Wireless backhaul is a promising technology to lower the cost for connecting a large number of densely deployed access points in the emerging fifth generation wireless system. In this study, the authors consider the joint optimisation of resource allocation in wireless backhaul links and user-centric clustering in the access links. The objective is to maximise the weighted sum rate of all users under the backhaul resource constraints. To solve this intractable problem, they first adopt the ℓ₁-norm approximation approach to convert the non-convex backhaul constraints into the solvable forms. They then reformulate the objective function as a set of second-order cone constraints based on the sequential parametric convex approximation method. An iterative algorithm is proposed to solve the transformed problem based on its special property. Simulation results show that the proposed algorithm outperforms other existing schemes under different network settings.

Being one of core characteristics for 5G cellular networks, ultra-dense small cell network is an effective approach to reuse the spectrum and achieve high data rate transmission in the wireless communication networks. However, because of sharing the spectrum resources, the interference problem among the macrocell base stations (MBS) and the small cell base stations (SCBSs) is hard to address. In this study, the authors model the scenario as a Stackelberg game, where the MBS act as the leader and all SCBSs act as followers. In the game, the MBS set its interference penalty price first, based on the prices the MBS then determines its channel allocation schemes to all SCBSs. Observing the interference penalty price and the amount of allocated channels performed by the MBS, each SCBS then determines its transmit power to achieve its optimal utility. Because of the first-move advantage, the MBS is able to predict the reactions of each SCBS and make optimal strategies. Simulation results show the correctness of the analysis and the significant benefits when the power control and channel allocation are jointly considered in the proposed schemes.

A device-to-device (D2D) discovery scheme is key enabler for proximity-based services in third generation partnership project long-term evolution-advanced systems for public safety (PS) and general LTE scenarios. The deployment of D2D networks results in severe co-channel interference between conventional cellular users and D2D users, and faces proximity interference management challenges because of the co-existence of multiple D2D users. We propose a time and energy-efficient contention-resolving device discovery resource allocation (TEECR-DDRA) scheme that has the capability to enhance the success ratio for discovery of D2D users by reducing collisions among users. Moreover, the proposed TEECR-DDRA scheme has the ability to prioritise PS users to meet their QoS and latency requirements. Furthermore, multi-channel slotted ALOHA with energy sensing can be used to increase the probability of successful discovery of non-PS users. This ability helps to reduce the discovery time of PS users under disaster scenarios, and also reduces the energy consumption of non-PS users by minimising the number of beacon retransmissions. System-level simulations show that the proposed TEECR-DDRA scheme performs remarkably well under D2D network. Compared with the conventional random access scheme, the proposed scheme almost doubles the discovery range and significantly improves the success ratio for discovery of D2D users.

Recently, nodes cooperation has emerged as a popular means for improving the quality of multimedia delivery over fifth-generation cellular networks. However, in the conventional relaying scheme such as amplify-and-forward (AaF), there is a higher probability of duplicate packets at the receiver node which affect the decoding probability and consequently deteriorate the quality of multimedia transmission. In this study, the authors propose a cooperative multimedia transmission protocol based on a novel merge-and-forward relaying and the best relay selection (RS) schemes. Their best RS scheme is based on two important parameters: (i) two-hop link distances and (ii) minimum block error rate value. Moreover, to combat the packet loss for enhanced and reliable video delivery, they adopt application layer forward error correction scheme which is based on the most improved and advanced version of fountain codes (i.e. RaptorQ codes). They evaluate the performance of the proposed scheme under different time-sharing scenarios between the direct and best indirect transmission links in terms of decoding failure probability, decoding overhead, peak signal-to-noise ratio, and mean opinion score. Simulation results show that the proposed scheme outperforms the conventional AaF relaying scheme.

This study investigates the cross-tier base station (BS) cooperation in non-uniform heterogeneous networks where the distribution of pico BSs (PBSs) is modelled as Neyman–Scott cluster process. The authors propose an edge aware cross-tier cooperation scheme to improve the performance of edge hotspot users that have weaker signal-to-interference-plus-noise ratio (SINR). Taking consideration of various user behaviours, non-hotspot users are only served by the nearest macro BS whilst the hotspot users with better SINR are only served by their serving PBSs. The edge hotspot users who suffer from high cross-tier interference operate in the cooperation mode. Stochastic geometry is utilised to derive the SINR and energy efficiency performance of the proposed scheme, which is compared with other classical schemes such as full cooperation (FC) and traditional non-cooperation scheme. Numerical results show that compared with the FC scheme, the proposed scheme can maximise the energy efficiency of the network by an optimal cooperation threshold, when SINR coverage is larger than a threshold. The authors also find that user behaviour have little effect on the tradeoff between SINR Coverage and energy efficiency, unless spatial aggregation coefficient is very small.

The authors study the secure transmission design in random cognitive radio networks where the primary users, the secondary users and the eavesdroppers are randomly distributed according to Poisson point processes. Centring on this scenario, the authors propose a simple and decentralised secure transmission scheme by jointly incorporating the secrecy guard zone and artificial noise. In particular, this transmission scheme helps to enhance secrecy performance via differentiating between secondary transmitters in accordance with the eavesdropping environment. They then analyse the connection outage and secrecy outage performance of the secondary network, based on which they obtain the closed-form expression of the secrecy throughput. They further determine the optimal transmission power of the secondary transmitters and the optimal power allocation between the information-bearing signal and artificial noise to maximise the secrecy throughput of the secondary network under primary and secondary outage constraints. The authors’ analysis highlights that introducing secrecy guard zone provides better security performance, and artificial noise performs as additional interference to insert a control between the reliability and security. Numerical results show how the system parameters affect the achievable maximum secrecy throughput, the optimal transmission power and the optimal power allocation between the information-bearing signal and the artificial noise.

In this study, the authors investigate the spectrum sharing and interference management in hyper-dense cloud radio access networks (C-RANs). The authors formulate this problem as a local altruistic coalition formation game (LACF) with externalities. Different from previous studies considering maximising individual small cell's throughput, the authors’ purpose is to maximise the social welfare, i.e. the sum satisfaction of remote radio heads (RRHs) with diverse traffic types. The authors design a local altruistic utility function for RRH, i.e. each RRH cares about not only his own interest but also his neighbours’. They make autonomous decisions, finally shaping the entire RRHs into multiple disjoint coalitions. In addition, joint transmission coordinated multi-point technology is considered within coalition to mitigate interference. Then, the authors propose a distributed coalitional formation algorithm based on modified recursive core to obtain the final stable coalition partition. Furthermore, the system stability, convergence and complexity of the proposed algorithm are analysed. Numerical results show that the proposed algorithm outperforms the classical and non-cooperation schemes in the perspective of both social welfare and individual fairness. To be specific, the average rate per RRH of the authors’ proposed scheme is superior to the classical and non-cooperation cases by 20 and 25% in hyper-dense scenario, respectively.

In recent years, coordinated beamforming (CBF) has attracted considerable attention because of its effectiveness in intercell interference (ICI) mitigation. To facilitate the operations of CBF for the frequency-division duplex mode, efficient channel state information (CSI) exchanges through backhaul links are necessary. In previous studies, uniform quantisation of CSI has been generally assumed in feedback schemes. Statistically, however, uniform quantisation may not be optimal from the viewpoint of the ICI in CBF, which is mainly caused by the quantisation error (QE). This study proposes a low-complexity cumulative distribution function (CDF)-based non-uniform quantisation method with a limited number of feedback bits for applying more quantisation levels to represent feedback CSI, which occurs with higher probability. This is because a more accurate representation of frequent CSI can lead to a lower QE for reducing the ICI level in most cases. To prove the effectiveness of the proposed CDF-based quantisation scheme, the ICI in the considered two-cell CBF scenario was analysed using several feedback bits. The simulation results proved the higher transmission rate, particularly in cases with fewer feedback bits.

In this study, the authors study the self-organising user assignment problem for the multi-user cooperation network. In the cellular network with user cooperation, idle users near the base station are seen as potential relay nodes, which can assist cell edge users to transmit data. Practically, the selfish nature of users is considered in the authors’ model. They design a score-based system, where the strategies of relay assignment are affected by the historical behaviours of users. That means not only the transmission performance, but also the accumulative contributions of users are considered. The proposed score-based system sufficiently encourages idle users to assist active users. Furthermore, the multi-user assignment problem is formulated as a one-to-one matching game, in which idle users and active users rank one another individually based on their own preference. To address the issue, they propose a self-organising mutually beneficial matching algorithm, which is proven to converge to a stable matching. Simulation results show that the proposed distributed algorithm yields well matching performance between source users and relay users, which is close to the optimal centralised results.

Massive multiple-input multiple-output technology has been considered a breakthrough in wireless communication systems. It consists of equipping a base station with a large number of antennas to serve many active users in the same time–frequency block. Among its underlying advantages is the possibility to focus transmitted signal energy into very short-range areas, which will provide huge improvements in terms of system capacity. However, while this new concept renders many interesting benefits, it brings up new challenges that have called the attention of both industry and academia: channel state information acquisition, channel feedback, instantaneous reciprocity, statistical reciprocity, architectures, and hardware impairments, just to mention a few. This paper presents an overview of the basic concepts of massive multiple-input multiple-output, with a focus on the challenges and opportunities, based on contemporary research.

In this study, an energy harvesting (EH)-based cooperative non-orthogonal multiple access (NOMA) system is considered, where node S simultaneously sends independent signals to a stronger node R and a weaker node D. The authors focus on the scenario that the direct link between S and D is too weak to meet the quality of service (QoS) of D. Based on the NOMA principle, R, the stronger user, has prior knowledge about the information of the weaker user, D. To satisfy the targeted rate of D, R also serves as an EH decode-and-forward relay to forward the traffic from S to D. In the sense of equivalent cognitive radio concept, R viewed as a secondary user assists to boost D’s performance, in exchange for receiving its own information from S. Specifically, transmitter beamforming, power splitter and receiver filter are jointly designed to maximise R’s rate with the predefined QoS constraint of D and the power constraint of S. Since the problem is non-convex, they propose an iterative approach to solve it. Moreover, a zero-forcing based low-complexity solution is also presented. Simulation results demonstrate that, both two proposed schemes have better performance than the direction transmission.

This study discusses synchronisation in phase noise-impaired spectrally efficient communication systems employing high-order modulations. In particular, an iterative receiver, where demodulation and decoding are separate from maximum a posteriori probability (MAP) synchronisation, is presented. The authors’ separate approach is tailored to the design of pragmatic iterative receiver schemes employing ‘off-the-shelf’ demodulation and decoding blocks. This allows full compatibility with already existing systems, which is attractive from the implementation viewpoint. The proposed MAP synchronisation algorithm also requires very limited knowledge of the phase noise process and achieves near coherent performance with moderate computational complexity. Although the approach is very general, the authors discuss its performance for low-density parity-check-coded pilot symbol-aided quadrature amplitude modulation schemes, demonstrating that a significantly lower computational complexity can be achieved with respect to benchmark joint receivers.

Coordinated beamforming designs based on energy efficiency of multiple-user interference channels have attracted much attention. The optimisation problem has a fractional form, and is coupled among users, which makes it difficult to be solved directly. A beamforming design for energy-efficient communication in multiple-input–single-output interference channels is studied, and proposes an efficient distributed approach to solve it. A novel method is developed to transform the optimisation problem into a DC (difference of two convex/concave functions) structure. The transformed optimisation problem is approximated by using a separable structure across the users, and this approximated version is solved iteratively. Numerical results show the effectiveness of the authors’ proposed algorithm.

In this study, a playout buffer and discontinuous reception (DRX) aware scheduling scheme (PBDAS) is proposed to improve the video streaming transmission over the long term evolution systems by considering the characteristics of both the DRX mechanism and the HTTP streaming. First, to reconcile the three mechanisms, the metric called remaining playout time (RPT) is proposed, which can be used to estimate the playout status of the clients. With the RPT, the scheduler can accurately differentiate the urgency among the clients. Then, a two level resource allocation schemes is proposed. In the scheduler, the upper level is responsible for determining the scheduling set, while the lower level will be in charge of allocating the resource to the user equipments (UEs) in the set. With the scheduling set, the priority of the UEs can be accurately distinguished. For different scheduling set, different forms of metrics are designed, with which both the efficiency of the radio resource and the playout continuity can be significantly improved. In addition, a playout buffer level estimation method is given to improve the feasibility of the implementation of PBDAS. By analysing the behaviour of the playout buffer, the buffer level can be estimated with the cumulative serving rate and the HTTP streaming information, which can be obtained in the eNodeB and from the quality of experience reports, respectively. The simulation results show that PBDAS can shorten the total interruption duration of the existing schemes by about 50% as well as keep the power consumption at a low level.

In this study, the authors study simultaneous wireless information and power transfer for multiuser multiple-input–single-output secure multicasting channels with imperfect channel state information. First, a robust secure beamforming design is considered, where the transmit power is minimised subject to the secrecy rate outage probability constraint for legitimate users and the harvested energy outage probability constraint for energy harvesting receivers. The original problem is non-convex due to the presence of the probabilistic constraints. By utilising Bernstein-type inequalities, the authors transform the outage constraints into the deterministic forms. In order to identify a local optimal rank-one solution, the authors propose an efficient approach based on a constrained concave convex procedure method to convert the original problem into a sequence of convex programming problems. Finally, simulation results are provided to validate the performance of the proposed design methods.

This study proposes a novel adaptive stochastic radio access selection scheme for mobile users in heterogeneous cellular-wireless local area network (WLAN) systems. In this scheme, a mobile user located in dual coverage area randomly selects WLAN with probability of ω when there is a need for downloading a chunk of data. The value of ω is optimised according to the status of both networks in terms of network load and signal quality of both cellular and WLAN networks. An analytical model based on continuous time Markov chain is proposed to optimise the value of ω and compute the performance of proposed scheme in terms of energy efficiency, throughput, and call blocking probability. Both analytical and simulation results demonstrate the superiority of the proposed scheme compared with the mainstream network selection schemes: namely, WLAN-first and load balancing.

In this study, the authors study energy-efficiency (EE) optimisation of three-node multiple-input–multiple-output wiretap channels. In particular, they aim to maximise EE by optimising the transmit covariance under the constraint of transmit power consumption. Such optimisation problems are non-convex and difficult to solve. Here, they propose a novel optimisation algorithm, which is very different from previous approaches, with guaranteed convergence to the Karush–Kuhn–Tucker point. In particular, through a channel improvement argument and an intelligent bounding technique, they first obtain a min–max reformulation of their original problem. Then, based on the idea of alternative optimisation, they derive two sub-problems from it. To solve these two problems, they used the efficient barrier Newton and the gradient projection methods. The outcome from this last step is a semi-closed-form solution for the two sub-problems. The numerical results obtained from the proposed algorithm represent better performances than the existing methods.

In this study, the authors address the problem of beamforming and combining based amplify-and-forward relaying in a satellite communication system in which two earth stations (ESs) with multiple antennas communicate via a single antenna based satellite relay. The transparent satellite is used to relay the received signals from one ES to other ES. Both ESs are assumed to be geographically separated by a very large distance, therefore, no direct path exists in between the ESs. The ESs-satellite links are assumed to follow the κ − μ shadowed fading. A closed form expression of moment generating function (MGF) of the instantaneous received signal-to-noise ratio at destination ES is derived. An expression for the symbol error rate of the considered system is obtained by using the expression of MGF. The analytical diversity order of the system is also obtained by using an asymptotic property of the Meijer-G function. It is shown by simulation and analysis that the diversity order of the considered system is min(L ₁ μ ₁, L ₂ μ ₂), where L ₁ and L ₂ are the number of antennas at the ES-1 and ES-2, respectively.

In this study, a robust power allocation scheme with orthogonal frequency division multiplexing-based cognitive radio network is proposed to maximise total data transmission rate subject to interference power constraint of primary user (PU) and transmit power budget constraint of secondary user where channel uncertainties and spectrum sensing errors are simultaneously considered. The authors first formulate the interference model by taking the imperfect spectrum sensing into account, then the channel state information errors are considered and assumed to be bounded with ellipsoidal and interval sets to establish robust resource allocation problem. On the basis of the worst-case approach and Lagrange dual decomposition method, the original optimisation problem is converted into a convex one and solved. Simulation results show the robustness of their proposed scheme and the trade-off performance with a sub-optimal data transmission rate, but better protection of PU.

Recently, substantial attention has been paid to analyse the performance of wireless networks in the cases where the positions of the base stations are modelled by stochastic geometry. In this study, the authors analyse the performance of Rayleigh-fading Poisson-point-process (PPP)-based networks. They derive the optimal transmission rate that maximises the per-user throughput. Also, they determine sufficient conditions for positive diversity gain in PPP-based networks, develop tight approximations for the effective density of the network and give a simplified expression to calculate the outage probability for the interference-limited case. The analytical and the numerical results demonstrate considerable potential for efficient data transmission in PPP-based networks.

The aim of this study is to design a receiver architecture which can jointly estimate the frequency selective (FS) channel impulse response (CIR), frequency independent (FI)/FS Receiver (Rx) Inphase Quadrature (IQ) imbalance, carrier frequency offset (CFO) and direct current offset using long training sequences. All of these problems are typical for low-cost radio-frequency front-ends. This study proposes a set of two scalable solutions to estimate CFO, whereas FS CIR and FI/FS Rx IQ imbalance are estimated in tandem through a closed-form expression. A low-complexity single stage equaliser is also proposed which can mitigate the effects of CFO and equalise the CIR along with FI/FS IQ imbalance in a single step. The proposed solutions are also extended to multiple-input–multiple-output-orthogonal frequency division multiplexing systems. The simulation results illustrate that solutions proposed in this study provide an excellent performance/complexity trade-off.

Cellular networks are of particular interest when communication takes place. The main barrier of employing cellular networks to reach broad access everywhere is interference. Although interference alignment has by theory raised hopes to leap this last hurdle, however, no operator will show interest for practical implementation of the complicated algorithms proposed so far, especially considering the need for global channel knowledge. Besides, there is no measure to appraise the performance of existing algorithms. In this study, the authors study blind cellular networks to characterise their achievable degrees of freedom. As it is very hard – if not impossible – to obtain its exact value, they provide related upper and lower bounds for this special scenario when power control mechanism is applied in the network. They also propose constructive proof for the lower bound and offer their seminal blind resource allocation algorithm in which they utilise concepts of both frequency alignment and fractional frequency reuse. Analytical upper bounds are also proposed and proved to be tight with respect to simulated results.

In this study, the authors investigate the physical-layer security in a cognitive amplify-and-forward relay network consisting of a secondary transmitter (ST) and a secondary destination (SD) with the aid of multiple secondary relays (SRs) in the face of multiple eavesdroppers. In cognitive radio networks, increasing transmit power may not always be beneficial in terms of improving the channel capacity of cognitive transmissions, which would not only cause an extra interference to primary user, but also enhance the possibility of successfully intercepting the cognitive transmissions at an eavesdropper because an improved signal strength is received in this case. The authors propose two relay selection schemes to improve the physical-layer security of cognitive transmissions against eavesdropping attacks, which are referred to as the global and partial channel state information based relay selection, denoted by GCSIbRS and PCSIbRS, respectively. The authors analyse the intercept probability of the proposed GCSIbRS and PCSIbRS, as well as the traditional round-robin and all-relay transmission schemes. It is shown that the proposed GCSIbRS and PCSIbRS schemes both outperform the conventional round-robin and all-relay schemes in terms of their intercept probability performance.

The authors report a numerical investigation of a non-stationary noise model, based on the generalised autoregressive conditional heteroscedasticity time series, to perform a direction-of-arrival (DOA) estimation. In many of the studies reported to date, DOA estimation algorithms have been proposed in the presence of stationary noise. The performance of the previous algorithms such as conventional maximum likelihood (CML) and iterative maximum likelihood (IML) is reduced in many practical applications such as sonar where the noise shows a non-stationary behaviour. In this study, a modified IML estimation algorithm is proposed to include a non-stationary noise model. Underwater DOA estimation is studied as an example of DOA estimation in a non-stationary noise environment. To validate the noise model, the experimental data, measured by a single hydrophone 27 m underwater, is applied. The results indicate that the proposed algorithm is able to provide a significant improvement compared with CML and IML in such environments.