Given the rising concerns on carbon emission and increasing operating expense pressure, mobile network operators and device vendors are actively driving the energy-efficient network evolution. Energy efficiency (EE) has been determined as one of the key objectives of the 5G system. To realise sustainable 5G, various new technologies have been proposed to reduce conventional energy consumption. Meanwhile, green energy sources are explored to reduce the dependence on conventional energy. This study makes a survey on recent academia and industry research on the EE of the 5G system from perspectives of radio resource management, architecture and deployment paradigm, green energy harvesting and smart grid integration. Typical green 5G enabling technologies are presented and discussed comprehensively. Moreover, the latest progress on EE in 3GPP is also investigated. Given the broad research areas, only those critical open issues and challenges are presented to inspire further investigations. Finally, the authors identify several research directions as the way forward to realise the green 5G system.

Existing handover authentication schemes are implemented in the upper layer through cryptographic techniques with different protocols and parameters involved under different handover scenarios, introducing high latency and complexity especially in the next generation (5G) highly heterogeneous network (HetNet). The authors propose to introduce wireless link signatures decided by users' locations as handover authentication data to achieve unified and fast handover authentication at the physical layer in 5G software defined networking-based HetNet. Specifically, the unique wireless channel characteristics between a user and the serving access point (AP) are extracted as the secure context information (SCI) and transferred to the target AP. The latter determines whether the user is the legitimate one who has already been authenticated according to the received SCI. They then analyse the authentication performance relating to multiple attributes and results demonstrate that the authentication strength can be adaptively adjusted. Furthermore, they find that optimum performance can be achieved by setting a proper decision threshold and derive the sub-optimal performance by iterative search. Lastly, analysis and simulations on latency and overhead compared with existing ones are conducted and results prove the effectiveness of the proposed scheme.

This study investigates the joint power allocation and energy cooperation problem in a multiuser downlink distributed antenna system with hybrid energy supply. The authors focus on the energy efficiency (EE) maximization problem for three different types of precoding, zero-forcing (ZF), general beamforming method and conjugate-beamforming. For ZF precoding, they apply fractional programming and reform the optimization problem to a convex one. An iterative algorithm to deal with the fractional objective function is presented. Whereas the problem is non-convex for general beamforming with user interference, they take maximum ratio transmission as an example and adopt a set of transformation and approximation based on the difference of convex (DC) programming. Furthermore, for conjugate-beamforming, they first transform the quadratic signal to interference plus noise power ratio into a trackable form and then DC programming is applied. A two-loop algorithm for the general beamforming and conjugate-beamforming is presented with fractional programming in the inner loop and DC programming in the outer loop. Simulations show that the proposed algorithm improved EE significantly and indicate that energy cooperation can contribute to a higher EE. It also reveals that ZF achieves better EE with small noise variance while conjugate beamforming in high noise circumstance.

Device-to-device (D2D) communication can effectively use cognitive radio network approach to coexist with cellular users. For such a cognitive D2D system, two approaches (underlay and overlay) are considered to manage the spectrum sharing among the cellular (primary) users and the D2D (secondary) users. Energy efficiency (EE) is crucial in both these cases due to limited battery capacity and quality of service requirements of the D2D users. This study effectively models the power allocation problem of such a cognitive D2D system by maximising the EE of the D2D users subject to a minimum rate requirement for both the D2D users and the cellular users. This leads to a non-linear fractional optimisation problem which is more complicated and computationally intractable. Alternatively, geometric water-filling approach have been utilised for power allocation to solve this optimisation problem which results in an ‘exact’ and ‘low complexity’ solution. Simulation results reveal the benefits of the proposed algorithm.

This study is to construct the autoregressive models for the low-voltage broadband power line communication (PLC) channel noise by two machine learning algorithms, namely the least square support vector machine (LS-SVM) and wavelet neural networks. The main work is to compare the two classical machine learning algorithms and also compare them with the traditional Markovian–Gaussian method. To verify their availability and ability to adapt to the time-variant PLC channels, noise measurements for low-voltage PLC channels in indoor and outdoor scenarios are carried out. The accuracy and efficiency of the two models are studied and compared based on a large amount of measurement data. The results show that both of the noise models can simulate and adapt to the time-variant low-voltage broadband PLC channels very well. The LS-SVM model is found to have shorter simulation time and higher accuracy. Moreover, the proposed noise models are also compared with the traditional Markovian–Gaussian model. The results show that both the proposed noise models exhibit higher accuracy and lower complexity, especially that the LS-SVM is more appropriate to be applied as a noise generator in PLC link and network level simulations instead of the current Markovian–Gaussian model.

The ever changing traffic and Quality-of-Service (QoS) requirements of different traffic classes in multimedia applications impose tremendous challenges to the routing algorithm design. To address these challenges, a novel priority-based dynamic multi-path routing algorithm (PDMR) over Software Defined Network (SDN) is proposed in this paper. PDMR comprehensively considers the priorities of multimedia streams and the real-time status of the link. The goal of PDMR is to determine what resources to be allocated to a set of flows keeping their priority, improving the utilization of network resources for satisfying stringent QoS requirements of the traffic flow. According to different QoS requirements in multimedia applications, traffic is classified into two classes and allocated their respective priorities. In addition, we derive a classification of the link cost function by considering the real-time parameters such as link bandwidth, link delay, and link load to allocate the resources flexibly for transmission and to reduce the influence of between traffic classes. Furthermore, our proposed communication model between application services and the controller, which can guarantee the reliable transmission of the designated traffic. By conducting extensive simulations, we demonstrate that our proposed PDMR algorithm significantly outperforms other existing non-priority-based schemes in improving network performance.

In this study, the authors propose a simple and robust near-optimal single differential coherent detection scheme for IEEE 802.15.4 binary phase shift keying (BPSK) receivers. The detection process is initiated by a bootstrap processor, which is responsible for estimating and compensating the residual carrier frequency offset effect in the sample from the autocorrelator output. In particular, for this bootstrap processor, a simple estimator with only one addition operation is provided. This low complexity benefits from that the high signal-to-noise ratio and a trigonometric approximation are combined, i.e. , for simplification of the full estimation scheme. Further, to achieve near optimal performance as well as robustness to carrier frequency offset, the observation space is subdivided into four equi-angular regions to decrease the estimation error introduced by the involved approximation. The proposed method is validated through detailed physical layer (PHY) simulations according to the IEEE 802.15.4 standard. The simulation results demonstrate that, compared with the full estimator, the proposed algorithm can acquire a fairly accurate estimation, with almost no loss of reliability and robustness, whereas complexity reduction is also achieved.

This study investigates the performance of a bidirectional/two-way relaying scheme with an energy-harvesting relay while amplify-and-forward relaying is performed. With multiple antennas at the relay, the authors propose the use of the max–min antenna selection scheme in the context of an energy harvesting scenario. They show that the proposed scheme attains diversity gain, whereby its end-to-end symbol error probability performance improves with increments in the number of energy harvesting relay antennas. For limited battery capacity at the energy harvesting node, they derive the lower bound of the outage probabilities and observe a good match between the analytical and simulated results. For this scenario, a simple power provisioning technique is proposed to optimise the end nodes' transmission powers. It is observed that the proposed technique saves significantly more transmission energy than the conventional equal power provisioning technique.

In this study, four channel-estimation (CE) methods are proposed for sparse high mobility doubly selective channels. These methods are designed to take advantage of the sparsity of the channel to decrease the training sequence size and the computational complexity of the CE. Two of the new methods use time domain training sequences. In the first method, the pilot is designed such that the time domain channel can be estimated tap-by-tap using an autoregressive procedure. In the second method, a truncated Taylor expansion of the channel phase is applied to linearise the equations for CE and a pseudorandom training sequence is utilised to solve those equations. The last two proposed channel estimators employ frequency domain pilots and are built upon a previously proposed estimator that exploits both the delay and Doppler shift sparsity of the channel. The computational complexity and the spectral efficiency of the methods are compared. In addition, simulations are performed to compare the performance of these estimators in a sparse channel. Simulation results indicate up to 30 dB improvement in the bit error rate calculation for our proposed CE methods compared to the conventional CE methods.

Different from the conventional receive scheme for millimetre wave (mmWave) communication, this study proposes a multi-beam receive scheme to improve the quality of the received signal and enhance the robustness of the system. The authors proposal is firstly formulated as an optimisation problem, where each signal received by different beams is combined through phase compensation to harvest more transmission energy. Then the original problem is divided into a series of sub-problems and an analytical solution is further obtained for each sub-problem. Furthermore, considering the spatial sparsity of the mmWave channel, they propose further a low-computational complexity algorithm by choosing a few candidate codewords with non-negligible receive signal power. Numerical results show that their proposal achieves remarkable performance improvements even with a small size codebook and is more robust for different scenarios, especially for a non-line of sight scenario. Compared with doubling receive antennas to obtain diversity gain, their proposal obtains larger signal-to-noise ratio gain while using fewer hardware resources.

Current approaches to information-centric network (ICN) implementation employ the edge storage of network infrastructures to minimise the latency of information retrieval. However, the edge storage of infrastructures is finite. Distributed content caching assisted by mobile devices becomes a potential solution to content publishing services. Nevertheless, under the conventional half-duplex-based ICN, extra memory is occupied and the delay is increased. Fortunately, full duplex (FD) communications can improve the spectrum efficiency of wireless networks, and reduce the access delay by more flexible content caching. In this study, the authors propose a novel FD-based ICN (FD-ICN) framework, where content caching is not only implemented in network infrastructures but also in mobile devices. Content cached by mobile devices can be delivered in a FD amplify and forward way without extra BS memory occupation and delay. To maximise the network utility of the FD-ICN, they formulate the caching strategy and FD radio resource allocation as a joint optimisation problem. A joint caching strategy and FD radio resource allocation algorithm are proposed. Simulation results show their FD-ICN framework can achieve superior system utility compared to the conventional ICN. Moreover, the proposed algorithm exhibits higher utility with similar converge rate compared to the heuristic algorithm.

In this study, a new chaos modulation scheme which combines M-ary differential chaos shift keying (DCSK) with code-index modulation (CIM-MDCSK) is proposed. In the CIM-MDCSK scheme, the two Walsh codes that are used to generate two orthogonal chaos components are selected from the candidate codes, whose code indices are determined by information symbols. Thus, the information bits are conveyed not only by M-ary DCSK signal but also by the indices of the Walsh codes. Theoretical symbol error rate (SER) and bit error rate (BER) of the proposed scheme are derived and confirmed by simulations. Furthermore, by applying the noise-reduction to reference signals of CIM-MDCSK, the SER/BER expressions are also derived. Simulation results show that the proposed CIM-MDCSK outperforms DCSK and M-ary DCSK based on Hilbert transform. Especially, the CIM-MDCSK with noise-reduction shows significant advantages. Moreover, the performance of CIM-MDCSK scheme is compared with direct sequences spread-spectrum system with code-index modulation over flat and frequency selective fading channel. The proposed CIM-MDCSK can offer good performance over frequency selective fading channel with a low complexity non-coherent receiver which does not require any channel state information and channel equalisation.

Orthogonal frequency division multiplexing-based pattern division multiple access (PDMA) is considered as a promising multiple access scheme for future wireless communication systems due to its high spectral efficiency and powerful ability to support massive users. In this study, it is shown that two pattern matrices with unequal diversity gain in the PDMA system have better convergence performance compared with the signature matrices in a traditional low-density signature multiple access system by simulations and extrinsic information transfer (EXIT) chart analysis. For a low-density parity check (LDPC)-coded PDMA system, the EXIT characteristics between the front-end multiple-user detector (MUD) and the LDPC decoder may be mismatch, which usually leads to degraded performance when an iterative detection and decoding algorithm is used. To overcome this problem, a two-stage iterative optimisation algorithm, which is easy to implement is proposed to find an optimal (near optimal) degree distribution pair for the LDPC code. Both EXIT chart analysis and simulation results demonstrate that the proposed algorithm exhibits further performance gain compared with regular (3,6) LDPC-coded systems under both an additive white Gaussian noise channel and a Rayleigh fading channel.

This study addresses the issue of block-sparse recovery in compressive sensing in the presence of non-Gaussian measurement noise. By using the generalised -norm noise constraint for to replace the popular -norm, in this study, the authors put forward a truncated model for recovering block-sparse signal. A theoretical analysis is first presented to guarantee the validity of proposed method. If the measurement matrix satisfies an extended block restricted isometry property, the reconstruction error is bounded in the optimisation. Moreover, in order to solve the induced optimisation problem effectively, they present an alternating direction method of multipliers via embedding Karush–Kuhn–Tucker system of -norm functions into the frame structure of augmented Lagrangian methods. When compared with some of the state-of-the-art methods, the proposed method becomes more competitive.

In this study, the authors investigate the secrecy performance at the physical layer of wireless communication systems where the channels are modelled as cascaded fading channels, in which the fading effects are worse than those in the cellular communication channels like Rayleigh and Nakagami-m. Analytic results are derived for the cascaded Nakagami-m fading channel model comprising the cascaded Rayleigh, 2*Nakagami-m, the generalised-K, and the conventional cellular channel models as well. By evaluating the information-theoretic physical layer security performance, they obtain the closed-form expressions of the average secrecy capacity and probability of the positive secrecy capacity in case of that channel-state-information of the eavesdropper is known by the source. Then they obtain the exact closed-form secrecy outage probability (SOP) when the eavesdropper is passive. Analytic results are computed in terms of the bivariate and univariate Meijer's G functions and later on are successfully validated through Monte Carlo simulations. The simulation results show that the secrecy performance worsens with the increasing cascading degree of the fading channels. For example, in 2*Nakagami-m fading channels where the cascading degree is 2, extra 4 dB signal-to-noise ratio is required to achieve the same SOP value in comparison with the classical Nakagami-m fading channels.