Fingerprint localisation technology based on received signal strength indication (RSSI) is an active area of study in wireless sensor network (WSN) research, mainly because it is cheap and easy to implement. However, due to measurement noise and the multipath effect in RSSI, the accuracy of state-of-the-art fingerprint positioning algorithms is diminished. To solve this problem, the authors propose a multi-channel fingerprint localisation algorithm for WSNs in multipath environments. This algorithm also addresses the issue of existing techniques based on multi-channel signal strength requiring an accurate initial estimate of target–beacon distance or prior knowledge of the target–reference distance. Their proposed algorithm first uses an adaptive Kalman filter to reduce the noise in RSSI measured in different channels, and then calculates the matched fingerprint according to the weight of different channels. Finally, a memetic algorithm is utilised to generate the optimised estimate of fingerprint and location. Extensive experimental results on an actual WSN testbed show that the proposed algorithm improves the accuracy of the existing fingerprint localisation algorithm by at least 50%, regardless of the placement of target node, the number of beacon nodes, and the number of calibration points.

The throughput performance of a random cooperative medium access control (CoopMAC) network in the presence of shadowing and path loss is considered. The nodes are assumed to be distributed as a homogeneous two-dimensional Poisson point process with constant intensity. The helpers are divided into several tiers each having a distinct operating region and a distinct cooperative throughput. Then, the conditions under which a helper in a particular tier can improve the transmission rate between a given pair of nodes are examined. Based on these conditions, an exact analytical expression is derived for the average cooperative throughput of a Poisson CoopMAC network that is subject to path loss and shadowing. The expression is then used to investigate the effects of shadowing, intensity of helpers and distance between source and destination nodes on the average cooperative throughput of the network.

This study analyses the bit-error-rate (BER) performance of filter bank multicarrier (FBMC) systems with offset quadrature amplitude modulation in the presence of phase offset. The authors consider that the FBMC intrinsic-interference has a Gaussian probability distribution, and they derive the BER analytical expressions for multilevel modulation over Rayleigh flat fading channels. Analytical expressions developed in this study are checked and confirmed by computer simulations.

Due to the high mobility of communication, channel times can vary rapidly and system performance can be decreased. In this study, pseudo-random noise is used as the guard interval and the training sequence in the time domain in order to estimate the channel-based compressive sensing scheme. This scheme reduces the number of pilots in the frequency domain and improves spectrum efficiency. By adequately exploiting the sparse characteristics and temporal correlation of the wireless channel, a low complexity compressive channel estimation scheme is proposed. Firstly, the authors average the successive symbols of the channel impulse response in the coherence time to improve the accuracy of the coarse channel estimation. Secondly, a low complexity partial priori information CoSaMP (PPI-CoSaMP) algorithm is proposed to accurately estimate the channel state information. Finally, based on the precise time delay, the accurate gains are estimated based on the least-squares algorithm. The simulation results show that compared with the conventional algorithms, the number of observation points required by the PPI-CoSaMP algorithm is reduced by at least 25%. Moreover, the proposed scheme is more robust at larger multipath channel delays. The complexity of the proposed scheme is reduced by 51.21% compared with the conventional CoSaMP algorithm.

In this study, the authors perform the asymptotic analysis of two-layer D-BLAST transmission scheme with group detection receiver under broad class of fading channels. The asymptotic analysis includes both diversity-multiplexing trade-off (DMT) and throughput-reliability trade-off (TRT) analyses. The D-BLAST considered here is a multi-layered space–time transmission scheme, wherein each diagonal of code-word forms a group. On the other hand, group detection considered detects symbols by nulling out interference from other groups and performs maximum-likelihood decoding on the chosen group. The reason for choosing this scheme is that the first inflexion of DMT of this system ceases at multiplexing gain ≪1, i.e. second inflexion began at multiplexing gain <1 under Gaussian fading scenario. The results of DMT indicate that the system behaves differently in different fading channel constraints when multiplexing gain ≪1. The results of the TRT analysis show that the system performs different in different fading channels in the zeroth operating region.

In this study, the authors propose novel cooperative spatial modulation (SM) systems with two main relaying techniques [amplify-and-forward (AF) and decode-and-forward (DF)], where all nodes have multiple transmit and/or receive antennas. Most of the studies in the literature of cooperative SM systems, which combine the advantages of cooperative communications and SM systems, consider only the space shift keying (SK) scheme with single receive/transmit antenna at relay and destination. Since the error performance of SM highly depends on the number of receive antennas and more flexible cooperative communications systems can be obtained by using SM with multiple antennas, it is essential to investigate multi-antenna cooperative SM systems. They derive analytical expressions of the average bit error probability for both the newly proposed cooperative SM-DF and cooperative SM-AF systems and validate with the computer simulation results. Furthermore, they present the bit error rate comparison of considered systems with classical M-ary phase SK/quadrature amplitude modulation cooperative systems. Computer simulation results indicate that multiple antennas cooperative SM systems provide better error performance than classical cooperative systems for both relaying techniques.

The single-channel blind separation performance of the mixed signals with parameters estimation error in paired carrier multiple access (PCMA) satellite communication systems is analysed in this study. Current literatures have theoretically analysed the blind separation performance using the symbol detection error probability of PCMA signals. However, the parameters of PCMA signals are assumed to be accurate during their derivations, which are not practical in blind separation scenario. In this study, the parameters' estimation error is considered during the derivation of the blind separation performance of PCMA signals. Thus, the derived performance is more general. The simulation separation result is obtained by per-survivor processing method. It is in accordance with the derived performance.

In this study, the authors investigate the physical-layer security in a cognitive radio network where both the secondary user (SU) and the primary user (PU) are facing security threats from the malicious eavesdroppers. To protect the PU, the SU acts as a friendly jammer to interfere with the eavesdroppers by splitting a certain portion of the transmit power for sending the jamming noise. The problem of optimising SU scheduling, power allocation and power splitting ratio to maximise the SU ergodic secrecy rate subject to the PU secrecy outage constraint with imperfect channel state information available at the SU is investigated based on the dual optimisation method. In addition, a greedy algorithm is also proposed for minimising the PU secrecy outage probability. Simulation results indicate that the proposed algorithms are effective in improving the PU secrecy performance in terms of secrecy outage probability as well as providing secure communications for the SU.

This study proposes a near-optimal packet scheduling scheme in the satellite long term evolution (LTE) network which uses multiuser multiple-in multiple-out technique. For the available resources in the satellite LTE network to be fully utilised and in order to meet the set targets of 4G standard, the need for an optimal scheduling scheme that will maximise the throughput without compromising the quality of service and fairness of users is very crucial. The aim of this study is to propose near-optimal scheduling schemes that have been obtained using Karush–Kuhn–Tucker multipliers and compare their performances with other throughput-optimal scheduling schemes. A new metric that can be used to compute the overall performance of the scheduling schemes is also presented. This work has adopted the use of a land mobile dual-polarised GEO satellite system.

In wireless networks, the cooperative diversity is an implicit form of space diversity commonly used when other conventional transmit diversity methods might not be practical. It was largely proved that cooperative transmission, where a source and a relay cooperate to communicate with a unique destination, is power-efficient compared to the point-to-point transmission. However, the model considered when stating this conclusion is counting only the transmission power consumption. In this study, the authors study the effect of taking into account not only the transmission power at each transmission node but also the processing power consumed in each reception node on the overall end-to-end performance. They formulate the optimisation problem aiming to minimise the total power consumption in order to achieve a target performance constraint, where the total power consumption stands for the sum of the transmission power and the processing power consumed in the decoding (neglecting other forms of power consumption). The authors' analysis relies on the characterisation of an information-theoretic bound on the decoding power of any modern code to achieve a specified bit error probability while operating at a certain gap from the capacity. As this bound is built on the sphere-packing analysis, this study focuses on message-passing decoders. Using this theoretical framework, the improvement of well-known cooperative protocols over the original non-cooperative point-to-point system system is reinvestigated in terms of total power consumption. Thanks to this theoretical framework, a new classification of the studied cooperative protocols is given revealing some surprising conclusions. In particular, the selective decode-and-forward protocol is no more constantly preferred to its simpler alternative, i.e. the decode-and-forward protocol.

Two-way relaying tends to become a celebrated technique in communication networks because of its unique characteristic in establishing a two-step bilateral information exchange mechanism between users' pairs, as well as, arranging a virtual spatial diversity scenario. In this paper, two-way relaying under amplify-and-forward strategy, and fast Rayleigh fading environment is considered. We investigate two distinct cases in which the relay retransmits users' superposed signals, either directly or after complex conjugation in two- or three-phase modalities. We derive the optimal detection rule which is inherently computational complex. Two closed-form suboptimal structures are proposed to circumvent this formidable problem. In the first form, we incorporate the destination noise into the relay counterpart, and assume Gaussian conditional distribution for the received signal in the latter. The first detector is designed using less stringent approximation and consequently has a better performance, whereas the second one benefits from a very low computational complexity and simple implementation and is more suitable for applications with strict computational and energy constraints such as sensor networks. Furthermore, we consider the imperfect self-channel information case and extend the corresponding results. Bit error rate analyses and accompanying computer simulations show an improvement of about 5 dB over existing methods.

With the exponential growth of network bandwidth and application requirements, the existing transmission control protocols have led to the issues of efficiency and applicability. In order to solve the network utility issues and accelerate the data delivery legitimately, the swift and self-learned transmission methods have attracted attention gradually due to its adaptability and predictability. In this research, we propose a high-speed transport protocol, called Hita, based on network performance learning framework to cope with high-speed transfer challenge over high bandwidth delay product networks. The key idea of Hita is to select preferable network performance metrics to reflect network property variability and build corresponding window control model. The proposed protocol, which adopts the online-learning methods, establishes the relation model between the transmission performance metrics and the corresponding congestion window. Afterwards, by determining the direction of window adjustment, the optimal sending window size can be predicted and approached quickly. Numerical results show that Hita can use the limited bandwidth more adequately. For simulation experiments, Hita achieves higher throughput while maintaining a lower packet delay comparing with other protocols. Moreover, Hita shows good performance in terms of intra-protocol fairness, friendliness and protocol stability. For real-world network experiments, Hita achieves more throughput than the other high-speed protocols as well.

Very recently, double generalised gamma (GG) distribution has been proposed for describing irradiance fluctuation in free-space optical (FSO) communication systems. As a generic model, double GG contains commonly used turbulence models such as gamma–gamma distribution as its special cases. In this study, first we derive an exact closed-form expression in terms of Meijer's G-function for the average bit error rate (BER) of FSO communication system with differential phase shift keying modulation over double GG turbulence channel. This study shows that in the special case, the derived BER expression coincides with the existing BER results presented in the literature for gamma–gamma turbulence channel. Then, to improve the BER performance of the system, dual-branch transmit laser selection diversity scheme is used and derive exact closed-form expression for the BER in terms of bivariate Fox's H-function. Numerical and simulation results are demonstrated to confirm the accuracy and applicability of the derived analytical expressions.

For real-time transmission of high-bandwidth sensor data from an unmanned aircraft vehicle (UAV) to the ground station (GS) in an unmanned aircraft system, a high-speed payload communication system is essential. While orthogonal frequency-division multiplexing (OFDM) is very effective for terrestrial wideband systems, possible higher speed of UAVs or higher carrier frequencies can increase the Doppler shift, and therefore increase the inter-carrier interference (ICI) in OFDM systems. In these scenarios, the complete frequency-domain channel matrix should be estimated and used for ICI mitigation and data recovery. In this study, a time-domain pilot-based channel estimation scheme is described to estimate the entire frequency-domain channel matrix for moderate-to-high Doppler OFDM systems. Simulation results indicate that the new scheme provides better performance compared with channel estimation schemes designed for low Doppler scenarios that partially estimate the frequency-domain channel matrix. The comparison is also presented with the other full channel estimation scheme, named autoregressive scheme, showing a comparable performance with much lower complexity for the new scheme.

In this study, the secret polar encoding and secret successive cancellation decoding algorithms are introduced; with these algorithms, secure and efficient communication can be enhanced between the honest parties. Also, the key size of the proposed polar code-based secure channel coding system is reduced significantly compared to the existing systems. To decrease the key size, the authors employ the three following methods: (i) a new approach is proposed to save some bit-channel indices instead of saving the generator matrix of the used polar code; (ii) the permutation and scrambling matrices are not used in this scheme; and (iii) by the help of the properties of polar codes, it does not need to save any vector as part of secret key set to generate an error vector. Moreover, the security analyses demonstrate that this system is resistant against conventional attacks on symmetric-key code-based cryptosystems. It means that reducing the key size of the proposed polar code-based scheme does not affect its security level.

This study describes a novel feed-forward segmented digital automatic gain control (FSD-AGC) algorithm for long term evolution (LTE) digital radio-over-fibre (DRoF) systems. It experimentally demonstrates the algorithm using a DRoF platform based on real-time field programmable gate arrays. The FSD-AGC algorithm is able to update power status accurately with a short delay (about 100 samples) and adjust the gain precisely by only one step. It can make full use of analogue-to-digital converter quantisation bits width without oversaturation and maintain a stable peak-to-average ratio to reduce the overall cost and energy consumption of digital links and to minimise the deterioration of error vector magnitude (EVM) in LTE systems. Compared with conventional solutions, the proposed algorithm shows significant improvement in the dynamic range (a 20 dB improvement is demonstrated experimentally) of 4G-LTE radio frequency signals in a DRoF system. This is a major step forward for the future commercialisation of DRoF systems for 4G and 5G network deployments. Meanwhile, FSD-AGC can be applied in both LTE time division duplexing and frequency division duplexing signals. Experimental results have shown a mean EVM of the DRoF system below 4.5%, which is well below the 8% required by 3rd generation partnership project.

An energy-efficient cognitive radio network (CRN) design is one of the primary requirements for the low-battery-driven wireless terminals in the presence of primary user emulation attack. Furthermore, sensing accuracy is also essential for allocating vacant bands to the secondary users (SUs) for data transmission. Hence, this study focuses on designing an energy-efficient double threshold-based CRN. The adversarial effects arising in the presence of the attacker are analysed and are treated as constraints while formulating the energy efficiency (EE) maximisation problem. To develop the formulation, a unique SU selection algorithm to identify most eligible SUs for data transmission is proposed. The EE is then maximised by minimising the total power consumption through novel adaptive resource allocation algorithm. Hence, the authors proposed approaches are based on the suitable selection of SUs and adaptive power allocation under the constraints of maximum throughput, controlled transmission power providing sufficient protection to the primary user, minimum power consumption and minimum false alarm probability. The extensive simulation results demonstrate that the proposed scheme substantially increases EE with lower complexity over the conventional scheme.

WiFi traffic offloading is becoming especially appealing because of the upcoming ultra-dense cellular networks. However, WiFi offloading decision as well as WiFi-Access Points (W-AP) selection should be carefully studied in order not to affect the offloaded users’ experience. Here, a new reinforcement-learning framework is presented. The authors propose a distributed Q-learning algorithm in which each cellular user learns about his local environment and selects the best base station (macro-BS or W-AP) after reaching convergence. They introduce a new reward parameter which takes into account the load of each detected W-AP, the duration of the vertical handover, the offered gain, as well as the achieved signal-to-interference-plus-noise ratio. With the Q-learning scheme, each user decides to join the WiFi offloading or not, depending on the received reward from his environment and from his previous learning. In addition, since the AP's load value is very important in the reward parameter, an optimal value of the weight given to the channel load is solved under quality of service constraint. Simulation results showed the effectiveness of the proposed Q-learning-based scheme when compared with common WiFi offloading scheme in terms of cellular residence time.

Spectrally efficient frequency division multiplexing enables higher spectral efficiency at the cost of suffering from inter-carrier interference (ICI), which leads to either a severe error floor or a heavy computational burden at the receiver. In this study, the authors propose a low-complexity demodulation technique, in which the detected symbols are used as feedback to effectively mitigate ICI. To restrain the error propagation caused by non-ideal feedback, the authors enumerate subsequent unknown symbols as preconditions, and then perform the demodulation based on minimum distance criterion, in order to enable the optimal solution in each step of feedback. As a consequence, the computations necessitated to data demodulation can be significantly reduced as a quadratic order of symbol-size. Furthermore, the authors mathematically characterise the demodulation performance by deriving the signal-to-interference-plus-noise ratio as a function of bandwidth compression factor. It is shown that the demodulation scheme can effectively reduce the error floor raised by ICI while preserving a low complexity. Simulation results demonstrate that the proposed demodulator outperforms the conventional ones, and achieves indistinguishable performance as that of orthogonal frequency-division multiplexing while increasing up to 25% spectrum efficiency.

The Internet of vehicles allows connecting vehicles to the Internet to make all data from vehicles available for applications aimed towards improving safety and comfort for passengers. Density is one of the most important sensed data to gather. This information is mainly obtained through periodic messages broadcast by the neighbouring vehicles. However, the availability of this information depends on the Internet. A low penetration rate of Internet of vehicles, or the loss of Internet connection, can significantly affect the accuracy of the sensed density. Moreover, the reception rate of the periodic messages seriously drops at short distances caused by the broadcast storm problem in high-density scenarios. To address this problem, using inter-vehicular communications, we propose a segment-based approach for enhancing the accuracy of the local density estimation. This approach provides a highly accurate estimation with low overhead over the maximum vehicles transmission range to all the vehicles. The proposed approach is extensively evaluated analytically and by simulation. Performance evaluation results show that our approach SLDE allows about 3% of mean error ratio with low overhead over the maximum transmission range.