Modulated wideband converter (MWC) is a compressed spectrum sensing system that randomly moves the sparse wideband signal spectrum to the baseband to realise low-speed sampling. Then, obtaining the effective support which is based on compressed sensing is the most important part for the signal recovery from samples. Aimed at the poor anti-noise performance of the support recovery, a relevant support recovery algorithm (RSRA) is proposed in modulated wideband converter for spectrum sensing. Specifically, the optimal initial support index is obtained by least squares. Then, the correlation between the measurement matrix column vector corresponding to the adjacent index and the sampling matrix is calculated, and the adjacent index with larger correlation is added to the support. The whole support is acquired by iterative updating under the thought of matching pursuit. Being different from other algorithms, RSRA takes the correlation about adjacent indexes into account, which can weaken the noise interference. Theoretical analysis and numerical simulations show that the proposed scheme can improve the recovery rate of effective support in lower SNR. While improving the anti-noise capability, other aspects of performance such as channels number and sparsity will not be sacrificed.

The interference between filtered multi-tone (FMT) symbols exists and becomes conspicuous especially in frequency selective fading channel, like an underwater acoustic channel. This leads to the necessity of channel estimation and equalisation. In this study, the authors consider two approaches to utilise the channel sparsity to improve FMT channel estimation performance and further reduce bit error rate in underwater acoustic communications. While the first studies FMT sparse channel estimation in the time domain and is based on received FMT signal and known transmitted FMT signal that is reconstructed by pilots, the second is based on matched filtering demodulated FMT symbols and pilots. Theoretical analysis is performed followed by simulation and experiment accordingly. It is found that the first method is able to successfully estimate the sparse channel while the estimation performance of the second method is unsatisfactory due to poor orthogonality between bases of the channel estimation matrix. Moreover, the lake experiment is carried out with the first method and its results prove that sparse channel estimation has better performance than least square channel estimation.

This work addresses frequency synchronisation and channel estimation for highly frequency selective orthogonal frequency division multiplexed systems with offset quadrature amplitude modulation. A two-step approach is proposed, wherein a coarse carrier frequency offset (CFO) estimator, which does not require channel knowledge, is designed in the first step by exploiting the correlation between the received and training signals. A time-domain model is derived for the joint estimation of fine CFO (FCFO) and highly frequency selective channel in the second step. In contrast to the frequency domain model in the literature, the derived time-domain model does not require the channel to be frequency flat. Based on the time-domain model, the weighted least squares and minimum mean square error estimators are investigated to jointly estimate the FCFO and frequency selective channel. The Cramer-Rao lower bounds (CRLBs) are derived for the proposed estimators, and are used to evaluate the performance of the joint FCFO and channel estimation in the presence of inter-symbol-interference due to the overlapping of adjacent time-domain orthogonal frequency division multiplexing/offset quadrature amplitude modulation (OFDM/OQAM) symbols. Simulation results demonstrate achievability of the CRLB bounds and performance gain of the proposed estimators over the state-of-the-art existing estimators.

In this article the performance of grey-coded advanced optical modulation formats is evaluated on a single-channel high-speed long-haul optical communication link and are compared to the respective differential-coded modulation formats. Polarisation division multiplexed optical in-phase quadrature modulator (IQM) structure and homodyne detection scheme are used to realise 100 Gbps quadrature phase-shift keying (QPSK), 120 Gbps 16-ary quadrature amplitude modulation (16-QAM), 360 Gbps 32-QAM and 480 Gbps 64-QAM modulation formats. Advanced digital signal processing unit with various pre-processing and recovery stages such as direct current blocking, normalisation, low-pass Bessel filter, resampling, quadrature imbalance compensation, chromatic dispersion compensation, non-linear compensation, timing recovery, adaptive equalisation, down-sampling, frequency offset estimation, and carrier phase estimation is used at the receiving end to compensate for signal impairments during propagation. Maximum transmission distances of 7200, 1050, 560, and 360 km have been achieved at an acceptable bit error rate for QPSK, 16-QAM, 32-QAM, and 64-QAM, respectively. The grey-coded systems outperformed the differential-coded systems regarding optical signal-to-noise ratio requirement, receiver sensitivity, and transmission distance.

With limited resources, it is quite challenging for cloud providers to meet dynamic and massive customers' demands. Higher utilisation or refusing any service level agreement (SLA) may lead to penalties which play a crucial role in the cloud business. Overutilisation of resources, instead of maximizing the revenue, may lead to a decrease in revenue due to the SLA violations. Various studies have been conducted to investigate these issues; however, there is still room for improvement. In this study, the authors proposed a model to address the resource scalability and SLA violation issues by hiring external resources at low prices. However, in contrast to a federated cloud, the proposed model allows a provider to hire resources from any external provider with flexible terms and price. They designed algorithms to optimise providers' revenue by taking into account different parameters, including resource utilization, customer satisfaction, SLA violation, and prices. Simulation result shows that the proposed model is efficient in handling massive demands, and improves revenue generation and customer satisfaction. Offering joint pricing on customers' choice and outsourcing the extra workload to external resources leads to revenue maximization. Hiring external resources earns external revenue as well as it maximizes the total revenue.

Although multiple-input multiple-output (MIMO) technique is used in free space optical (FSO) systems to reduce the effect of atmospheric turbulence, however, employing this technique without sufficient attention to the interference of laser beams not only does not reduce the effect of atmospheric turbulence, but also it can significantly degrade the performance of the FSO system. This study investigates that the average intensity of laser beams at the receiver aperture of MIMO FSO systems is very sensitive to small variations of path lengths between the transmitter and receiver. Therefore, the destructive interference that degrades the performance of MIMO FSO systems compared to equivalent single-input single-output (SISO) FSO ones is due to the difference in path lengths of laser beams between transmitter and receiver apertures. For this reason and in order to mitigate the interference effect, the authors compensate small changes of path lengths through adjusting the sending times and the initial parameters of laser beams in the transmitter apertures. The authors' analysis supported by numerical results show that the adjustment of laser parameters could increase the chance of peak intensity of MIMO-FSO systems to be higher than the peak intensity of equivalent SISO-FSO ones.

Wireless sensor network in the industrial environment [industrial wireless sensor network (IWSN)] has data delivery time constraint. Due to the dynamic routing and transmission collision, the data delivery time is unpredictable. The authors utilised time division multiple access (TDMA) MAC to avoid data collision and to provide bounded transmission delay. Moreover, a linear programming model is proposed to construct the TDMA schedules, which is focused on spatial reuse and fixed routing in IWSN. The objective function of the model is to minimise the time slot usage to increase the overall network bandwidth. Finally, both simulated annealing algorithm and particle swarm optimisation are applied to approximate the optimal solution of time slot usage.

The unmanned aerial vehicle (UAV) channel measurements have shown that the propagation environment of UAV channel is non-stationary. In this study, a three-dimensional (3D) non-stationary UAV multiple-input multiple-output (MIMO) channel model is proposed. In order to sufficiently describe the propagation environment of UAV-MIMO channel, the stationary scatterers and moving scatterers are investigated in the proposed model, which are mimicked using 3D cylinder and two-dimensional (2D) disc, respectively. The Doppler shifts associated with moving scatterers are also considered in the proposed model. The movement of UAV, receiver, and moving scatterers results in non-stationarities, and time-variant distances, azimuth angles, and elevation angles are investigated in the proposed model. The statistical properties of the moving scatterers are also investigated in the proposed channel model. In order to validate the proposed model, the spatial correlation is compared with the measurement results, and the numerical results show that the proposed channel model is applicable to describe the UAV-MIMO communication systems.

Indian regional navigation satellite system (IRNSS) is a navigation system developed by the Indian Space Research Organisation (ISRO), India. The IRNSS receiver granted by Space Application Centre (SAC), ISRO, Ahmedabad is installed at SVNIT, Surat, India. A solar flare is a natural event that occurs when an unpredicted flash of distended Sun's illumination is observed near its surface. The ionosphere is greatly ionised by solar radiations. Hence it is a current challenge to investigate effects of ionospheric scintillation on IRNSS signals. This study examines impact of major solar flare events like Class ‘C’ solar flare happened on 22 July 2016 and class ‘M’ solar flare occurred on 23 and 24 July 2016, on IRNSS signals with measurement of total electron content (TEC). Real-time ionospheric scintillation monitoring (RTISM) model based on empirical mode decomposition (EMD) and second-order Daubechies (db2) wavelet is used for comparing measured and denoised TEC. The RTISM model is also used for determining automatic threshold using Neyman–Pearson detector, probability of detection and probability of false alarm. It is proven with analysis that EMD is giving more sharp results as compared to db2 wavelet for determining fluctuations in TEC during the solar flare events.

In fibre-wireless (FiWi) access networks, the achievement of survivability becomes critical because any failure of FiWi components may result in severe traffic interruptions. In this study, the authors proposed a new backup fibre deployment mechanism with the consideration of time-varying daily traffic demand. Firstly, a new remote node structure for the protection of switching is established to help the backup fibre deployment. Secondly, they formed a minimum deployment cost problem in terms of the daily traffic demand and interrupted traffic protection. Furthermore, a two-stage algorithm is proposed to solve this problem and obtain an optimal deployment pattern. Simulation results demonstrate that the proposed mechanism can reduce the cost of the backup fibre deployment and the delay of the interrupted traffic recovery significantly.

Bit error rate (BER) and channel capacity are two important metrics to assess the performance of free-space optical communication (FSOC) systems. Due to the fading of the optical signal owing to the atmospheric effects, these two quantities behave as random variables. Most of the studies in this direction have focused on the calculation of only the average of these quantities. However, since the complete information about a random variable is encoded in its distribution, it is more informative to examine the latter itself. In this work, the authors derive exact probability density function (PDF) expressions for the BER and the channel capacity for an arbitrary irradiance model. In particular, they investigate these exact results for log-normal, gamma-gamma, and K distributions. For the BER analysis, they focus on the binary phase shift keying and quadrature phase shift keying modulation schemes. The authors' analytical reults are found to be in conformity with Monte Carlo simulations. The exact PDFs of the BER and the channel capacity reveal that there are several instances when the average is unable to capture the actual behaviour of these quantities, and therefore one must be careful in drawing conclusions based on the first moment only.

Nowadays, most of the research focuses on the distributed algorithm to form the clusters in wireless sensor networks, in which the sensor nodes act autonomously to self-configure themselves with the help of the local information. However, the issues in such distributed mechanisms are (i) how to assign the time division multiple access (TDMA) schedule to collect the data from the cluster member (CM), (ii) how to distribute and balance the overall energy consumption of the cluster heads (CHs) under the circumstance of node's mobility. To overcome these problems, a cluster switched data gathering protocol (CSDGP) is proposed which ensures a uniform distribution of CHs by utilising a waiting time-based CH selection and an effective cluster switch based TDMA scheduling mechanism. The salient feature observed in the proposed CSDGP is that the migrated node has a chance to transmit the sensed data to the CH, whenever the CH has a free time slot. From the simulation results, it is proved that CSDGP provides a good performance under three different scenarios in comparison with existing protocols in terms of average energy consumption, average end-to-end delay, packet delivery ratio, and control overhead.

Security of confidential data at the physical layer has been analysed in a network where the source sends the confidential data to the destination via multiple energy harvesting decode and forward relays in the presence of a single eavesdropper (EAV). In this two-hop communication, the first hop is broadcasting hop when the source sends the information signal to relay and other is the relaying hop when a selected relay forwards the information signal as well as transmits a jamming signal to destination and EAV. Each relay has the two batteries; one for accumulating the harvested energy and the other for power supply to relays for relay operation over a number of frames until the accumulated harvested energy becomes sufficient. In the broadcasting hop, relays harvest energy using a power splitting ratio scheme and accumulate the harvested energy in the battery over a number of communication frames. The performance is analysed in the form of secrecy outage probability (SOP) when the relay uses only the harvested energy to forward the signal. A closed-form analytical expression for the SOP is derived. MATLAB-based simulation results match well with the analytical results.

The most famous and attractive strategy used in wireless communication for huge transmission of data with higher rate was orthogonal frequency division multiplexing (OFDM) approach. Efficient methods are important for PAPR reduction in high-speed wireless communication systems. The reduction of PAPR in OFDM system has been carried out with one of the most familiar approach called Partial transmit sequences (PTS). Various techniques are already presented for reducing the PAPR, some of them are, clipping, SLM, and PTS. From that PTS is considered as an efficient method because the PAPR was reduced by PTS without causing any signal distortion. In this work, PTS along with hybridization optimization algorithm named as PS–GW will be implemented to get the minimum performance on PAPR and computational complexity. The PS–GW is a combination of both the Particle Swarm Optimization (PSO) and Grey Wolf Optimizer (GWO) which search the optimal combination of phase rotational factors efficiently. A fundamental thought in this method was that the capacity of exploitation in PSO was enhanced with the capacity of investigation in GWO to create a two variations in quality. The results produced by this proposed method shows that the reduction was effectively determined in both PAPR and computational complexity.

A system that employs wavelength division multiplexing (WDM) in conjunction with sub-carrier multiplexing (SCM) tones is proposed to realise high data rate multi-user indoor visible light communication (VLC). The SCM tones, which are unmodulated signals, are used to identify each light unit, to find the optimum light unit for each user and to calculate the level of the co-channel interference (CCI). WDM is utilised to attain a high data rate for each user. In this study, multi-colour (four colours) laser diodes are utilised as sources of lighting and data communication. One of the WDM colours is used to convey the SCM tones at the beginning of the connection to set up the connection among receivers and light units (to find the optimum light unit for each user). To evaluate the performance of the VLC system, two types of receivers are proposed: an array of non-imaging receivers and an array of non-imaging angle diversity receivers. In this study, the effects of diffuse reflections, CCI and mobility on the system performance are considered.

In this study, the authors deal with the problem of simultaneous measurement of temperature, pressure, and strain using novel technologies of optical fibre (OF) sensors. Indeed, they address the problem of early surveillance systems to detect disasters in real-time. Through these sensors, they try to predict prospective and possible disasters (landslides, fire, earthquake etc.). Temperature, pressure, and strain should be simultaneously monitored to prevent betimes any damages. They propose a novel design of disaster system, which is able to measure the variation of temperature, pressure, and strain using optical sensors based on Brillouin scattering, two types of these sensors are discussed Brillouin optical time division reflectometers and Brillouin optical time division analysis (BOTDA). Thus, they indicate the performance of BOTDA sensors on disaster detection systems. However, these sensors cannot measure pressure variation, so they introduce the application of hybrid BOTDA/fibre Bragg grating (FBG) system in order to predict disasters caused by pressure.

The next-generation wireless communication network is expected to provide a significant increase in average throughput, radio resource utilisation as well as reduced call blocking probability for edge-cell user equipments (UEs). Satisfying these goals has remained as a Herculean task to wireless network designers and operators. The cooperative communication has been proposed by researchers as a possible technique to surmount these challenges. This study addresses the problems of enhancing the network performance of cell-edge UEs in wireless communication networks. A Buffered Cooperative Communication (BCC) model that exploits the transmission channel qualities using link adaptation to enhance the average throughput, quality of service and radio resource utilisation is proposed. In the proposed BCC model, the Markov chain analysis is used to investigate the effect of the queue buffer size on the average throughput, data blocking probability and radio resource utilisation. Finally, this work provides a framework to investigate the performance of the BCC scheme compared to the benchmark: non-BCC (NBCC) scheme. The simulation results show the proposed BCC scheme has significant improvements in the performance over the NBCC scheme.

A Wi-Fi scatter communication method based on microcontroller unit (MCU) is proposed, and an ultra-low power micro Wi-Fi scatter communication device μWi-Fi is designed and implemented. First, according to the characteristics of the microcontroller, the software virtual modulation method and the serial communication port direct memory access (DMA) transmission method is proposed to realise Wi-Fi scattering communication. Then the MCU + exclusive OR (XOR) baseband architecture is proposed to further reduce the main frequency of the microcontroller and the system power consumption. The communication test and power consumption measurement results show that μWi-Fi can generate signals conforming to the IEEE802.11b standard, which can be received and forwarded by universal Wi-Fi routers. Its effective communication distance reaches 15 m, its communication peak current reaches 720  μA, and its standby current reaches 390 nA. Compared with traditional internet of things (IOTs) Wi-Fi devices, μWi-Fi can not only reduce the power consumption of Wi-Fi communication by 2–3 orders but also has a simple composition and low cost, which is very helpful for the rapid development of Wi-Fi IoT products.

Parallel relay is an effective way to extend wireless communication distance. Employing multiple-input multiple-output (MIMO) relay can improve communication quality on a large scale, but the communication efficiency is reduced due to channel estimation. In this study, a mutual information-based estimate-and-forward scheme is proposed based on unitary space-time modulation in MIMO system. An equivalent transmission model is also constructed by regarding that the source signal is affected by a multiplicative factor and an additive noise. Based on this equivalent MIMO model, the generalized signal-to-noise ratio and global mutual information of the forwarding schemes are calculated. Error rate and mutual information analysis show that the proposed soft information forwarding can improve the reliability of parallel relaying system and has a better error rate performance than all the existing memory-less forwarding schemes.

For the unmanned aerial vehicle (UAV)-aided vehicular multiple-input multiple-output Ricean fading channel, this study proposes a novel three-dimensional geometry-based stochastic model (GBSM). This model is the first GBSM for UAV-aided vehicular communication channels with the ability to investigate channel characteristics in different vehicular traffic density (VTD) scenarios, which is a combination of a single-cylinder model and an elliptic-cylinder model, and the signal is a sum of the line-of-sight component, single-bounced, and double-bounced rays. In addition, some expressions of channel statistical properties are derived, including space–time correlation function, space-Doppler spectral power density, envelope level crossing rate, and average fade duration. Based on the reference model, corresponding deterministic and stochastic simulation models are developed. Finally, the authors further explore the impact of some unique UAV-related parameters and different VTDs on channel statistics, and get some useful conclusions based on numerical results.

Although green networking and fairness are both vital and rapidly increasing areas of research, providing energy-fairness in multi-domain green networks is a hitherto unexplored issue. In this study, the authors address energy-fair routing in multi-domain green networks by formulating an optimisation problem as an integer linear programme. The authors' problem maximises the energy saving of the domain with minimum energy saving while ensuring that the energy consumption of each domain is below a given threshold. The model they have established in this study also provides a flexible bandwidth assignment mechanism which improves the feasibility performance of their methods. They then propose a polynomial-time heuristic algorithm for this problem. They evaluate the performance of their heuristic algorithm by comparison with the results obtained from their integer linear programming formulation using optimisation software CPLEX. The simulation results demonstrate that the heuristic algorithm yields close results to the values obtained from the CPLEX implementation of their proposed formulation in terms of energy-fairness and outperforms the previous results while at the same time having low computational complexity.

In this study, the authors consider a diffusive molecular communication channel where the information to be transmitted is the time of release of the information molecules. Using the truncated Lévy distribution to model the first passage time of a molecule, the authors develop some general statistics for a random variable described by a truncated Lévy distribution. The authors then consider a multi-particle molecular communication system, where the average arrival time of the information particles can be represented by a truncated Lévy flight, and the number of molecules required for the cross-over from the Lévy regime to the Gaussian regime to occur is calculated. Furthermore, they use these results to analyse single as well as multi-particle molecular communication channels in terms of capacity bounds and symbol error probability.

The increasing demand for cellular network capacity can be mitigated through the installation of nomadic eNodeB, which serve a temporal increase of traffic volume in specific area. When nomadic cells are deployed, the transmission power of neighbour base stations needs to be optimised to limit the inter-cell interferences. The authors analyse the problem of neighbourhood selection for the optimisation, to define what part of the networks needs to be reconfigured when new base station is added. They evaluate the iterative approach, with increasing range of neighbouring cells being reconfigured and propose a novel, sampling-based local TX power reconfiguration method, which is evaluated by a numerical model in both regular (honeycomb) topology and in realistic topology reflecting locations of cells in a city. The analysis confirms that the proposed algorithm allows to select small subset of neighbouring cells to be reconfigured (in majority of the cases cells), and achieve similar efficacy as global optimisation, with total network throughput different by comparing to the global optimisation.

This study proposes adaptive downlink association schemes for controlled device-to-device (D2D) communication in cellular networks. The proposed schemes utilise active devices under specific conditions to improve the network performance. Specifically, active devices are classified into two disjoint groups according to their individual quality of service (QoS) requirements from their base station (BS). The BS adaptively allocates downlink physical channels to meet individual QoS of devices using a minimal number of these available channels. The unused channels at each served device (in the first class) can be then utilised by that device to serve other devices from the second class, which are not served by the BS, via controlled D2D associations. Herein, D2D pair discovery as well as the conditions for establishing successful D2D association between the classified devices are treated. Furthermore, two D2D association schemes that vary in terms of their performance and implementation complexity to meet certain objectives at the device of interest are presented. The developed analytical results address the scenarios of idealised perfect and practical imperfect D2D association. Numerical results are provided to further explain the performance variations between the proposed association schemes under perfect and imperfect operation scenarios.

In this study, the authors study the achievable rate of the full-duplex massive multiple-input multiple-output (MIMO) relaying system with low-resolution analogue-to-digital converters (ADCs) over Rician fading channels, where maximum ratio combining/maximum ratio transmission are adopted. They first investigate the approximate rate with perfect channel state information by considering the effect of the quantisation error, the loop interference (LI) and the Rician K-factor. Then, they analyse the relationship between the achievable rate and several important variables in the Rician fading channel. It is shown that a large number of antenna arrays at the relay can compensate for the rate loss caused by quantisation at the relay end, and the quantisation bits at the destination have a greater influence on the rate than the quantisation bits at the relay end. In particular, as the number of antennas increases, the rate determined by the quantisation bits at the destination tends to a finite value. They also conclude that the Rician K-factor is proportional to the rate and the attenuation of the rate is very obvious when the LI is large. Finally, the simulation results are presented to verify their analysis.

Spherical phased-array antenna has hemispherical scan coverage for transmission of satellite imagery data at high bit rates to the ground station. Different conditions have been assigned based on their effects on the overall performance of the communication link. Reliability analysis consequently becomes an important requirement of any system onboard a satellite. Although the phased array and some connected algorithms have been presented in the literatures; however, there is no extensive systematic and theoretical performance evaluation framework formulated. In this work, the authors present new method that efficiently and effectively analyses the statistical performance of phased-array antenna systems using spherical harmonics expansion approach. Specifically, the errors caused by limited antenna element number, measurement noise of antenna, imprecision in phased-array antenna elements positioning, and spatial aliasing are systematically and theoretically benchmarked via simulations. Spatial sampling mechanisms for the positioning of array antenna elements on a sphere are presented and evaluated. This study proposed design guide and analysis for spherical phased-array antenna systems, and antenna arrays that do not employ spherical harmonics explicitly.

To address the energy-efficient (EE) routing problem in software-defined wireless sensor networks (SDWSNs), in this study, a centralised routing algorithm, namely, the interference-aware EE routing algorithm (IA-EERA), is proposed to extend the network lifetime (NL) in SDWSNs. Both the link quality of service requirements and the balance between the link energy loads are considered in the proposed IA-EERA when selecting the EE relays. Concretely, the IA-EERA comprises the EE relay selection (RS) and the centralised relay scheduling schemes, which are responsible for generating a valid link set with RS priorities and scheduling the eligible relay nodes with expected link rates from the valid link set, respectively. For supporting the network compatibility and scalability, we propose a hierarchical SDWSN based network architecture, upon which the IA-EERA can be devoted to solving the EE routing problem in the relay layer of SDWSN. Simulation results show that for one data source without interference, the proposed IA-EERA can significantly improve the NL compared with the traditional routing algorithm utilising the energy efficiency maximisation. For multiple data sources incurring interference at nodes, the IA-EERA is able to reduce the NL-dropping rate by adjusting the interference-aware parameter that affects the RS priorities

Dynamic resource control and routing are important for realising the intelligent control of data transmission in wireless multi-hop networks. It is well known that back-pressure routing based on a max-weight policy maximises network throughput and optimises resource allocation in multi-hop wireless networks with time-varying channels. Due to the slow routing convergence and complex control of data queues, however, back-pressure routing also results in large end-to-end delays and a waste of network resources, particularly when the network loads are light or moderate. In this study, a differential back-pressure routing scheme with single-queue management is proposed to improve the packet delay performance and simplify the management of data queues. Unlike in traditional back-pressure routing, the authors use the differences in the rates of change in data queue length to calculate data pressure. Compared with the method of data backlog calculation based on queue length differences, this method achieves faster routing convergence. They also consider the ceiling problem for a single queue and enhance the effect of the queue cap on the routing metric by means of dynamic weighting. Simulation results show that the proposed routing algorithm achieves a 20% decrease in end-to-end delay in grid and random networks.