The authors take the quality of sensing data into consideration and design a reputation-aware incentive mechanism (RAIM) with the properties of truthfulness and individual rationality while maximising the weighted social welfare of the whole system. In addition, in order to reduce the computational complexity of RAIM and improve the system feasibility, the authors propose a heuristic algorithm RAIM-H, with the computational complexity of . Simulation results show the nice performance of the proposed mechanisms RAIM and RAIM-H in terms of the weighted social welfare and the average reputation. Specifically, RAIM can improve the weighted social welfare by 8.65 and 48.16% compared with trustworthy sensing for crowd management (TSCM) and random selection, respectively, with the number of smartphone users . Meanwhile, RAIM-H approaches to the maximum very well and can improve the weighted social welfare by 6.15% and 75% compared with TSCM and random selection, respectively, with the number of smartphone users .

In this study, a novel model for the joint compensation of dual-band power amplifier (PA) distortion and in-phase/quadrature (I/Q) imbalance, which are the dominant impairments of wireless signal transmitters, in a complexity reduced structure is proposed. This model is mainly based on the augmented Hammerstein approach in a Cartesian form so that a static block is intended to model the PA non-linearity and the modulator I/Q imbalance while a finite impulse response filter based block is used to model the PA memory effects. The proposed approach reduces significantly the complexity of the proposed model compared with the recently published memory polynomial models. Experiments with and without I/Q modulator impairments have been carried out on a dual-band PA to verify the accuracy and the performance of the linearisation technique based on the proposed model. The experimental results have revealed a good impairments reduction with much less model coefficients compared with the recently published ones.

In this study, the authors investigate the employment of transmit antenna selection (TAS) against eavesdropping in cognitive radio systems, where a cognitive source (CS) node transmits to a cognitive destination (CD) node in the face of an eavesdropper, each equipped with multiple antennas. The authors derive a closed-form expression of secrecy outage probability for the proposed TAS scheme. For the purpose of comparison, the authors also study the random antenna selection (RAS) as a baseline. Moreover, the secrecy diversity orders of TAS and RAS are analysed to provide an intuitive insight into the effect of the number of antennas on the secrecy outage performance. It is of interest to observe that the secrecy diversity order of TAS is the product of number of transmit antennas at CS and receive antennas at CD and the secrecy diversity order achieved by RAS scheme is the number of receive antennas at CD, which both have nothing to do with the number of antennas at eavesdropper. Finally, the simulation results validate the authors’ theoretical results and the proposed TAS outperforms the conventional RAS in terms of secrecy outage probability.

Time-division duplex (TDD) is the most efficient technique for acquiring channel state information in massive multiple-input multiple-output (MIMO) systems where the reciprocity between the uplink and downlink channels is utilised by the pilot signals to extract the channel parameters. In this study, the authors consider the pilot contamination problem in TDD multicell multiuser massive MIMO systems and examine two different pilot signal allocation schemes for which they derive the lower bounds on the achievable rate on the uplink for the cases of maximum-ratio combining (MRC) and zero-forcing (ZF) detectors. To achieve further performance enhancements, they propose a new algorithm for pilot sequences allocation in which the multiplicity of the pilot sequences over the number of users in each cell is exploited. The authors' results show that when pilot contamination is severe, allocating more system resources for channel estimation results in a better system performance especially in limited mobility environments. Moreover, they show that when the signal-to-interference plus noise ratio is low, MRC is superior to ZF, and vice versa. Finally, they demonstrate that their proposed allocation algorithm can significantly improve the spectral efficiency of the network compared to the conventional pilot allocation method.

In recent years, the vehicular ad-hoc networks (VANETs) have attracted plenty of attention. However, VANETs can hardly meet surging demands of mobile data. Device-to-device (D2D) communication is regarded as a promising method for providing the reliable connectivity between vehicles. The heterogeneous networks including conventional cellular network and VANETs, where the cellular links and the D2D-based vehicle-to-vehicle communication links coexist by reusing the same spectrum resources, result in a more complicated interference scenario. Thus the access mode switch and resource allocation between cellular and VANETs becomes a challenging issue. In this study, the authors formulate an optimal access mode selection and resource allocation scheme as a user aggregate utility maximisation problem with the joint consideration of various network topologies, transmission delay and power reduction. To reduce the high computation complexity, they provide a distributed algorithm that converges to a near-optimal solution via augmented Lagrangian technique. Numerical results show that remarkable throughput gains are achieved relative to the existing work, especially for large-scale networks. The network throughput can be considerably improved as well due to power reduction.

Spatial modulation (SM) is an efficient transmission scheme based on multiple-input multiple-output systems. SM, by nature, requires coherent detection to achieve optimal error performance. This requires that the receiver has full knowledge of the channel state information (CSI), however, determining the CSI results in an increase in the detection complexity at the receiver. Differential modulation systems are capable of performing detection without knowledge of the CSI at the receiver, however, they suffer a 3 dB error performance penalty as compared to their coherent counterparts. In this study, the authors present a generalised differential scheme for SM (GD-SM) based on generalised differential modulation, which is capable of reducing the performance penalty incurred through optimal power allocation. Furthermore, they extend the architecture of GD-SM and optimal power allocation to conventional differential SM. The architecture of the proposed systems, advantageously permits the use of either M-ary quadrature amplitude modulation or M-ary phase shift keying constellations. Simulation and theoretical results demonstrate that GD-SM incurs only about 0.5 dB performance loss as compared to coherent SM when the frame length is 400.

In massive multiple-input multiple-output (M-MIMO) systems, the base station (BS) estimates the downlink and uplink channels using the uplink pilot training in conjunction with channel reciprocity property of time division duplex (TDD) operation. However, this channel estimation is contaminated due to the use of non-orthogonal pilot sequences for the uplink training in neighbouring cells that results in inter-cell interference. This study proposes an effective pilot contamination elimination scheme along with zero forcing precoding for multi-cell TDD M-MIMO systems. In the proposed scheme, each BS is assigned with a specific orthogonal variable spreading factor (OVSF) code row and a set of Zadoff–Chu (ZC) sequences are used for uplink pilot training. Then, the set of ZC sequences is multiplied element-wise at each BS with its OVSF code row to generate the orthogonality among the pilot sequences across the neighbouring cells. The proposed method can promise uncontaminated channel estimation and interference free downlink transmission without requiring the knowledge of the channels’ second-order statistics and without increasing the training overhead by a factor equal to the number of interfering cells. The simulation results authenticate the effectiveness and superiority of the proposed scheme over other schemes.

In this study, the authors propose an improved localisation algorithm in the software-defined sensor networks (SDSNs). This algorithm includes a node-selection strategy under the whole network power constraint, based on the software-defined networking (SDN) technique for providing the centralised control of the network. The analogous Cramer-Rao lower bound (A-CRLB) value is derived for each participating node, which represents a fundamental bound on the variance of the position estimator and is used to evaluate the contribution of each node to localisation accuracy. On the basis of A-CRLB values, the most helpful nodes for localisation are selected to maximise the sum of the nodes' contributory values to the localisation accuracy. With the global network knowledge provided by the SDN controller in the SDSN, the node-selection strategy is formulated into a 0-1 programming problem on the premise of power satisfaction of each node. Furthermore, the proposed node-selection -based localisation algorithm is applied to both noncooperative and cooperative localisation scenarios. Simulation results show that the proposed algorithms provide efficient and effective localisation schemes in SDSNs, and can improve the performance in terms of both the selection convergence speed and the localisation accuracy.

The combination of forward error correction (FEC) and interleaving can be used to improve free-space optical communication systems. Recent research has optimised the codeword length and interleaving depth under the assumption of a fixed buffering size; however, how the buffering size influences the system performance remains unsolved. This study models the system performance as a function of buffering size and FEC recovery threshold, which allows system designers to determine optimum parameters in consideration of the overhead. The modelling is based on statistics of temporal features of correct data reception and burst error length through the measurement of the channel good time and outage time. The experimental results show good coherence with the theoretical values. This method can also be applied in other channels if a continuous-time-Markov-chain model of the channel can be derived.

It is commonly acknowledged that most of the output signals of digital receiver front-end are noisy and cannot be directly delivered to post-processing subject to the working condition and the limitations of devices. This study presents an improved singular value decomposition-based de-noising algorithm by the adoption of time-domain constrained optimisation. The improved algorithm contains a filter factor which plays a role in distributing information contributions of each retained singular value component to the de-noised signal, according to the relative contribution of noise in each singular value. The selection methods for several critical factors of the algorithm are discussed, including the noisy matrix, de-noising order, noise power and Lagrange multiplier. In particular, the effects of de-noising order and Lagrange multiplier on de-noising performance are studied. The results of the verification tests of extensive simulations and actual measurements from receiver front-end show that the proposed algorithm can significantly reduce the background noise and guarantee the integrity of the information contained in the de-noised signal.

Recently, there are increasing requirements of security in wireless communications, especially for the multiuser systems. In this study, the authors consider the security of two-hop cooperative multicast networks with an untrusted relay. An energy harvesting destination aided cooperative jamming framework is proposed to protect information from being intercepted by the untrusted relay. For the multiple destinations, a maximum interference jammer selection (MIJS) scheme is proposed to further improve physical layer security. Then the ergodic secrecy rate (ESR) for MIJS scheme is investigated and both the lower bound of ESR and the approximation of ESR are obtained. Finally, the effect of both the energy arrival rate and the number of destination nodes on ESR has been shown via numerical simulations. It can be revealed that as the number of destinations increases, the ESR is determined with two common behaviours regarding the multicast nature and energy arrival rate: (i) multicast nature forces the secrecy rate to decrease with the increasing number of destinations and (ii) the probability that a jammer exists increases with the increasing number of destinations but limited to one.

The author consider a relay-assisted, two hop, cooperative device-to-device (D2D) communication system where a source device S transmits data to a destination device D using a non-regenerative cooperative relay whose average transmit power is constrained. For the cooperative D2D system, the author consider the problem of optimally adapting the relay gain as a function of fading gains of S–R and R–D links to maximise fading-averaged spectral efficiency. The author derive the spectral efficiency-optimal relay gain adaptation policy (SERGAP), which determines optimal gain for the relay, and, analyse the fading-averaged spectral efficiency of SERGAP. To gain more insights, the author derive upper bounds on the average spectral efficiency, and, also investigate its asymptotic behaviour using an insightful analysis. Furthermore, the author extend the fading-averaged analysis to a system having multiple relays. The author also present numerical results for single relay and multiple relay systems and benchmark the proposed policy's performance with conventional and suboptimal relaying policies. The author show that SERGAP delivers higher average spectral efficiency than conventional relaying policies. Finally, spectral efficiency-optimal relay placement for the proposed policy is also investigated via simulations, and, the author find that it is different from the suboptimal relaying policies.

This study addresses the joint pricing and service selection problem between two primary operators (POs) and multiple secondary users (SUs). The SUs are divided into two priority classes in terms of their delay-sensitive demands. A M/G/1 queueing model of four queues is established, in which each PO serves two queues to support SUs' heterogeneous sensitivity to price and delay. A unique Wardrop equilibrium point of the proposed service selection strategy is developed, at which not only the overall cost perceived by SUs at two POs are equal; however, the cost perceived by SUs of the same PO in different class are equal. Moreover, the authors propose two pricing strategies for maximising the revenue of POs. The first one is that both POs set their prices simultaneously, the second one formulates the price competition as a two-stage Stackelberg game, and then the authors show the existence of a unique Nash equilibrium. The performance of the proposed mechanism is finally verified by numerical results.

In massive multiple-input multiple-output (MIMO) high-speed train (HST) wireless communication systems (WCS), due to the large-dimension and rapidly time-varying property, channel tracking rather than conventional channel estimation is more feasible. Due to the non-linear channel variation, the channel is first decomposed into sub-channels with different angle of departure. By exploiting the property of near line of sight (LoS) and location information, Kalman filtering is used to track the channel by predicting and modifying the channel gain of the LoS sub-channel. To further improve the tracking performance, a location-based sequentially optimal beam pattern design is proposed. Since placing pilot beams for many receive antennas with different locations in time or frequency division manner costs much system resource, the authors further propose a low-complexity grouping algorithm based on location. Finally, two transmission designs based on the proposed channel tracking scheme and the location only, respectively, are introduced. Simulations validate the efficiency of the authors' proposed tracking scheme and the corresponding transmission design, which shows the importance of location information and channel tracking in massive MIMO HST-WCS.

Two-way relay is potentially an effective approach to spectrum sharing and aggregation by allowing simultaneous bidirectional transmissions between source–destinations pairs. In this study, the two-way relay network, a class of four-unicast networks, where there are four source/destination nodes and two relay nodes, with each source sending a message to its destination, is studied. They show that without relay caching the total degrees of freedom (DoF) is bounded from above by , indicating that bidirectional links do not double the DoF (it is known that the total DoF of one-way relay network is 2). Further, they show that the DoF of is achievable for the two-way relay network with relay caching. Finally, even though the DoF of this network is no more than for generic channel gains, DoF of 4 can be achieved for a symmetric configuration of channel gains.

To obtain a robust physical-layer network coding (PLNC) for two-way relaying system, the authors propose a low-density parity-check (LDPC) coded PLNC scheme with phase pre-rotation to combat the carrier phase asynchronous in the multiple access stage. At two users, each modulation symbol is rotated according to a predefined incremental phase without the knowledge of carrier phase difference. Decoding simulation and numerical analysis are carried out to evaluate this joint LDPC and PLNC scheme with phase pre-rotation. Simulation results show that this strategy can achieve a significant improvement and a good trade-off between performance and complexity. Protograph-based extrinsic information transfer analysis demonstrates the proposed scheme is robust, which is consistent with the simulation results.

In this paper, we consider the problem of estimating the infection probability of nodes in backward time steps of worm propagation with Bayesian networks. The infection probability of a node at each time depends on the out-degree of the node and the number of infectious nodes at that time. It is assumed that we have prior knowledge of worm infection parameters and also the number of susceptible, infectious and removed nodes at a time of worm propagation. The out_degree of a node is needed at each time step for estimation. It also needs to learn a degree distribution model over time based on the observation of historical out_degree of nodes in the network when the spread of worm happens. We applied simulations to study the accuracy of our probability distribution. The results of simulation indicate that the probability distribution predicts the infection probability of nodes at each prior time step with high accuracy. This method can be used to infer the origin and worm propagation path. This method has low storage and computational requirements, and also less limiting assumptions compared to other methods of estimating the origin nodes of epidemic spread.

In this study, the authors consider a decode-and-forward (DF) relaying protocol with full-duplex wireless information and power transfer, and investigate its outage performance. In this protocol, a cooperative relay can transmit the information to the destination and harvest the energy from the source simultaneously. Thus, part of the energy used by the relay can be recycled through the self-loop channel that exists in the relay's full-duplex operation. An approximated expression for the outage probability is derived under the scenario where the self-loop channel is fading, and then the authors derive an exact closed-form expression for the outage probability under a scenario where the self-loop channel is non-fading. Moreover, to optimise the outage performance, a power allocation scheme is also provided. The authors analyse the effect of self-loop channel on the outage performance, and show that, benefiting from the full-duplex operation and self-energy recycling, the considered protocol is superior to the existing power splitting-based and time switching-based DF relaying protocols, in terms of outage performance. Simulations are provided to validate the authors' results.

To detect the presence of primary users, spectrum sensing is considered as one of the most important and basic functions of cognitive radio. To improve the detection probability in spectrum sensing, this study mainly investigates the effect of channel gain and signal-to-noise ratio to secondary users (SUs) cooperation in weighted combining energy detection. In particular, with the objective to maximise the detection probability, optimal linear combining weights are derived as well as optimal transmit power of each SUs for sensing data transmission from the SUs to the fusion centre. Simulation results indicate that the detection probability can be improved by the presented scheme and the performance of the proposed method outperforms some recent works detection.

A root mean square (RMS) delay spread model in indoor femtocell scenarios is proposed. The proposed model is based on extensive channel sounding of indoor stair, corridor and office environments. In this model, the RMS delay spread is described as a linear function of the path loss, and a normal stochastic variable is introduced and utilised to characterise the deviation of the measured RMS delay spread from the linear function. The proposed model can be used to simulate the RMS delay spread directly from extracted model parameters and the separation of the transmitting and receiving antennas. The closed-form formulas for fast calculating the mean value and variance of the RMS delay spread using some deterministic values, including the femtocell coverage distance and the parameters of the proposed model, are derived. The validity of the proposed model is verified by comparing the cumulative distribution functions and the statistical values of the measured and simulated RMS delay spread.