sigfox, and NB-IoT as emerging technologies, in terms of power consumption, throughput, scalability, and range. For practical reasons, the comparison also includes cellular GPRS. Although GPRS does not fit the description of LPWAN technologies, it is a legacy method for IoT communications and provides insight into application areas where LPWAN technology can be applied. The study gives a clear comparative overview of the advantages and shortcomings of the various communication networks and highlights the most suitable applications cases for each technology on the basis of the tested metrics.

In vehicular ad hoc networks (VANETs), mobility among vehicles can result in rapid topology changes with frequent link breakage and unstable communications, which cause collision and packet loss. Conversely, cooperative transmission can improve communication reliability and can enhance communication rate with lower delay by alleviating wireless channel impairments caused by mobility in VANETs. In this study, a novel reliable and efficient cooperative medium access control protocol for VANETs (RECV-MAC) is proposed. Since a random access mechanism is suitable and efficient because of the dynamic and open nature of VANETs, authors used the random access approach, i.e. carrier sense multiple access with collision avoidance, which is used by IEEE 802.11p. The RECV-MAC protocol is compatible with IEEE 802.11p. New control messages are introduced to support cooperative communication. The mechanism is defined to choose suitable transmission mode as well as to select optimal helper. To investigate the performance of RECV-MAC protocol, Markov chain model-based analytical analysis is provided. The RECV-MAC protocol is validated by numerical results which demonstrate that RECV-MAC protocol improves the performance with higher throughput, enhances the reliability of communication by decreasing packet dropping rate (PDR), and decreases delay, in particular, satisfies the delay constraint of 100 ms for sm.

The applicability of cognitive radio (CR) techniques into satellite communications has received considerable attention in recent years. This study considers the integration of relay transmission into CR-based satellite terrestrial network, which offers the advantages of not only increasing the overall spectral efficiency by spectrum sharing but also extending the wireless coverage through the deployment of relays. Specifically, the authors derive the exact closed-form expression of the outage probability (OP) for the cognitive network, which provide an efficient means to evaluate the impact of key parameters on the system performance. Furthermore, the asymptotic OP expression at high signal-to-noise ratio is presented, which reveals the achievable diversity order and coding gain of the considered network. Finally, numerical results are carried out to validate the theoretical results, and shows that although a higher transmit power or weaker shadowing severity of the satellite interference link has a severe detrimental impact on the outage performance of the cognitive network by reducing the coding gain, the achievable diversity order only depends on the fading severities and the number of relays of the cognitive network.

In this paper, analytical performance of efficient soft-data combining schemes (SDCSs) for cognitive radio network (CRN) is investigated. The performance is investigated in the presence of noise and generalized fading. In more detail, each CRU senses the PU and reports its sensing information to the fusion center (FC). At FC, different SDCSs, which differ in process of fusing the sensing data, are implemented to make the global decision on the status of a PU. In the present work, first the novel mathematical expressions, subject to SDCS and fading are derived. Next, the performance is evaluated through receiver operating characteristics (ROC) and average error rate (AER), considering the significant impact of network and channel parameters. The performance of hard-decision combining schemes (HDCSs) is also studied for comparison purpose. The analysis presented in this paper eliminates the need of analysis of SDCSs over individual fading channels. An optimal sensing threshold and an optimal number of CRUs where AER attains its minimum value are also determined for all HDCSs and SDCSs. Finally, the derived expressions are validated by computer based simulations for several parameter values of the network.

Fountain codes are promising forward error correction codes suitable for broadcast and multicast applications where many users with different capabilities are involved in the system. Fixed-rate codes need a priori information about each channel to decide the best code rate and the code rate is usually chosen according to the worst channel to avoid an outage. Fountain codes are agnostic to the channel conditions and rateless. The rate is realised based on the channel conditions for users separately. Overlapped fountain codes were previously invented over the binary erasure channel to provide more degrees of freedom and better trade-offs for the rateless-coded system parameters. In this study, the authors show via analysis and simulations that overlapped fountain codes need fewer decoding steps in comparison with the conventional fountain codes. For example, overlapped fountain codes reduce the number of decoding steps/iterations of belief propagation decoder by even at a source length . They optimise the overlap selection probability of the overlapped fountain codes to maximise the code rate and/or minimise the complexity. At source length, , the proposed analytical and simulation studies show that the highest code rate and lowest average complexity are achieved at an overlap selection probability .

Designing a new pulse-shaping filter that satisfies the Nyquist condition to mitigate inter-symbol interference and achieve better stopband attenuation is a new step towards the development of next-generation mobile communication systems. In this study, the authors propose a novel Nyquist filter based on the convolution of a rectangular and a truncated sinc pulses. Introducing two-time parameters in the filter function provides more degrees of freedom and high flexibility to shape different Nyquist pulses. Four Nyquist pulse shapes are introduced, examined in terms of time and frequency characteristics, and compared with those of the two most popular pulses in the literature: root-raised cosine (RRC) and PHYDYAS. The results demonstrate an improvement in the eye pattern, impulse response, and spectrum behaviours. The error rates are evaluated over a noisy channel, and the new pulses offered better performance than PHYDYAS and RRC. The intrinsic interference was examined by determining the autocorrelation and cross-correlation coefficients of the prototype filters in the frequency-time grid. The results for the proposed filters portray good interference confinement either in time or frequency axis. The reduction in the out-of-band emission makes the proposed filter an efficient candidate for future filter bank multicarrier scheme.

Cellular users on-board vehicles often experience low quality of service (QoS) due to the vehicular penetration loss. Hence, the so-called mobile-cells (MCs) have been proposed as a solution. The envisaged MCs will require additional radio resources, which will lead to poor spectral efficiency. This study proposes new methods by which MCs can share the resources of the other links. Firstly, this study presents resource sharing algorithms according to which, MC's access-link (AL) will share resources either with the backhaul-link (BL) or with a conventional user. Secondly, it proposes a scheme for controlling AL transmit power to reduce the interference caused to BL while maintaining the QoS for the in-vehicle users.

In a conventional cellular network underlaid with femtocells, the authors employ interference alignment (IA) to restrict cross-layer co-channel interference (X-interference). In their scenario, locally obtained channel state information is allowed to be conveyed between heterogeneous nodes to construct a decentralised IA-based scheme. Furthermore, they provide closed-form formulas for the upper bounds of X-interference in both uplink and downlink directions and characterise how they asymptotically approach zero for big enough channel dimensions used by individual nodes. Simulation results demonstrate that X-interference is always bounded by the above-mentioned limits and prove accuracy of their analytical formulas.

In this study, the authors investigate the security and reliability trade-off (SRT) performance of a multiuser wireless network, where an eavesdropper attempts to overhear the confidential transmissions between a base station and multiple users under the impact of co-channel interference. To enhance the SRT performance of the network, the authors propose two joint user and jammer selection schemes, namely the joint optimal user and random jammer selection (JOU-RJS) scheme and the joint optimal user and optimal jammer selection (JOU-OJS) scheme. For SRT performance comparison purposes, the traditional multiuser scheduling (TMUS) scheme is also considered. The authors derive closed-form outage and intercept probability expressions for the JOU-RJS and JOUOJS schemes. Simulation results show that the SRTs of both JOU-RJS and JOU-OJS schemes are better than that of the TMUS scheme, where JOU-OJS achieves the best SRT performance. Additionally, this study also shows that an expected outage or intercept probability of the TMUS, JOU-RJS, and JOU-OJS schemes can be achieved by giving an appropriate overall rate. Finally, the sum of the outage and intercept probability can be minimised through an optimal power allocation between the selected user and friendly jammer for the proposed JOU-RJS and JOU-OJS.

Voice over Internet Protocol (VoIP) networks have recently emerged as a promising telecommunication medium for transmitting voice signal. One of the essential aspects that interests researchers is how to estimate the quality of transmitted voice over VoIP for several purposes such as design and technical issues. Two methodologies are used to evaluate the voice, which are subjective and objective methods. In this study, the authors propose a non-intrusive machine learning-based (NIML) objective method to estimate the quality of voice. In particular, they build a training set of parameters – from the network and the voice itself – along with the quality of voices as labels. The voice quality is estimated using the perceptual evaluation of speech quality (PESQ) method as an intrusive algorithm. Then, the authors use a set of classifiers to build models for estimating the quality of the transmitted voice from the training set. The experimental results show that the classifier models have a valuable performance where Random Forest model has superior results compared to other models of precision 94.1%, recall 94.2%, and receiver operating characteristic area 99.2% as evaluation metrics.

In this study, the authors propose a novel three-dimensional (3D) non-stationary geometry-based stochastic model (GBSM) and the corresponding deterministic and stochastic simulation models for non-isotropic unmanned aerial vehicle (UAV) multiple-input multiple-output (MIMO) Ricean fading channels. The proposed GBSM employs a two-cylinder model, where the signal is a superposition of line-of-sight component, single-bounced rays around the UAV, single-bounced rays around the ground station (GS), single-bounced rays on the ground, and double-bounced rays. The non-stationarity is reflected on the time-varying angles of departure and angles of arrival. Since the authors consider the GS to be mobile, the proposed 3D GBSM is general and suitable for UAV-aided vehicular communication scenarios. Based on the proposed model, some important channel statistical properties are derived and thoroughly investigated, including the space-time correlation function, Doppler power spectral density, envelope level crossing rate and average fade duration. Moreover, the proposed model has the ability to investigate the influence of some unique UAV-related parameters on channel characteristics and non-stationarity. Finally, excellent agreement is achieved between the reference model and simulation models, demonstrating the feasibility of simulation models as well as the correctness of theoretical derivations.