Joint link and power allocation for device-to-device (D2D) communication underlaying cellular networks are necessary to coordinate the mutual interference. Most of the works consider the sum interference from D2D pairs. However, mobile devices are carried by human beings who are connected with social ties. For one cellular user, the strengths of the social ties with D2D pairs are different. Thus, his interference tolerance temperatures (ITTs) are various. In this study, we distinguish D2D pairs through the social ties, and propose a social aware pricing-based joint link and power allocation scheme. Specifically, the base station (BS) prices the interference on every link and updates the prices according to the ITTs of cellular users. Subsequently, with the prices, the competition of D2D pairs for the links is modelled as a non-cooperative game. The authors prove the existence and the uniqueness of the Nash equilibrium (NE), and demonstrate that the NE is Pareto optimal. Moreover, an iterative decentralised algorithm is designed to solve the game. Especially, if the number of the price on one link for one D2D pair being updated is up to an upper bound, the power is forced to be 0. Numerical simulations verify the effectiveness of the authors' proposed scheme.

To cope with the tremendous growth of data traffic and obtain a given communication service with minimal energy use, traffic offloading and energy efficiency (EE) improving are two important issues to address for green cellular networks. The authors investigate downlink WiFi offloading in a heterogeneous network consisting of one long term evolution eNodeB (eNB) and multiple overlaid WiFi access points to maximise the user satisfaction of the whole system. In addition, a designed resource reallocation scheme after offloading is jointly considered to improve the EE of the eNB. In the offloading model, two constraints are considered to guarantee the rate promotion of the offloaded users and less impact on WiFi networks. Moreover, the authors transform the model into a combinatorial optimisation problem and adopt the best response (BR) algorithm based on game-theoretic approach to obtain the optimal offloading user set. Numerical results show that the proposed WiFi-offloading model can significantly improve the aggregate user satisfaction as well as EE of the eNB. Also, the BR algorithm can converge to the optimal solution same as the exhaustive search algorithm through several iterations.

As cognitive radio (CR) technologies developed, cooperative CR networks (CCRNs) have become a potential way to increase the spectrum efficiency. Moreover, as the authors face the problem of energy shortage nowadays, energy harvesting (EH) is considered to be an effective method to alleviate this problem. However, with fitful and random energy arrivals, the energy harvested from natural energy source cannot guarantee satisfactory quality of service in EH networks. Hybrid energy supplies system has emerged as a promising way to solve unstable power supply problems, which mean that the communication terminals in these networks are powered by both fixed power supply and harvested energy. In this study, they propose a novel utility-based cooperative spectrum leasing scheme for CCRNs with hybrid energy supplies. The secondary user (SU) is a cooperative relay powered largely by harvested energy extracted from the radio-frequency signal of the primary user (PU). In this way, SU can shorten the primary data transmission period, and then win the access opportunities for secondary data transmission. They formulate this model as a Stackelberg game. In such a scenario, the PU intends to enhance its revenue and save energy by cooperating with the SU, while the SU tries to improve throughput and minimise the fixed energy consumption. The Stackelberg equilibrium for the proposed scheme is analysed. The experimental results show that the utility of both PU and SU can be improved under this scheme.

Device-to-device (D2D) communication can increase network coverage, spectrum efficiency and energy efficiency (EE) within the existing cellular infrastructure, which makes it a promising architecture for the future networks. Due to the diversification of services, heterogeneous statistics quality-of-service constraints are considered in this study, where cellular users are concerned about the delay constraint and D2D user groups pay more attention to the outage probability of data transmission. The power allocation problem of cellular users can be solved by optimising the capacity-payoff power-loss game model. Upon exploiting Lagrange dual decomposition and the Newton iteration method, the power optimisation problem of cellular users is transformed into a parameter optimisation problem. Due to the limited energy resource of D2D users, EE is the focus of D2D user groups. Using fractional programming and convex optimisation techniques, energy-efficient optimal power allocation algorithms of D2D users are proposed subject to the outage probability constraint. As a result, a power allocation algorithm based on hierarchical game is conceived for efficiently solving the power optimisation problem. The simulation results show that the proposed algorithm can obtain a performance improvement compared with other algorithm and converge within a certain number of iterations.

Now, the authors’ life is full of vast amount of information, the era of information has arrived. So the content-centric networks face severe challenges in dealing with a huge range of content requests, bringing protection and sharing concerns of the content. How to protect information in the network efficiently and securely for the upcoming 5G era has become a problem. The authors propose a scheme based on a blockchain to solve the privacy issues in content-centric mobile networks for 5G. The authors implement the mutual trust between content providers and users. Besides, the openness and tamper-resistant of the blockchain ledger ensure the access control and privacy of the provider. With the help of a miner, selected from users, the authors can maintain the public ledger expediently. Also, in return, the authors share the interesting data with low overhead, network delay and congestion, and then achieve green communication.

The energy-efficient power allocation (PA) of distributed antenna system using multiple receive antennas is studied over spatially correlated Rayleigh channels. A new energy efficiency (EE) defined as the ratio of the average transmission rate to the consumed total power is presented. According to this definition, subject to the maximum power constraint, an optimal PA scheme is developed by maximising the EE. It is shown that the solution of PA in the constrained EE optimisation does exist and is unique. A Newton method with iterative algorithm is proposed to attain the PA. To avoid iterative calculation of the optimal scheme, a suboptimal PA scheme is derived by means of the Lambert function. As a result, closed-form PA is obtained. The developed schemes only need the statistical channel information and large scale information, and thus they have lower overhead and better robustness. Moreover, they may include the ones over spatially independent channel as special cases. The theoretical EE is further derived for performance evaluation, and the resultant closed-form expression is obtained. Computer simulation indicates that the theoretical EE agrees well the simulation result, and the suboptimal PA scheme can achieve the EE value near to the optimal one with lower complexity.

Recently, a considerable research interest has grown up in the millimetre wave wireless system as the most promising technologies in the next generation communication. Since high-frequency channels of the millimetre wave are easily attenuated in space, beamforming technology relying on the massive multi-input-multi-output system is introduced to transmit the millimetre wave in a very narrow directional beam, so as to greatly improve the transmit efficiency. Then a challenging problem lies in that how to optimise the overall throughput by allocating the antenna resources to different mobile users in the massive MIMO antenna system. In this study, the authors handle such a difficult problem in two different cases. They first begin with the one-direction case, i.e. all sub-arrays are deployed in several parallel rows along the edge of a rectangle antenna array. They decompose the problem and solve it gradually. Then they generalise the authors' result to the two-dimensional case, where the sub-arrays can be deployed in orthogonal directions. They apply the similar scheme, decompose the problem and solve each sub-problem progressively. Both NP-hard problems are solved with time efficient approximation algorithms. Simulation results demonstrate the efficiency of the proposed algorithms in different cases.

In this study, an energy-efficient optimisation scheme for a large-scale multiple-antenna system with wireless power transfer (WPT) is presented. In the considered system, the user is charged by a base station with a large number of antennas via downlink WPT and then utilises the received power to carry out uplink data transmission. Novel antenna selection, time allocation and power allocation schemes are presented to optimise the energy efficiency of the overall system. In addition, the authors also consider channel state information cannot be perfectly obtained when designing the resource allocation schemes. The non-linear fractional programming-based algorithm is utilised to address the formulated problem. Their proposed schemes are validated by extensive simulations and it shows superior performance over the existing schemes.

This paper considers the queue-aware optimal energy minimisation sparse beamforming design (QESB) in a downlink cloud radio access network (C-RAN) system where multi-RRH communicates with multi-user through a central computing cloud via digital front-haul links. The problem is formulated as the joint optimisation problem of the transmission energy consumption, system queue length and front-haul cost with sparse beamforming design. As we know, the beamforming design adaptive to both QSI and CSI is challenging because of the high complexity. Apart from previous works that take queue length as constraints, in this paper we directly minimise the queue length state involved joint optimisation problem with SINR constraints. A smooth function is proposed to approximate the -norm function which is discrete and non-convex. To overcome the challenge due to the non-convexity of the optimisation problem, the semidefinite relaxation (SDR) technology is utilised to convert the primitive problem into the difference of convex (DC) programming problem, and convex and concave procedure (CCP) algorithm is used to induce the sparsity of the beamforming control. The simulation results show that the scheme proposed by this paper can obtain a good tradeoff between system energy consumption, queue length and front-haul cost with SINR constraints in C-RAN system.

The radio resource management for relay-assisted access where every terminal user communicates with the base station through relay users is studied. In particular, the problem formulation is to maximise the total utility across relay users and terminal users under the bandwidth constraint of device-to-device (D2D) links. To solve such an optimisation problem, the authors first explore the diversity of channels between the relay users and the terminal users based on the maximum weighted bipartite matching theory, and adopt Hungarian algorithm to select the best relay user for each terminal user. Then, to stimulate relay users to participate in the cooperation, they design a two-stage Stackelberg game to jointly maximise the utilities of the selected relay user and the terminal user. In this doing, every terminal user can obtain the optimal data rate with the aid of relay. Finally, the authors' simulations show that the proposed relay user selection and game-theoretic resource allocation scheme can effectively improve the downloading rates of terminal users and achieve a ‘win-win’ strategy between the terminal users and relay users for relay-assisted access using D2D communications.

Energy efficiency (EE) is one of the main requirements for future fifth generation wireless networks to allow a sustainable network development. Toward this goal, this study proposes a novel iterative algorithm to maximise the EE of multicast services in ultra dense networks. Macrocells and small cells cooperate using a multicast beamforming strategy to efficiently radiate the power in the considered area. Moreover, small cells are activated opportunistically, and their power levels are adjusted suitably. Due to the high complexity of the optimisation problem, the proposed algorithm works calculating iteratively beamforming weights and power adjustments, thus reducing the set of possible solutions. Then, an exhaustive search is performed among the elements of this restricted set. This solution has reduced computational complexity, and the achieved EE is higher than benchmark alternatives. Performance in terms of EE and complexity is provided together with a solution feasibility evaluation.

Historically, transportation electrification has been largely hindered by the limited battery capacity and the long charging time. Battery swapping has emerged as one promising technology to mitigate these problems. A centralised battery charging station (BCS) is responsible for charging depleted batteries (DBs) and providing fully-charged batteries (FBs) for multiple geographically-distributed battery swapping stations (BSSs) so that they can carry out battery swapping services. Facilitated by the recent advancement in sensor and communication technologies, one salient advantage of this centralised approach lies in its convenience to better utilise dual energy sources (i.e. the traditional power grid and local renewable energy generators). This is achieved via optimising the charging processes of a large number of DBs. In this study, the authors propose an optimisation framework for a centralised BCS to minimise the energy cost from the dual energy sources to satisfy the FB demands from multiple BSSs. Particularly, the power dispatch problem in the day-ahead and real-time electricity markets is formulated as a two-stage stochastic optimisation through consideration of the intermittent renewable energy. Numerical simulations show that the proposed optimised power dispatch is capable of achieving cost saving of 76% compared with the benchmark, subject to the limited information available in day-ahead.

A rate adaption scheme is given at the receiver using rateless codes and log-likelihood ratio (LLR) threshold-based adaptive demodulation (ADM). The received bits with LLR absolute values higher than the preset threshold are demodulated by the receiver, otherwise, deleted. Through the theoretical analysis of the average mutual information (MI) of the demodulated bits, the method is obtained to calculate the LLR demodulation threshold under the required error performance after decoding and the constraint of codeword length for decoding. Then, the rate adaption scheme is applied in a parallel multiple relay wireless communication system. The LLR threshold is set according to the instantaneous SNR of the received signals in order to keep the average MI per demodulated bit of each relay link the same. The demodulated bits coming from all links are combined for decoding. The 256-QAM constellation and Raptor code are then considered as a special case to design a sample scheme. Simulation results prove the correctness of the theoretical analysis and the feasibility of the proposed scheme, and when it is employed by a multi-relay transmission system, the diversity gain can be obtained, and the anti-fading and the anti-jamming abilities of the system are promoted.

In this article, intra- and inter-cell interference caused by the non-ideal backhaul in coordinated multipoint (CoMP) are studied. A recursive estimation-based zero-forcing beamforming (RE-ZFBF) scheme is proposed to mitigate the interference. Based on an initial value, the RE-ZFBF scheme recursively approximates the beamformer variation between two consecutive time points by exploiting the temporal channel correlation. In contrast to a previous work, the authors convert the original non-convex constraint quality-of-service problem to an unconstrained convex one, by optimising the estimation of the beamformer error, rather than the beamforming power. It is shown that the proposed scheme can mitigate at most half the intra- and inter-cell interference, enhance the ZFBF performance, and outperform the existing works for CoMP with a non-ideal backhaul in heterogeneous small-cell networks.

In this study, the authors study the power efficiency optimisation in wireless-powered full-duplex relay (WFR) systems, where the entire transmission process can be partitioned into wireless power transfer phase (WP) and full-duplex information transmission phase (FP). For WFR systems with same source transmit power, where the source transmit powers of WP and FP are same, they first prove that the power efficiency is a strictly concave function over the time-switching factor, and an optimal time allocation scheme is proposed to maximise the power efficiency. Then, for the given time-switching protocol, the optimal power allocation strategy is obtained by analysing the derivative of the power efficiency with respect to the transmit power. Finally, they propose the joint power and time allocation scheme. For WFR systems with different source transmit power, where the source transmit powers of WP and FP are different, the optimal time allocation scheme and optimal power allocation strategy are derived by studying the derivative of the power efficiency. Furthermore, the joint power and time allocation scheme is proposed to maximise the power efficiency. Simulation results are presented to validate the authors' proposed schemes for the WFR systems.

In this work, signal space diversity (SSD) is incorporated into a multiple-input multiple-output system with maximal ratio combining and transmit antenna selection. The performance of the proposed system with phase-shift keying (PSK) modulation is studied under a slow flat Rayleigh fading channel scenario with the correlated receive antennas. By adopting the realistic exponential correlation model, an exact closed-form expression is derived for pairwise error probability. The optimal rotation angles are obtained for binary and quadrature PSK signal constellations. The theoretical analysis is verified by the numerical simulations. It is shown that the error performance of the system can be improved with almost no extra complexity or cost. It is also demonstrated that the proposed scheme with SSD is more resistant against the studied correlation model as compared to the original scheme without SSD.

Heterogeneous cognitive radio networks (H-CRNs) operating in the same TV white space (TVWS) spectrum cause severe mutual interferences, which heavily degrades the network performance of coexisting H-CRNs. Inspired by the Lotka–Volterra competition model of different species in a biological ecosystem, this study formulates the coexistence of H-CRNs over TVWS as an equilibrium assignment problem of a discrete non-linear control system (DNCS). By using the local linearisation method, the authors can find an approximate linear control system (ALCS) model to the DNCS. Further, they obtain an effective feedback control to the equilibrium assignment of the ALCS via solving a sufficient condition in the form of linear matrix inequalities. Third, they propose a novel ecology-inspired heterogeneous coexistence algorithm (EHCA) based on the obtained feedback control. It is shown in simulations that the proposed EHCA could guarantee any desired but feasible spectrum share among H-CRNs.

The latency and reliability of single-relay and multi-relay systems are investigated in this study. In a single-relay system with the amplify-and-forward protocol, a new approximation analytical method is proposed for the outage probability, which can also be extended to be used in the multi-relay system. The latency-reliability trade-off degree (LRTD) of single- and multi-relay systems, i.e. the slope of the latency-outage probability curve with logarithmic scales, is analysed and proved to be the same as the number of relay nodes. In the multi-relay system, the relationship between the system LRTD and the channel state information overhead is investigated. The optimum number of relay nodes can be derived according to the approximate expression of the outage probability. A simple iterative method is proposed to obtain the optimum number of relay nodes. The convergence of the iterative method is also proved.

Despite extensive studies on optimal power allocation, how to design an efficient joint user scheduling and power allocation scheme for uplink multiuser networks remains largely unexplored. This study investigates joint opportunistic user scheduling and power allocation in uplink multiuser networks to maximise user throughput subject to the power and resource sharing constraints. By exploiting the cumulative distribution function-based scheduling method, the authors first characterise the optimal power allocation subject to both long-term and short-term power constraints. Instead of calculating the transmit power in an iterative and central manner, users can independently decide their instantaneous transmit power in the proposed scheme, which facilitates the algorithm implementation for each user in uplink networks. The closed-form throughput of the proposed scheme is also derived, which can provide an efficient way to estimate and evaluate user performance. Numerical results reveal that compared with several benchmark schemes, the proposed scheme improves throughput performance significantly.