Abstracts:Cognitive radio (CR) concept is turning out as a prominent approach used in the wireless communication network for increasing spectrum efficiency by opportunistically and mutually sharing the spectrum of contemporary networks. CR can bear high traffic loads during emergencies and major disasters by overcoming the limitations like lack of network capacity. The fundamental issues pertaining the implementation of CR network (CRN) are the presence of co-channel interference and adjacent channel interference among CR users; and most importantly interference to primary users. Effective interference mitigation and management in CRN will make it more robust in easing the additional stress because of very high traffic loads during an intense emergency and disaster scenarios. In this study, an approach has been taken to minimise interference among secondary nodes by employing interference index as interference minimisation key which in turn maximises the system capacity. To validate the results, the authors thoroughly used an existing distributed greedy algorithm, which, on the introduction of interference index, furnished a gain of 60% in the CR network capacity. Further, a trade-off analysis between the interference index and channel leakage ratio is presented with an interference bound of 10 dBm, which may form the basis of interference management in CRN.

Abstracts:A new idea regarding the generation of a block code for a code rate of 1/2 and less than 1/2 is developed here. The minimum distance between the codewords can be maximised using a suitable transformation of the <bold><italic>P</italic></bold> matrix in the generator matrix <bold><italic>G</italic></bold> of the block code. This study gives the construction of distance increasing mapping (DIM) such that the proposed code is a variable distance modified block code with a code rate equal to 1/2. An algorithm for such DIM is developed here. The construction for distance preserving mapping (DPM) is also generalised in an algorithmic way. Further, to achieve DIM from the proposed DPM, for the established codes with a code rate less than 1/2, transformation is developed with the help of permutation arrays. The performance of the codes has also been evaluated. Decoding of this code is also simple and can be carried out using the existing techniques of decoding of block codes. The probability of undetected error is found to be better than the existing block codes.

Abstracts:Massive multi-input&#x2013;multi-output (MIMO) is expected to be an eminent technique to meet the demands of high system capacity and data rates of wireless networks in 5G wireless communication. However due to inherent imperfections of the transmitter such as power-amplifier (PA) non-linearity and crosstalk, practically, the signal quality suffers and does not reap sufficient benefits from the various MIMO techniques. Digital predistortion (DPD) is a popular technique for single-input&#x2013;single-output transmission to enhance signal quality. This study examines the issue of high DPD's complexity in mitigating imperfections in MIMO transmitters. This work proposes a less complex, novel DPD model for linearising large-scale MIMO transmitters along with its characterisation procedure. The proof-of-concept is provided with the measurement setup containing 4<inline-formula><alternatives><tex-math notation="LaTeX">$times $</tex-math><mml:math overflow="scroll"><mml:mo>&#xd7;</mml:mo></mml:math><inline-graphic xlink:href="IET-COM.2019.0809.IM1.gif" /></alternatives></inline-formula>1 MIMO transmitters in the presence of non-linear crosstalk, linear crosstalk, and strong PA non-linearity. The proposed model performs comparably to the state-of-art DPD models like parallel Hammerstein and dual-input crosstalk mismatch with lower number of floating-point operations (flops). The proposed model improves adjacent channel power ratio up to <inline-formula><alternatives><tex-math notation="LaTeX">$-54.13$</tex-math><mml:math overflow="scroll"><mml:mo>&#x2212;</mml:mo><mml:mn>54.13</mml:mn></mml:math><inline-graphic xlink:href="IET-COM.2019.0809.IM2.gif" /></alternatives></inline-formula>&#x2009;dBc and error vector magnitude up to 1.08% for LTE signal of 40&#x2009;MHz bandwidth.

Abstracts:In this paper, the authors consider an underlay multi-hop cognitive radio network with energy harvesting secondary nodes, where there is a cluster of secondary decode-and-forward relays in each hop. The secondary nodes have no separate energy source available with them, but wake up from idle mode to harvest energy from the primary signal with the time-switching protocol, and use it for transmitting/relaying using the peak interference constraint. In each cluster, a relay with maximum transmit power is selected except in the last one. In the last cluster, a relay which has a maximum signal-to-noise ratio (SNR) at the secondary destination is selected. Though the suggested scheme has low implementation complexity and requires very little channel estimation, its performance is close to that of a scheme in which the link with the best SNR is chosen in each hop (which requires a lot of channel estimation). Analytical expressions are derived for the end-to-end outage probability and throughput assuming Rayleigh faded channels. They show that it is important to optimise the time-switching parameter (fraction of time devoted to energy harvesting) and the number of hops. Simulations confirm the accuracy of the derived expressions.

Abstracts:Blind signal modulation recognition is an essential block for designing a cognitive radio. Different algorithms are developed in the literature, but few are given with detailed implementation. This study proposes a software-defined radio based implementation of blind signal modulation recogniser (BSMR) on field-programmable gate array (FPGA), which works without any prior knowledge of the received signal. The algorithm estimates carrier frequency offset, symbol rate, symbol timing offset, and corrects the signal for these offsets to extract constellation points. It uses clustering structure formed by constellation signature in I/Q plane to detect the modulation for different orders of ASK, PSK, and QAM. The proposed algorithm is deployed on FPGA, using LabVIEW, for a reliable and reconfigurable platform. The algorithm is optimised to use minimum hardware resources and facilitate future up-gradation. The system developed by implementing the algorithm on NI-FlexRIO-7975 FPGA module with NI-5791 adapter detects modulation type in real time without any training. Signals for testing are generated using NI-PXIe-5673 (RF transmitter), and BSMR identifies the modulation type in 81.451&#x2009;ms under additive white Gaussian noise channel.

Abstracts:Identifying the location of randomly deployed sensor nodes in wireless sensor networks (WSNs) is a major challenge because sensor nodes have limited energy and computational capacity. This study presents a low complexity, scalable, and energy-efficient localisation scheme capable of localising dense as well as sparse deployment of nodes using a single beacon node (SBN). The nodes act in passive listening mode to receive information transmitted by the SBN to determine their locations. The energy consumption is reduced at the nodes as well as at the SBN. The SBN has an omni-directional antenna and a directional antenna (DA). DA can rotate to transmit beacons in different directions in the <inline-formula><alternatives><tex-math notation="LaTeX">$XY$</tex-math><mml:math overflow="scroll"><mml:mi>X</mml:mi><mml:mi>Y</mml:mi></mml:math><inline-graphic xlink:href="IET-COM.2019.1298.IM1.gif" /></alternatives></inline-formula>-plane. The time required and energy consumption for localisation are reduced at the node side as well as at the SBN side. The expressions for energy consumption and computational complexity are deducted analytically. The proposed scheme is verified with MATLAB simulation. The simulation results show a significant improvement in localisation accuracy and reduction in energy consumption.

Abstracts:To prolong the time duration of smart mobile devices (SMDs) or enable low-latency tasks, mobile edge computing (MEC) has emerged as a promising paradigm by offloading tasks to nearby MEC servers (MECSs). In this study the authors propose an optimisation problem to minimise the weighted sum of the total delay and energy consumption of all SMDs in a multi-MECS-multi-SMD network via multi-dimensional optimisation on offloading strategy making, load balancing, computation resource allocation and transmit power control. Since the problem is NP-hard, the authors decompose it into three subproblems to solve. First, they propose a low complexity heuristic algorithm to obtain the offloading strategies while guaranteeing load balancing between the multiple MECSs. Then they solve computation resource allocation subproblem using Lagrange dual decomposition. Finally, employing fractional programming, the authors transform the transmit power control subproblem into a convex programming problem where the closed-form solution is obtained. The proposed simulation results verify the convergence of the proposed iterative algorithms, and demonstrate that the proposed joint optimisation could achieve good performance in both delay and energy reduction.

Abstracts:In this study, a two-way full-duplex amplify-and-forward relay network is considered in which two multi-antenna fullduplex user nodes manage to exchange their information via a full-duplex multi-antenna relay. The users and relay can concurrently transmit their symbols in all time slots in the same frequency band, which leads to self-interference (SI) at all nodes. The joint beamforming algorithm is used in which the relay and users beamforming matrices are updated in each time slot to suppress the SI. This algorithm needs the channel state information (CSI) of all previous time slots, so the complexity increases as time lapses. To decrease the complexity, an algorithm is proposed in which the beamforming matrix is computed recursively. Moreover, the channel estimation error is considered when the relay and users have partial CSI. Thus, a robust algorithm, i.e. an algorithm that takes the estimation error into account is proposed to decrease the effect of estimation error. The proposed algorithm has been evaluated in terms of mean square error, achievable sum rate and BER for various values of the estimation error variances and compared with the non-robust algorithm. The results show that the superiority of the recursive robust algorithm in terms of SNR and complexity.

Abstracts:The ultra-dense network (UDN) has been identified as a promising solution to accommodate a tremendously increasing number of traffic. Clustering for small cell base stations is considered as an efficient frequency resource management scheme. In this study, the authors propose a flexible clustering algorithm to achieve traffic load balancing between clusters as well as reduced inter-cell interference. They implement a malleable cluster configuration with cluster splitting and recombining. Simulation results demonstrate that the proposed clustering technique is useful and practical, providing high average throughput and lowering outage probability.

Abstracts:The convergence of fibre and wireless technologies realised the fibre-wireless (FiWi) networks. Despite huge capacity offered by fibre, the user experiences a network bottleneck caused by the wireless side. This study investigates wireless local area network (WLAN), the wireless side of the FiWi networks with a gigabits passive optical network (GPON) as the backhaul. The work aims to improve WLAN performance by utilising information gained from GPON. The proposed technique enables all contending stations in multiple access points (APs) WLAN to achieve a desired downlink-to-uplink transmission ratio, k while maintaining maximum throughput. Optimum contention window (CW) sizes for the APs and associate wireless users (WUs) are derived by incorporating the principles of idle sense (IS) and asymmetric AP. However, fairness problem between WUs occurred when they contend the channel with different CW sizes. Hence, this study simplifies the IS scheme to increase fairness between WUs. Furthermore, AP self-adapting and WU adjusting algorithms are proposed to assist the network to achieve the desired <italic>k</italic>, while maintaining the throughput fairness amongst basis service sets. The robustness of the proposed scheme is demonstrated under various conditions: achieved target <italic>k</italic> with nearly perfect fairness and gained near-to-maximum throughput within 96% of the theoretical optimum.