This study proposes some multivariable approaches for power allocation in orthogonal frequency multiple access-based differential chaos shift keying (OFDM-DCSK) system. The objective is to minimise the overall bit error rate (BER) under the total transmission power limit. There is some literature focusing on the power allocation for OFDM-DCSK systems, but all of them have only addressed the case where the power allocated to the reference subcarrier is assumed to be equal to one to simplify the problem to a single-variable optimisation problem. In this study, the authors simultaneously take the reference and data-bearing subcarriers power into consideration. They formulate a multivariable optimisation problem and solve it using Lagrange relaxation to derive a closed form solution. As the main contribution, the problem is converted to a cubic equation which is solved theoretically. Since the equation is non-convex, they solve it again using a genetic algorithm (GA)-based method for additive white Gaussian noise channel as a case study. The heuristic algorithm validates the theoretical approach. As another conclusion, the simulation results indicate that both of the proposed approaches outperform algorithms relaxing the reference power in terms of the BER performance, but the analytical solution leads to less time complexity in comparison with the GA-based method.

This study investigates two-way relaying where an energy harvesting capable relay exchanges information between two sources. Legitimate information is wire-tapped by an eavesdropper. To intercept wire-tapping, this study exploits a friendly jammer. Secrecy outage analysis of the energy harvesting two-way relaying network with the friendly jammer over Rayleigh fading channels is first proposed in terms of individual secrecy outage probabilities and then validated by computer simulations. Various results demonstrate the efficacy of the jammer in preventing the eavesdropper from stealing the source information and significant impacts of relay location, jammer location, jammer's transmit power, energy conversion efficiency, time switching ratio on the security performance.

Aiming at the shortcomings of the existing frequency hopping signal parameter estimation algorithms based on compressed sensing theory, such as weak anti-noise performance, high data transmission and processing, and high hardware implementation cost, this study proposes an improved frequency hopping signal parameter estimation algorithm based on analogue information converter called Baseband Parameter Estimation (BPE) method. BPE does not reconstruct the frequency hopping signal into the Nyquist spectrum, and after obtaining the support set of the signal, the parameter estimation of the frequency hopping signal is performed directly at the baseband. The processing of baseband spectral slices can convert unreconstructed signal parameter estimates into parameter estimates for certain support sets, which makes BPE possible. Simulation experiments show that compared with the existing parameter estimation algorithm, BPE can not only greatly reduce the bandwidth and storage pressure required for subsequent transmission, but also has good anti-noise performance.

In wireless ad hoc networks, the channel access scheme allows different nodes to communicate simultaneously without creating outages at nearby nodes. Therefore, the scheme should be easy to implement, i.e. with as little coordination between the nodes as practically possible and it should be able to schedule the maximum number of concurrent transmissions. The proposed scheduling scheme ensures the spatial separation among packed nodes by suppressing the active interferers around an active receiver. Moreover, the scheme utilises each interferer's transmitter–receiver (Tx-Rx) separation to make a decision regarding its inclusion in the scheduled transmissions. The proposed scheme not only gives significant () increase in the transmission capacity as compared with the random ALOHA but also outperforms the latest guard zone-based scheduling scheme for the distributed ad hoc networks. Additionally, it performs nearly as good as the near-optimal centralised scheduling scheme. While the attainable transmission capacity is comparable but still inferior to the centralised scheme, it can be implemented easily in a distributed manner, unlike the centralised scheme. The derived results provide the optimal guard zone size and corresponding transmission capacity under varying network parameters – outage probability, path-loss exponent, maximum Tx-Rx separation, and spread spectrum's spreading gain.

This study investigates the effects of the imperfect channel state information on the leakage rate-based untrustworthy relay selection strategies. The investigation considers that the channel state information is imperfect because of the channel estimation errors and also the feedback delay with time-variant channels. The investigation also considers three different types of leakage rate-based selection strategies, which are half-duplex, full-duplex, and hybrid. The investigation also considers a dual-hop one/two-way amplify-and-forward-based half-/full-duplex wireless relaying network in the system model. In addition, in order to mitigate the information leakage, a finite number of friendly jammers are affecting the untrustworthy relay terminals. According to analytical, asymptotic, and Monte–Carlo simulation results, the leakage rate-based selection strategies achieve cooperative diversity order in high signal-to-noise ratio regimes. The channel estimation error causes system coding gain losses in low signal-to-noise ratio regimes. The feedback delay degrades the achievable diversity order from M to 0 and also causes system coding gain losses in high signal-to-noise ratio regimes. In addition, the friendly jammers and loop-interference also degrade the achievable diversity order and also cause system coding gain losses in high signal-to-noise ratio regimes.

Filter bank multicarrier with offset quadrature amplitude modulation (FBMC-OQAM) has gained significant importance as a contender for the fifth generation mobile communication system and also meets the application requirements of the Internet of things. The peak-to-average power ratio (PAPR) of the FBMC-OQAM is very high due to using a same prototype filter for each subcarrier and the addition of different subcarriers at the transmitter. Therefore, a novel randomly assigning prototype filter (RAPF) method is proposed to reduce PAPR in FBMC-OQAM system. Based on the proposed RAPF method, the authors analyse the performances of both PAPR and bit error rate (BER) in the FBMC-OQAM system. Simulation results show that the proposed RAPF method helps to significantly reduce PAPR of FBMC-OQAM system. Meanwhile, compared with conventional FBMC-OQAM system, the proposed RAPF-FBMC-OQAM scheme has almost the same BER performance in the additive white Gaussian noise channel but is descended slightly only in the high signal-to-noise ratio region of the frequency selective fading channel.

In future small cell networks, tracking areas (TAs) that are defined for location management will be updated frequently to cope with the massive signalling overhead. In this study, a TA planning method based on spectral clustering is proposed to minimise the network signalling overhead. Firstly, handover and paging statistics are simulated to construct a series of graphs showing user mobility and traffic. Then, the TA planning problem is formulated as a classical graph partitioning problem. Finally, a new TA planning method based on spectral clustering is used to build the new TA plan. Simulation results show that the proposed method can effectively reduce the system location update rate and signalling overhead, and improve the system performance.

Ultra-dense small cell (SC) deployment in the future 5G network makes the architecture of the network as heterogeneous networks (HetNets). This is a good solution to boost the capacity of the network and extend its coverage. However, the dense SCs deployment has brought new challenges to the network including interference, frequent unnecessary handovers, and handover failures. Therefore, user equipment will suffer from a degraded quality of service. In this paper, the authors propose a grey rational analysis-based handover (GRA-HO) method in dense SCs HetNet. The proposed method combines the analytical hierarchy process technique to obtain the weight of the handover metrics and the GRA method to rank the available cells for the best handover target. The performance of the proposed method is evaluated and compared with the traditional multiple attribute decision-making methods including simple additive weighting and VIKOR methods. Results show that the GRA-HO method has outperformed the existing methods in terms of reducing the number of frequent handovers and link failures, in addition to enhancing energy efficiency.

Generalised frequency division multiplexing (GFDM) utilises a circular pulse shaping mechanism to hinder out-of-band emissions and for achieving low latency. However, fallacious synchronisation of this multicarrier technique would lead to severe inter carrier interference and inter symbol interference. Conventional training sequence-based methods alleviate the effect of time and frequency misalignments by using the concept of data repetition in the pilot preamble, which recedes data efficacy. This study enlightens various aspects in real-time implementation of blind GFDM signal transceiver using oversampling for carrier frequency offset (CFO) correction in indoor environments. It is observed that the phase shift between neighbouring sample points in an oversampled GFDM symbol is constant throughout the symbol duration. This phase shift is found to be unassociated with either subcarrier or subsymbol indices. Using this property, the maximum likelihood estimate of the CFO is deduced and is analysed in various channel environments. The Cramer–Rao lower bound for the oversampling-based GFDM signal model is derived and the authors prove through simulation that the proposed algorithm results in a little error floor. The results obtained in simulations have been validated with real-time test bed built with universal software radio peripheral 2953R as hardware and LabVIEW as software.

In this study, the authors analyse the coverage probability of downlink Poisson networks under a double shadowed (DS) fading channel, where the DS fading composes of lognormal shadowing and – shadowed fading with integer parameters. Firstly, they provide a probability density function of DS fading and approximate it as a weighted sum of – shadowed distributions according to the Gaussian–Hermit quadrature rule. The comprehensive nature and heavy-tailed feature of the DS fading model are presented. Secondly, under the closest cell-association rule and the general cell-association rule, they, respectively, derive closed-form expressions for the coverage probability of downlink Poisson networks with DS fading. Numerical results show that the DS fading environment with rich clusters and mild fluctuations enlarges the coverage probability of Poisson network under the two types of cell-association policies. Moreover, the coverage probability decreases as the large-scale shadowed parameter increases when a severing base station (BS) is selected by the closest cell-association rule to avoid the ping-pong effect compared to the general cell-association rule. The convergence of coverage probability is also validated in the numerical section when the locations of users or BSs are, respectively, modelled by modified Thomas cluster processes.

The max–min fairness (MMF) strategy has been widely employed to manage wireless networks since it guarantees fairness among users. However, with a large number of users awaiting service, the network tends to be congested and the quality-of-service (QoS) will degrade substantially. This motivates us to study the MMF problem jointly with the consideration of admission control. Specifically, the authors consider a downlink network consisting of a multi-antenna base station (BS) and multiple single-antenna users. By jointly optimising the admissible users and the BS transmit beamformers, they aim to maximise the minimum signal-to-interference-plus-noise-ratio of the admissible users, such that high QoS and fairness can be guaranteed simultaneously for them. This problem is essentially NP-hard, and hence they pursue an efficient approximate solution to it. To this end, they first reformulate this problem from the perspective of sparse optimisation, and then develop a low-complexity algorithm to iteratively solve the approximate problem. Moreover, to facilitate the algorithm's implementation, they further recast the subproblem in each iteration, such that it fits into the framework of the alternating direction methods of multipliers. Finally, an efficient distributed algorithm is designed, with each step being simply computed in a closed form.

Although the Cognitive Radio Ad-Hoc Network (CRAHN) is an effective technology to fully utilize the spectrum resource, the appearance of selfish nodes seriously reduces the communication efficiency of CRAHN and generates unfair resource competition. In this paper, a new incentive strategy is proposed to tackle selfish nodes in CRAHN. In our CRAHN model, the Secondary-User (SU) cooperates with the Primary-User (PU) in a spectrum leasing mode. Since PU can select multiple SUs as relays but only leases a common authorized spectrum usage time to SUs, the SU has the selfish tendency to reduce its power in relay task, which seriously damage the partnership between PU and SUs. We propose an evaluation coefficient to evaluate the behavior of each SU, where the evaluation coefficient establishes the reward and punishment mechanism to suppress the selfish behavior of SU in relay task. Meanwhile, in order to solve resource allocation problem, a Stackelberg game between PU and SUs is formulated and the optimal solutions are determined in a distributed manner. Simulation results validate that the incentive strategy can effectively suppress the selfish behavior of SUs, in the meantime, the total communication throughput is increased.

In this study, the authors study the collaborative data aggregation using multiple antennas sensors and fusion centre (FC) with energy harvesting capability in the wireless sensor network (WSN). The optimisation problem is formulated to improve the data transfer rate, based on the parameters of collaboration among sensors, the energy harvesting, and storage of each sensor. In particular, they observe several practical constraints for energy harvesting and capability battery energy storage to maintain network connectivity. They propose three scenarios based on the number of antennas for transferring, collecting, and sharing the data on sensor and FC. It is shown these optimisation problems are a non-convex and to resolve this issue, the objective function is converted to a convex function using a relaxation method. The numerical results show the impact of different parameters on the data rate at FC and improvement in network connection and throughput by using proposed collaborative data aggregation techniques compared to their counterparts.

Mobile devices are increasingly developing, and more sophisticated wireless networks are available as well. Users nowadays want to access the best available technology anytime, following the always best-connected concept, which leads often to vertical handovers. It means changing the wireless access type and is an important research area in the next generation of networking. In contrast, when changing the point of attachment while using the same wireless technology, it is a ‘horizontal handover’. When handing over the communications, the transfer should be ‘seamless’, i.e. it should not cause delays or break the session and disconnect the user. Indeed, the vertical handover process is continuously improving, especially the network selection step, which is the most crucial one. Naturally, multi-attribute decision-making (MADM) methods fit this kind of issues, but they still produce some undesirable results sometimes, due to metrics imprecision and vagueness. The authors propose in this study a new network selection scheme, combining the fuzzy logic and a new MADM method, named fuzzy Manhattan distance to the ideal alternative. They compare through simulations this new technique, with the best known MADM methods, as well as with fuzzy grey relational analysis, to evaluate its performance in the same context.

A well-known harmful attack against wireless sensor networks (WSNs) is the Sybil attack. In a Sybil attack, WSN is destabilised by a malicious node which forges a large number of fake identities to disrupt network protocols such as routing, data aggregation, and fair resource allocation. In this study, the authors suggest a new algorithm based on a composition of learning automaton (LA) model and client puzzles theory to identify Sybil nodes in stationary WSNs. In the proposed algorithm, each node sends puzzles to its neighbours periodically during the network lifetime and tries to identify Sybil nodes among them, considering their response time (puzzle solving time). In this algorithm, each node equipped with a LA to reduce the communication and computation overhead of sending and solving puzzles. The proposed algorithm has been simulated using J-SIM simulator and simulation results have shown that the proposed algorithm can detect 100% of Sybil nodes and the false detection rate is about 5% on average. Also, the performance of the proposed algorithm has been compared to a wellknown neighbour-based algorithm through experiments and the results have shown that the proposed algorithm is significantly better than this algorithm in terms of detection and false detection rates.

Due to the characteristics of the underwater acoustic (UWA) channel, the process at the receiver is complicated to match the channel. To simplify receiver design and match UWA channel better, this study proposes a deep neural network-based orthogonal frequency division multiplexing receiver for UWA communication. Different from existing receivers needing a neural network and several other processing parts, the proposed receiver only uses a single neural network to implement the whole signal processing. Moreover, it is a general receiver which is suitable for other modulation schemes. Simulation results show that the proposed receiver offers better bit error rate performance over traditional ones.

Cyber physical internet of things systems (CPIoTs), taking advantages of cyber physical systems, have been considered as a promising technology to provide better interaction and interoperability among various machines. However, the development of CPIoTs suffers severely from big data. In this context, fog computing is proposed to handle the big data bottleneck of CPIoTs. In this study, the authors focus on the joint optimisation of the communication resources and computation resources in fog computing-based CPIoTs to maximise the overall system energy efficiency, in which multiple fog nodes and end users are taken into consideration. Moreover, since the channel estimation error will become serious with the expanding scale, the imperfect channel state information is considered in this study. The formulated optimisation problem is a mixed integer non-linear problem which is indeed non-deterministic polynomial hard, hence a probability distribution method is proposed to reformulate the problem into a non-probability form, and the resource allocation algorithm based on Dinkelbach algorithm and Lagrange duality approach is adopted to tackle the problem efficiently. The simulation results confirm the effectiveness of the proposed scheme, especially when the scales are enormous.

Non-orthogonal multiple access (NOMA) has been widely recognised as a promising technology due to its potential to achieve high spectral efficiency and massive connectivity. The authors study a multiple-relay multiple-input and multiple-output cooperative NOMA system. In particular, a joint relay-and-antenna selection (JRAS) scheme with coordinated direct and relay transmission is proposed, which makes it possible to maximise the instantaneous rate of far user with high quality ofservice (QoS) priority while guaranteeing the requirement of near user with low QoS priority. Then, closed-form expressions for outage probability are derived and asymptotic expressions for outage probability in the high signal-to-noise ratio regime are also obtained in order to provide further insights. Analysis results demonstrate that the proposed JRAS scheme significantly enhances the outage performance for cooperative NOMA, and simulation results are provided to verify the accuracy of theoretical analysis.

In order to enhance simultaneously the association robustness of mobile users and spectrum efficiency (SE) of systems, by integrating the decoupled uplink (UL)/downlink (DL) association (DUDA) and cross-tier dual connectivity (DC), the orthogonal multiple access (OMA)-mode and non-OMA (NOMA)-mode design schemes are investigated over a three-tier heterogeneous network (HetNet) accompanying with the proposition of a conditional association analysis method. The scheme exploits effectively the DC requirement of NOMA. Additionally, in the proposed conditional association design and analysis method, the decoupling UL association designs are conducted only under a given DL association condition. Owing to low complexity, this method shows that it is very easy to achieve the possible decoupling UL DC designs and the corresponding condition association probabilities. Then, the conditional coverage probabilities and SEs of the OMA-mode and NOMA-mode HetNets are derived by specially considering DUDA and coupled UL/DL association strategies. The proposed conditional design framework can be easily extended to multi-tier HetNets and is helpful to select feasible DL candidate from all possible DL associations so that the resulting UL associations are optimal. Besides this, the cross-tier DC design ensures the effective exploitation of the whole network resources because different tiers have different serving levels.

This research article proposes a multiple relay-based Reed–Muller network-coded cooperative (MR-RMNCC) scheme for wireless communication. In the MR-RMNCC scheme, Hadamard transform construction is adopted to build Reed–Muller (RM) codes that effectively achieve network coded-cooperation among multiple sources and multiple relays over slow and fast Rayleigh fading channels. In any network coded-cooperative system, a proper encoding strategy at the relay nodes is vital for achieving an optimum code construction at the destination node. Therefore, the authors have proposed an efficient message bit selection algorithm at relay-2 that optimally selects the message bits. The supremacy of the message bit selection algorithm is demonstrated by Monte–Carlo simulation. Furthermore, the performance bound for average error-probability is also derived for the MR-RMNCC scheme that validates its simulated bit-error-rate performance over a fast Rayleigh fading channel. At the destination node, the MR-RMNCC scheme is jointly decoded by two different decoding strategies, i.e. joint soft maximum likelihood decoding and joint majority logic decoding. Monte–Carlo simulations suggest that the MR-RMNCC scheme not only provides a significant bit-error-rate performance gain over its corresponding coded non-cooperative scheme but also to the existing state-of-the-art RM network-coded cooperative scheme under identical conditions.