Clustering is an important method for extending the network life of each node in wireless sensor networks. Owing to the untrustworthy environment, these nodes unintentionally sacrifice their energy and lost their life which is a major challenge and requires appropriate attention for smooth communication. Thus energy efficiency and network life period both are major concerns in critical and sensitive real-life applications such as military applications, landslide monitoring etc. This study reviews and analyses existing trust-based clustering routing protocols for a complete understanding of research contribution to date made by researchers of this domain. In addition, a novel trust-based energy efficient protocol based on a Whale Optimisation Algorithm named WOATCA has been presented. This algorithm focuses on the selection of trust worthy nodes as cluster heads (CHs) by considering five parameters namely (i) node's residual energy, (ii) number of packets forwarded by a node, (iii) average cluster distance, (iv) transmission delay, and (v) node density. Simulation results and analysis demonstrate that WOATCA outperformed existing protocols by showing a percentage decrease of 87.85, 64.58 and 61.36% in the selection of compromised nodes as CH in comparison with existing trust-based schemes such as Adoptive LEACH Mobile (ALM), Topology Control Algorithm for node mobility (TCM), Q12 and secure CH selection protocols, respectively.

This study aimed at analysing intercarrier interference (ICI) of filter bank multicarrier signals which are made by hyperbolic fractional Fourier transform, depend on optimum order of transform for the Internet of Things applications. Calculation of ICI power based on joint time and frequency selective fading channel has been derived. The upper bound of ICI power has been found as an applicable equation for the system design, which has been mathematically calculated. In order to minimise the amount of ICI power which is relative to the order of transform, the optimum order of transform with almost accurate formula has been computed. Simulations demonstrate the proposed signal is so robust to the frequency offset and by selecting the optimum order of transform, the acceptable amount of ICI is generated.

This study investigates codes in the term-rank metric. These codes can be used to correct crisscross errors in a () matrix. These errors can be found in memory chip arrays, in magnetic tape recordings, or in the parallel-channel system with interference. In this study, the authors will build an algorithm for computing term-rank of a matrix and new construction of term-rank codes. Single error-correcting codes in the term-rank metric are considered and help us build a generator matrix and parity-check matrix for term-rank codes. Research results derived from this study show that the term-rank metric is suitable for correcting crisscross errors.

In this study, the authors explore a wireless network consisting of multiple smart terminals relying on multi-mode in the presence of an eavesdropper, where the eavesdropper may be deployed to wiretap the wireless communications deliberately. In general, a smart terminal can be switched between the licensed modes (e.g. LTE) and the unlicensed modes (e.g. WiFi) according to user's demands (e.g. costs). The designed tradeoff is that the demands can be met by switching, but the security of wireless transmissions may be deteriorated, as the wireless communications can be overheard by the eavesdropper. The authors propose a transmission mode aware smart terminal scheduling (TM-STS) scheme to improve the security of wireless transmissions of a smart terminal. Moreover, they analyse the security-reliability tradeoff (SRT) of the TM-STS scheme. They also present the SRT of the conventional round-robin aided smart terminal scheduling (Rr-STS) scheme. Numerical results show that the TM-STS scheme outperforms the Rr-STS scheme in terms of its SRT, and reveal that increasing the number of smart terminals not only can upgrade the SRT of the TM-STS scheme, but also can be a major influence on the probability of mode switching between a licensed mode and an unlicensed mode of the TM-STS scheme.

This study considers a downlink power consumption problem for unmanned aerial vehicles (UAVs)-assisted wireless communications, in which UAVs are used as aerial base stations to provide service for the ground users and equipped with a directional antenna of fixed beamwidth. Moreover, the on-board circuit power of UAV is taking into consideration. The authors derive a closed-form expression for the optimal flying altitude and number of UAVs by minimising the total power consumption under the users' rate requirements in the given coverage area. The numerical simulation and theoretical results show that the optimal flying altitude of UAVs depends on the beamwidth of the directional antenna at UAVs, the on-board circuit power of UAVs, and the rate constraint of each user.

In this study, joint users selection and beamforming based on users positioning are proposed for enabling non-orthogonal multiple access (NOMA) in the millimetre-wave (mmWave) transmissions. In the proposed scheme, the mmWave users are arranged in descending order based on their estimated distances from the mmWave base station (BS), which guarantees the users ordering based on their line-of-sight availability, as well. Out of the ordered users, the two users having the minimum pairing angle and expected to lie within the specified mmWave beamwidth are selected as the two NOMA users. In this study, the users' pairing angle is defined as the maximum expected difference angle between two users considering their location-uncertainty areas. Consequently, the BS antenna beam is formed towards the two selected NOMA users by adjusting its boresight angle to lie in between their estimated location angles. Then, the fixed power allocation scheme is used to adjust the power allocation coefficients of the selected NOMA users. Mathematical analysis is performed to bound the performance of the proposed mmWave NOMA scheme. Also, numerical simulations are conducted to prove the mathematical findings and to show the superior performance of the proposed scheme over the well-known technique of using random beamforming.

Massive multiple-input multiple-output (MIMO) systems with hundreds of correlated antennas at base station are capable of offering abundant spatial resources. When spatial-domain modulation is applied to these systems, the spatial modulation (SM) using only one radiofrequency chain benefits practical implementation, but suffers from significantly reduced multiplexing gain offered by the massive number of antennas. By contrast, the generalised SM (GSM) allows to simultaneously activate multiple transmit antennas, which improves spatial multiplexing gain, but degrades the achievable error performance, as its design pays no attention to the antenna correlation. The authors propose an antenna grouped SM (GrSM) scheme, which is capable of circumventing the shortcomings of both the SM and GSM schemes suffered in massive MIMO scenarios. In the proposed GrSM scheme, transmit antennas are partitioned into multiple groups, where the relatively strongly correlated antennas within individual groups are used to implement component SM schemes, while the relatively weakly correlated antennas in different groups are beneficial to obtain multiplexing gain. In order to further improve the spectral efficiency, adaptive modulation is integrated with GrSM to form the adaptive GrSM (AGrSM). The achievable error and spectral efficiency performance of GrSM and AGrSM systems are investigated based on both mathematical analysis and Monte-Carlo simulations, which are also compared with that of the conventional SM and GSM schemes, when massive MIMO communication scenarios are considered. Their studies and performance results show that GrSM is a promising transmit scheme for massive MIMO, which can outperform both the SM and GSM schemes.

In this study, the authors analyse the downlink (DL) performance of dynamic-time division duplexing (D-TDD) enabled millimetre-wave (mmWave) network with different base station (BS) heights using a channel model that incorporates the effect of shadowed fading. Modelling the combined effect of small and large (shadowing) scale fadings with shadowed fading, they provide a general framework based on stochastic geometry that comprehensively includes the smallest path loss BS association with either a line-of-sight (LoS) path or a non-LoS (NLoS) path. For the precise analysis of the network, they further consider different PL distributions for NLoS and LoS links which are associated with the 3D distance, blockage model that includes outage, and directional beamforming at the transmitter and the receiver. Specifically, they assume the directional beamforming at the transmitter and the receiver using scanning angle and number of antennas. Through simulation results, they first illustrate the performance efficiency of D-TDD over the static-TDD for DL mmWave networks. Later, they show the impact of shadowed fading parameters on the network performance under the both LoS and NLoS propagations, and only NLoS propagation. Next, the effect of BS heights on the coverage of the network is investigated to provide more insights on the performance in more realistic scenarios. Finally, the coverage of the network is analysed using the varying number of transmitting antennas, scanning angle and BS heights.

Hybrid precoding, combining the digital and analogue precoding, is a key enabler to reach a compromise between system performance and hardware complexity in millimetre wave (mmWave) massive multiple-input multiple-output (MIMO) systems. Most previous studies on hybrid precoding considered narrowband channels. However, mmWave systems are expected to operate on wideband channels with frequency selectivity. In this study, the authors focus on the hybrid precoding design in mmWave massive MIMO systems using orthogonal frequency division multiplexing (OFDM). By transforming the hybrid precoding problem into a series of sub-problems, they propose a low-complexity algorithm to design the digital precoder and analogue precoder alternately. In particular, a phase pursuit method is introduced to seek this solution of analogue precoding matrix with the constant amplitude constraint. Simulation results and complexity evaluations reveal that the proposed algorithm can obtain better performance and lower complexity than some existing solutions in mmWave OFDM systems.

This study introduces an accurate design and optimisation of a passive optical code division multiple access (OCDMA) network encoder using the coupled cavity waveguide (CCW) as an optical delay line. Such CCW has the capability of providing more time delay with minimum encoder size. The proposed design and analysis are based on the two-dimensional (2D) photonic crystal (PhC) structure. Additionally, two different 2D-PhC structures are studied, in which a silicon material with an effective refractive index of 3.487 is used. The first structure is a silicon bar in air background, whereas the second one is air holes in a silicon substrate. Furthermore, the behaviour of the proposed 2D-PhC structures is studied over the wavelength, ranging from 1300 to 1600 nm. Since the structure geometry is simple with a clear operating principle, it is sufficient to use in the photonic integrated circuits. Moreover, the performance analysis of such design is investigated in terms of the bit error rate (BER) calculations. Finally, the results showed that a 21% BER performance enhancement was achieved using the optimised silicon bars in air background encoder model and this model can be utilised for the multimedia applications in the OCDMA networks.

Internet of things (IoT) is one of the modern technologies, developing existing cellular communication networks to the emerging fifth-generation technology. The traffic modelling of IoT applications is different from the recommended traffic modelling of a Human-type communication. Numerous unstructured data arise from rapid growth of IoT heterogeneous networks and services. One of challenges occurs by diverse IoT unstructured data is a variety of IoT data characteristics, which increase traffic modelling influences. The study of IoT characteristics has a crucial role in modelling data bursts of IoT use cases. This study proposes an enhanced ON/OFF traffic modelling technique to model IoT data characteristics of diverse applications, especially the IoT smart city. A novel modelling technique categorises and analyses characteristics of IoT smart city use case into five major traffic patterns. In this study, realistic smart home networks were built as a part of IoT smart city in an experimental model. Massive traffic profiles are generated from a pilot according to a proposed IoT smart city architecture model. Various traffic profiles of a pilot are modelled into theoretical models by Easy-Fit tool. Traffic modelling concept of a novel technique and their five traffic patterns are proven in the pilot results.

A novel direction-of-arrival (DOA) estimation method based on electronically controlled beam scanning leaky-wave antenna (LWA) combined with estimation of signal parameters via rotational invariance techniques (ESPRIT) algorithm is proposed. In order to implement this method, a virtual partial pattern synthesis method is presented to construct an array manifold of subarrays from LWA for the ESPRIT algorithm. Then, the multi-channel receiver model and signal subspace are established based on the beam scanning property of LWA. As the traditional array antenna is substituted by LWA, the rotation operator of the algorithm has to be changed. From this point, the preprocessing ESPRIT algorithm based on the Hadamard product is proposed to extract the directional matrix of LWA. Numerical simulations are conducted, and the DOA performance is demonstrated through estimation error, response rate, and compared with the Cramer-Rao bound. Simulation results show that the DOA method utilising LWA exhibits satisfactory estimation performance and fast response speed. In addition, the influence of antenna parameters on the estimation accuracy and the method to improve the performance of DOA estimation for LWA are discussed.

This study proposes a scheme to realise secure orthogonal frequency-division multiplexing (OFDM) wireless communication between two full duplex nodes—node A and node B. If node A wants to send secret messages to node B, node A and node B transmit the training signal to each other to acquire channel state information (CSI) in the first time frame. Node A acquires the phases of the received signal from node B (no need to decode). In the second time frame, node A then sends secret messages to node B with the phases of the modulated signal being added to the random phases of the signal from node B in the previous time frame, i.e node A relaying the phases of the signal from node B. Node B can recover the secret messages from node A, but eavesdroppers cannot because they do not know the CSI of the main channel. The secrecy capacity is irrelevant to the CSI of the eavesdropper channel, which is a big advantage over other schemes. The scheme can guarantee secrecy capacity to be positive in all circumstances and work well for single-input single-output systems. A computation efficient algorithm is presented to optimally allocate power over sub-carriers for secrecy capacity maximisation.

Wireless sensor network (WSN) consists of spatially distributed miniature size and autonomous nodes along with batteries as a power source. The major bottleneck of WSN is efficient energy utilization. The energy consumption for transmission of signals increases with the distance. This problem of energy consumption is addressed in this study. This study presents a strategy, namely distance-based dynamic duty-cycle allocation (DBDDCA) algorithm. In DBDDCA, longer distance nodes from cluster head (CH) transmit relatively less time in order to save energy. Conversely, transmit for the higher time when the distance is near to CH. The proposed DBDDCA is compared with the other existing strategies: low-energy adaptive cluster hierarchy (LEACH), modified leach, and stable election protocol and with two existing medium access control (MAC) protocols: sensor (S)-MAC and timeout (T)-MAC. The performance of the proposed and existing strategies is evaluated with the following network parameters: energy consumption, network energy utilization, network lifetime, latency, and packets delivery. These parameters have been evaluated with different network scenarios such as number of nodes increases, number of rounds, and with variation in initial energy of nodes. Simulation results show the performance of the proposed strategy is significantly better than the existing strategies under the investigated network parameters.

The need to maximise energy efficiency (EE) for device-to-device (D2D) communication has become an urgent necessity for the fifth-generation wireless networks. In this study, the power allocation problem is considered for the cellular system underlaid with D2D users (DUs) to maximise the EE for the whole network. Firstly, the random distribution of DUs and cellular users (CUs) are described by utilising the homogeneous Poisson point process based on stochastic geometry. Secondly, successful transmission probabilities are deduced. Finally, the optimisation problem for maximising EE is formulated to determine the optimal power values for both D2D and CUs. An adaptive mesh size algorithm is suggested to solve the non-convexity of the EE optimisation problem. Simulation results prove that the suggested technique has the ability to accomplish the near-optimal EE. Furthermore, it has superior performance when compared with the related algorithms.

Breaking down botnets has always been a big challenge. The robustness of command and control (C&C) channels is increased, and the detection of botmaster is harder in peer-to-peer (P2P) botnets. In this study, the authors proposed a probabilistic method to reconstruct the topologies of the C&C channel for P2P botnets. Due to the geographic dispersion of P2P botnet members, it is not possible to supervise all members, and there does not exist all necessary data for applying other graph reconstruction methods. So far, no general method has been introduced to reconstruct C&C channel topology for all type of P2P botnet. In their method, the probability of connections between bots is estimated by using the inaccurate receiving times of several cascades, network model parameters of C&C channel, and end-to-end delay distribution of the Internet. The receiving times can be collected by observing the external reaction of bots to commands. The results of their simulations show that more than 90% of the edges in a 1000-member network with node degree mean 50, have been accurately estimated by collecting the inaccurate receiving times of 22 cascades. In case the receiving times of just half of the bots are collected, this accuracy of estimation is obtained by using 95 cascades.

In this study, the problem of adaptive modulation and frame length (AMFL) is investigated in long-term evolution for railway (LTE-R) communication system. By considering the effect of frame length, a novel AMFL strategy based on Moore state machine (MSM) is proposed. The influence of the frame length on the goodput is discussed by theoretical analysis and simulation evaluation. According to modulation and frame length schemes (MFLSs) adopted in LTE-R system, the finite state set of the MSM is designed. For different MFLSs, the frame error rate (FER) and signal-to-noise ratio (SNR) curve is obtained. By giving a target FER, the SNR thresholds corresponding to different MFLSs are achieved. From the perspectives of modulation priority and frame length priority, two different AMFL-MSMs are designed to change MFLSs dynamically. Simulation results show that the proposed two AMFL-MSMs have more stable goodput than the common modulation schemes and less symbol energy consumption than the high-order modulation scheme. In addition, the AMFL-MSM with modulation priority has better performance than the AMFL-MSM with frame length priority in terms of goodput stability.

Holographic data storage (HDS) can access data in a short amount of time and can also quickly transmit data because HDS records and reads data in units of pages. Thus HDS is regarded as a promising candidate for future optical recording storage systems. Conventional storage systems such as CD, DVD, and HDD have one-dimensional (1D) inter-symbol interference (ISI). However, HDS has a 2D ISI that degrades performance. In this study, to avoid and overcome the 2D-ISI problem, the authors propose a 14/16 modulation code for 4-ary HDS systems which represents 2 bits on each pixel. The proposed 14/16 modulation code allows a bit of unwanted ISI cases in order to raise the code rate, but it has a higher code rate but similar performance compared to a 3/4 modulation code that has no unwanted ISI cases.

The Cognitive Radio (CR) plays a key role in identifying free bandwidths in the Radio Frequency (RF) spectrum. High-speed Analog-to-Digital Converters are normally applied for spectrum sensing of sideband signals providing several raw data for digital signal processors resulted in energy-inefficient complex circuits and hardware resources in digital signal processing blocks. In some instances, the frequency spectrum is sparsely occupied by various users, i.e., only a few active frequency bands exist at the same time. This feature enables CR application to use sub-Nyquist sampling approaches for designing a system representing significantly reduced cost and power consumption, as well as improved processing speed. The current paper introduced a novel Cooperative Real-valued Sparse Spread Spectrum Sensing algorithm (CR4S) based on a sub-Nyquist sampling approach by employing the sparsity of the frequency spectrum and the real-valued properties of the RF signal to identify free bandwidth with minimum computational complexity. The CR4S algorithm aimed at improving CR spectrum sensing by utilizing techniques such as Real-valued FFT, Sparse Fast Fourier Transform, and collaborative spectrum sensing. The proposed algorithm has been approved by simulation to above 95% detection performance. The performance enhancement in the CR4S algorithm is an emerging advance being fascinating for portable CR devices.

There are two main classes of decision fusion methods, namely hard decision fusion (HD) and soft decision fusion (SD), in which the number of bits transmitted by each local sensor to the fusion centre (FC) is always same, namely one bit in HD and n (n ≥ 2) bits in SD. However, considering that there is always a limit of bandwidth in a distributed detection system, the number of bits sent by each local sensor to the FC does not need to be the same and should be allocated reasonably and suitably. Therefore, this study proposes an optimal bit allocation scheme based on the memetic algorithm, in which the number of bits transmitted by each local sensor could be different. This scheme aims to maximise the detection probability under the limit of bandwidth for a detection system with imperfect channels. The overall detection probability objective function about the number of allocated bits is derived. To optimise this objective function, an improved memetic algorithm with two local adjustment strategies, namely non-elite learning local adjustment optimisation strategy and elite greedy local adjustment optimisation strategy, is proposed to allocate the optimal number of bits. Simulation results show the efficiency and effectiveness of the proposed scheme.