Showing papers in "Iet Communications in 2017"
TL;DR: The authors first generate a random compressive sensing kernel to compress the received signals of coprime array to lower-dimensional measurements, which can be viewed as a sketch of the original received signals to perform high-resolution direction-of-arrival (DOA) estimation.
Abstract: A coprime array has a larger array aperture as well as increased degrees-of-freedom (DOFs), compared with a uniform linear array with the same number of physical sensors. Therefore, in a practical wireless communication system, it is capable to provide desirable performance with a low-computational complexity. In this study, the authors focus on the problem of efficient direction-of-arrival (DOA) estimation, where a coprime array is incorporated with the idea of compressive sensing. Specifically, the authors first generate a random compressive sensing kernel to compress the received signals of coprime array to lower-dimensional measurements, which can be viewed as a sketch of the original received signals. The compressed measurements are subsequently utilised to perform high-resolution DOA estimation, where the large array aperture of the coprime array is maintained. Moreover, the authors also utilise the derived equivalent virtual array signal of the compressed measurements for DOA estimation, where the superiority of coprime array in achieving a higher number of DOFs can be retained. Theoretical analyses and simulation results verify the effectiveness of the proposed methods in terms of computational complexity, resolution, and the number of DOFs.
169 citations
TL;DR: The authors introduce a novel fast adaptive beam steering IR system (FABS-IR) to improve the uplink performance at high data rates while providing security for applications to enhance the received optical power signal, speed up the adaptation process and mitigate the channel delay spread when the system operates at a high transmission rate.
Abstract: The need for high-speed local area networks to meet the recent developments in multimedia and video transmission applications has recently focused interest on visible light communication (VLC) systems. Although VLC systems provide lighting and communications simultaneously from light emitting diodes, LEDs, the uplink channel design in such a system is a challenging task. In this paper, we propose a solution in which the uplink challenge in indoor VLC is resolved by the use of an Infrared (IR) link. We introduce a novel fast adaptive beam steering IR system (FABS-IR) to improve the uplink performance at high data rates while providing security for applications. The goal of our proposed system is to enhance the received optical power signal, speed up the adaptation process and mitigate the channel delay spread when the system operates at a high transmission rate. The channel delay spread is minimised from 0.22 ns given by hybrid diffuse IR link to almost 0.07 ns. At 2.5 Gb/s, our results show that the imaging FABS-IR system accomplished about 11.7 dB signal to noise ratio (SNR) in the presence of multipath dispersion, receiver noise and transmitter mobility.
102 citations
TL;DR: The derived asymptotic expressions show that the proposed NOMA scheme can improve over the traditional OMA not only the sum rate but also the user fairness.
Abstract: Non-orthogonal multiple access (NOMA) in amplify-and-forward relay systems with partial relay selection (PRS) is investigated. More specifically, new exact closed-form expressions for the outage probabilities at two users are derived, based on which an asymptotic analysis at high signal-to-noise ratio (SNR) is carried out. Additionally, to investigate the performance gap between the NOMA and orthogonal multiple access (OMA) schemes, a closed-form approximate expression at high SNR for the sum rate is derived. Furthermore, relying on the results, the impact of the PRS on the sum rate and outage probability of the proposed NOMA scheme is examined. In particular, the derived asymptotic expressions show that the proposed scheme can improve over the traditional OMA not only the sum rate but also the user fairness. Finally, simulation results are presented to corroborate the analytical results.
101 citations
TL;DR: Numerical results reveal the critical importance of an optimized bit allocation in order to enable significant energy savings as compared to local mobile execution for stringent latency constraints.
Abstract: Mobile cloud computing relieves the tension between computation-intensive mobile applications and battery-constrained mobile devices by enabling the offloading of computing tasks from mobiles to a remote processors. This study considers a mobile cloud computing scenario in which the `cloudlet' processor that provides offloading opportunities to mobile devices is mounted on unmanned aerial vehicles (UAVs) to enhance coverage. Focusing on a slotted communication system with frequency division multiplexing between mobile and UAV, the joint optimisation of the number of input bits transmitted in the uplink by the mobile to the UAV, the number of input bits processed by the cloudlet at the UAV and the number of output bits returned by the cloudlet to the mobile in the downlink in each slot is carried out by means of dual decomposition under maximum latency constraints with the aim of minimising the mobile energy consumption. Numerical results reveal the critical importance of an optimised bit allocation in order to enable significant energy savings as compared with local mobile execution for stringent latency constraints.
63 citations
TL;DR: A cluster-based fault tolerance technique using genetic algorithm is proposed, which minimises the energy loss and overhead in wireless sensor network during fault detection and recovery.
Abstract: In wireless sensor network (WSN), during fault detection and recovery, average energy loss, and message loss occurs including the link failure. Also, the number of faulty nodes and the traffic overhead is increased with the size of WSN. In order to overcome this issue, in this study, a cluster-based fault tolerance technique using genetic algorithm is proposed. Here the network is clustered according to energy-efficient distance-based clustering algorithm. For each cluster head, a set of backup nodes are selected using genetic algorithm based on the sponsored coverage and residual energy parameters. This helps in detecting the faults occurring in cluster members and cluster heads. Simulation results show that the proposed technique minimises the energy loss and overhead.
51 citations
TL;DR: This study study cooperative jamming and power optimisation in untrusted relay networks to improve physical layer security and tight lower bound of ergodic secrecy capacity and asymptotic secrecy outage probability are derived in closed form.
Abstract: The inherent broadcast characteristics of wireless medium make wireless data transmission difficult to be shielded from unintended recipients. As such, secure communication over wireless channels becomes a critical issue in the design of wireless networks. In this study, the authors study cooperative jamming and power optimisation in untrusted relay networks to improve physical layer security. By exploiting the direct link, a source-based jamming (SBJ) scheme is proposed to hinder the untrusted relay from intercepting the confidential message. Considering the total power budget, a power allocation strategy is also proposed to optimally determine the power of source and untrusted relay as well as the power of information and jamming signals. Furthermore, to evaluate the secrecy performance of the proposed SBJ scheme with the power allocation strategy, tight lower bound of ergodic secrecy capacity and asymptotic secrecy outage probability are derived in closed form. Simulation verifies the advantages of the proposed SBJ scheme and the power allocation strategy.
48 citations
TL;DR: A new data access control model has been proposed in this paper for efficient data accessing, which can minimise many problems, such as high searching time for providing the public key of the data owner, high data accessing time, maintenance of the database, etc.
Abstract: Cloud computing is a very trending technology because of its efficiency, cost effectiveness, pay-per-use, flexibility and scalability. Data security and access control are two significant issues experienced while availing these advantages of cloud computing. Access control can be defined as a procedure by which a user can access data or file or any kind of resources from a server. A new data access control model has been proposed in this paper for efficient data accessing, which can minimise many problems, such as high searching time for providing the public key of the data owner, high data accessing time, maintenance of the database, etc. The proposed scheme is evaluated in terms of both theoretical and experimental results, which show the proficiency of the proposed scheme over the existing schemes in a cloud computing environment.
47 citations
TL;DR: Improved performance of the proposed protection model as compared with two baseline defence mechanisms, namely, the random and equal-protection defence mechanisms with static signal-to-noise ratio (SNR) and variable SNRs, proves to be beneficial for securing communication over CRSN.
Abstract: The authors propose a game-theoretic approach using the Stackelberg game for securing cognitive radio sensor network (CRSN) against the spectrum sensing data falsification attack; this attack aims at corrupting the spectrum decisions communicated from the ambient sensor nodes (ASNs) to the fusion centre by imposing interference power. The proposed game approach is developed for two different attack–defence scenarios. In the first scenario, the attacker selects to attack a group of delivered reports of the ASNs that have a protection degree below a specific threshold. In the second scenario, the attacker applies its maximum attack interference power to the delivered reports of the ASNs that have been reported to be least protected in the previous round. Simulation results indicate the improved performance of the proposed protection model as compared with two baseline defence mechanisms, namely, the random and equal-protection defence mechanisms with static signal-to-noise ratio (SNR) and variable SNRs. Consequently, Stackelberg game features prove to be beneficial for securing communication over CRSN.
43 citations
TL;DR: This study proposes a new CS security model, in which circulant matrix is exploited to improve the generation efficiency of the measurement matrix, and binary resilient functions are utilised to enhance the security.
Abstract: Information security is a vital concern in Internet of Things (IoT). Traditional security method based on public or private key encryption scheme is limited by the trade-off between low cost and high level of security. Among different security solutions, utilising compressed sensing (CS) in combination with the physical-layer security to achieve the security is a remarkable method. However, in the current literatures, little attention has been given to the area of static environment, which will lead the risk of information leakage in the CS security model. In this study, the authors propose a new CS security model, in which circulant matrix is exploited to improve the generation efficiency of the measurement matrix, and binary resilient functions are utilised to enhance the security. Furthermore, considering the practical application, they present a feasible framework, named CS security scheme based on frequency-selective, where the frequency-selective feature of the wireless channel is applied to support the static environment. To verify the effectiveness of the proposed scheme, they conducted experiments and numerical simulations to evaluate the performance, and the results are satisfactory.
42 citations
TL;DR: A reinforcement learning technique, called as Q -learning (QL), is used to solve the relay selection problem and a `QL-based relay selection algorithm' (QL-RSA) is proposed for wireless cooperative networks that maximises the total capacity of the network.
Abstract: Relay selection in cooperative communication is a crucial task for achieving the spatial diversity since the improper relay selection can decrease the overall capacity of the network. In this study, the authors use a reinforcement learning technique, called as Q
-learning (QL), to solve the relay selection problem. They propose a `QL-based relay selection algorithm' (QL-RSA) for wireless cooperative networks that maximises the total capacity of the network. QL-RSA receives the reward (feedback) in terms of the capacity by learning a multi-node amplify-and-forward cooperative environment with time-varying Rayleigh fading channels. The advantages of QL-RSA are that it is less complex, requires less channel feedback information and it is distributed in a multiple-sources environment as it provides each source a self-learning capability to find the optimal relay without exchanging information with other source nodes.
42 citations
TL;DR: This study considers the problem of pilot contamination and analytical expressions are presented on the normalised mean square error (NMSE) of the minimum meansquare error channel estimation algorithm to design the optimal pilot sequences for mitigating the pilot contamination.
Abstract: The performance of multicell massive multiple-input multiple-output (MIMO) systems is heavily affected by pilot contamination. This study considers the problem of pilot contamination and analytical expressions are presented on the normalised mean square error (NMSE) of the minimum mean square error channel estimation algorithm. Based on the NMSE of the massive MIMO systems, a pilot design criterion is proposed to design the optimal pilot sequences for mitigating the pilot contamination. Following this criterion, Chu sequence with perfect auto-correction and cross-correlation properties are employed to design the optimal pilot sequences. Then the performance of the proposed pilot design-based scheme is investigated, and the exact NMSE expressions are presented. The excellent performance of this pilot design scheme has been confirmed in the authors' simulations.
TL;DR: Numerical and simulation results verify that there exist optimal UAV altitudes for different scenarios as shown in the authors' analyses, and verify that the number of UAVs must be larger than a certain value to guarantee a target connectivity threshold among vehicles.
Abstract: After disasters, road side units, which can provide wireless communications to vehicles, may fail due to physical damages or power outages Vehicle-to-vehicle communication also may not perform well owing to lack of neighbours in low vehicle density scenario or collisions in high vehicle density circumstance which may happen in disaster areas In this study, the deployment of unmanned aerial vehicles (UAVs) as flying base stations to improve connectivity among vehicles in disaster affected areas is analysed First, the connectivity among vehicles as a function of the altitude of the UAV is derived Furthermore, multiple UAVs scenario is analysed to determine the minimum number of UAVs needed to guarantee a target connectivity threshold among vehicles for a given geographical area and vehicle density Numerical and simulation results verify that there exist optimal UAV altitudes for different scenarios as shown in the authors' analyses, and the simulation results also verify that the number of UAVs must be larger than a certain value to guarantee a target connectivity threshold among vehicles
TL;DR: A new scheme for video distribution over cellular networks is proposed by exploiting full-duplex (FD) radios for D2D devices in two scenarios: (i) two nodes exchange their desired video files simultaneously and (ii) each node can concurrently transmit to and receive from two different nodes.
Abstract: Spectrum scarcity and dramatically increasing demand for high data rate and high-quality video live streaming are of future cellular network design challenges. As a solution to this problem, cache-enabled cellular network architecture has been recently proposed. Device-to-device (D2D) communications can be exploited for distributed video content delivery, and devices can be used for caching of the video files. This can increase the capacity and reduce the end-to-end delay in cellular networks. In this study, the authors propose a new scheme for video distribution over cellular networks by exploiting full-duplex (FD) radios for D2D devices in two scenarios: (i) two nodes exchange their desired video files simultaneously and (ii) each node can concurrently transmit to and receive from two different nodes. In the latter case, an intermediate transceiver can serve one or multiple users’ file request(s) whilst capturing its desired file from another device in the vicinity. Mathematical expressions along with extensive simulations are used to compare their proposed scheme with a half-duplex scheme to show the achievable gains in terms of sum throughput, active links, and delay. They will also look into the energy cost for achieving the improvements provided by operation in FD mode.
TL;DR: This study presents a survey on several channel quality estimation metrics such as bit error rate, signal-to-interference-plus-noise ratio, outage probability, channelquality estimation index, spectrum sensing accuracy of secondary user, and the idle state duration expectation.
Abstract: The rapid growth of wireless communication systems around the world has led to a significant demand for more radio spectrum resources Radio spectrum regulators are facing several challenges due to spectrum scarcity caused not only by increased demand but also by inefficient management of this resource Currently, the spectrum is statically allocated to licensed users even though some of them use this resource intermittently This has resulted in underutilisation of the spectrum and therefore, spectrum scarcity for new users Cognitive radio aims at solving this problem through dynamic spectrum access, which uses spectrum holes opportunistically A cognitive radio can select the best channel available at a particular location and time To accomplish that goal, the system requires some criteria, or channel quality estimation metrics, to rank the channels that it potentially could use In this study, the authors present a survey on several channel quality estimation metrics such as bit error rate, signal-to-interference-plus-noise ratio, outage probability, channel quality estimation index, spectrum sensing accuracy of secondary user, and the idle state duration expectation
TL;DR: It is demonstrated by the analysis and simulation that the performance of the AF-based hybrid satellite-terrestrial communication systems can be significantly improved by deploying more relay ES at the ground in between satellite and destination ES.
Abstract: The problem of relay selection in amplify-and-forward (AF)-based hybrid satellite-terrestrial cooperative communication systems is considered. A partial relay selection scheme is studied in which satellite selects a relay earth station (ES) among multiple relay ESs (situated on ground) on the basis of maximum instantaneous signal-to-noise ratio (SNR). Satellite-relay ESs are assumed to follow Shadowed-Rician fading, whereas relay ESs-destination ES links (terrestrial links) are assumed to follow Nakagami-
m
distribution. First, the cumulative distribution function and probability density function (PDF) of the maximum instantaneous SNR of satellite-relay ESs links are derived; then by using this PDF, the expression of moment generating function (MGF) of the received instantaneous SNR at destination ES is obtained. The average error performance of the considered system with the proposed relay ES selection is derived in terms of Meijer-
G
functions by using MGF approach. In order to get the diversity order of the relay ES selection-based AF scheme, the asymptotic PDF of the considered scheme is derived, and then by using this asymptotic PDF, the analytical diversity order of the system is obtained. It is demonstrated by the analysis and simulation that the performance of the AF-based hybrid satellite-terrestrial communication systems can be significantly improved by deploying more relay ES at the ground in between satellite and destination ES.
TL;DR: A weighted k-nearest neighbour model for user positioning in a visible light communications (VLC) system that outperforms the trilateration method by 36 and 50% accuracy with and without ambient light interference, respectively.
Abstract: This study introduces a weighted k-nearest neighbour model for user positioning in a visible light communications (VLC) system. The new model offers a higher degree of accuracy compared with conventionally existing techniques in VLC, such as trilateration. In the proposed model, the current position of the receiver is estimated based on the positions of the k-NN (known as reference points) pre-defined and recorded in a lookup table. The Euclidean distances from the actual receiver to the reference points are weighted in order to improve accuracy. Simulation results show that the proposed model outperforms the trilateration method by 36 and 50% accuracy with and without ambient light interference, respectively.
TL;DR: The approaches, NLOS identification support vector machine (NISVM) and related channel information regression model (RCIRM), based on machine learning are proposed to identify NLOS and mitigate NLOS error, respectively.
Abstract: Indoor localisation could benefit greatly from non-line-of-sight (NLOS) identification and mitigation, since the major challenge for WiFi indoor ranging-based localisation technologies is multipath and NLOS. NLOS identification and mitigation on commodity WiFi devices, however, are challenges due to limited bandwidth and coarse multipath resolution with mere MAC layer received signal strength index. In this study, the authors explore and exploit the finer-grained PHY layer channel state information (CSI) to identify and mitigate NLOS. Key to the authors' approach is exploiting several statistical features of CSI, which are proved to be particularly effective. The approaches, NLOS identification support vector machine (NISVM) and related channel information regression model (RCIRM), based on machine learning are proposed to identify NLOS and mitigate NLOS error, respectively. Experiment results in various indoor scenarios with severe interferences demonstrated an overall NLOS identification rate of 94.12% with a false alarm rate of 5.88% and a better mitigation performance.
TL;DR: The performance of decode-and-forward relay-assisted free-space-optical communication systems under atmospheric turbulence induced fading and misalignment errors is investigated and the expression for the moment generating function (MGF) of the instantaneous signal-to-noise ratio is derived.
Abstract: In this paper, the performance of decode-and-forward relay-assisted free-space-optical (FSO) communication systems under atmospheric turbulence induced fading and misalignment errors is investigated. To mitigate the adverse effects of the atmospheric turbulence, the aperture averaging receivers are considered both at the relay and destination sides. The atmospheric turbulence induced fading is modeled via the exponentiated-Weibull distribution, which has recently been proposed to characterize an FSO
link in the presence of finite-sized receiver aperture. The expression for the moment generating function (MGF) of the instantaneous signal-to-noise ratio is derived. Further, new closed form expression for the outage probability is obtained. Moreover, the new expression for the average symbol error rate of the subcarrier intensity modulated M-ary phase shift keying is obtained using the MGF-based approach. Finally, numerical examples are discussed and all the derived analytical results are corroborated by Monte-Carlo simulations.
Relayed FSO Communication with Aperture Averaging Receivers and Misalignment Errors. Available from: https://www.researchgate.net/publication/307931308_Relayed_FSO_Communication_with_Aperture_Averaging_Receivers_and_Misalignment_Errors [accessed Nov 10, 2016].
TL;DR: A reliability analysis of cloud services is conducted by applying a Markov-based method and a genetic algorithm-based chaotic ant swarm (GA-CAS) algorithm is proposed, in which four operators and natural selection are applied, to solve this constrained multi-objective optimisation problem.
Abstract: Cloud computing enables service sharing in a massive scale via network access to a pool of configurable computing resources. It has to allocate resources adaptively for tasks and applications to be executed effectively and reliably in a large scale, highly heterogeneous environment. Resource allocation in cloud computing is an NP-hard problem. In this study, the authors conduct a reliability analysis of cloud services by applying a Markov-based method. They formulate the cloud scheduling problem as a multi-objective optimisation problem with constraints in terms of reliability, makespan, and flowtime. Furthermore, they propose a genetic algorithm-based chaotic ant swarm (GA-CAS) algorithm, in which four operators and natural selection are applied, to solve this constrained multi-objective optimisation problem. Simulation results have demonstrated that GA-CAS generally speeds up convergence and outperforms other meta-heuristic approaches.
TL;DR: This study takes an integration of PLC and VLC into consideration, three implementation schemes which differ in frequency domain, time domain, and bit division multiplexing (BDM) are proposed and suggest that the proposed schemes have the ability to support multi-service transmission with no big modification of current power line network.
Abstract: As the shortage of spectrum is becoming a serious problem to the wireless communication, visible light communication (VLC) is attracting widespread attention. However, the access to the backbone network is likely to completely modify the communication network, thus leading to a great cost. Fortunately, the technology of power line communication (PLC) is a perfect match to VLC, which provides power supply and connection for VLC to the backbone network. In this study, the authors take an integration of PLC and VLC into consideration and mainly focus on a communication framework with multi-service. In the case of not making a big modification to the origin network, a direct re-transmission concept is considered and three implementation schemes which differ in frequency domain, time domain, and bit division multiplexing (BDM) are proposed. The demonstration platform and the simulation results suggest that the proposed schemes have the ability to support multi-service transmission with no big modification of current power line network. Moreover, the BDM scheme can accommodate different requirements of quality of service with better performance than conventional multi-service schemes.
TL;DR: In this article, the authors used the statistical characteristics of the users to address one of the important kinds of attacks called primary user emulation attack (PUEA), and the proposed scheme has higher performance in detecting the primary transmission comparing with the previous works.
Abstract: Cognitive radio (CR) is proposed to solve the spectrum scarcity problem. One of the significant issues which arises recently in CR networks is security threats. Most of the proposed methods to defend against the attacks need the previous knowledge about the system. In this study, the authors use the statistical characteristics of the users to address one of the important kinds of attacks called primary user emulation attack (PUEA). In the proposed scheme, the received power statistics of the CR users is used to detect the PUEA. The results show that their scheme has higher performance in detecting the primary transmission comparing with the previous works.
TL;DR: A throughput efficient subcarrier allocation (TESA) and geometric water-filling based optimal power allocation (GWFOPA) method for multi-class cellular D2D systems is proposed and the objective of TESA and GWFOPA method is to maximise the data rate of each class while maintaining interference constraint and fairness among the D1D users.
Abstract: This study examines subcarrier and optimal power allocation in orthogonal frequency division multiple access based 5G device-to-device (D2D) networks. To improve spectrum efficiency, D2D users share same subcarriers with the legacy users using underlay approach. In this approach, it is challenging to design an efficient subcarrier and power allocation method for D2D networks which guarantees the quality of service requirements of legacy users. Therefore, the key constraint is to check the interference condition among D2D and legacy users while allocating the same resources to D2D users. In this study, the authors propose a throughput efficient subcarrier allocation (TESA) and geometric water-filling based optimal power allocation (GWFOPA) method for multi-class cellular D2D systems. First, the TESA method selects subcarriers and allocates power equally for D2D users according to their service classes while maintaining interference and data rate constraints. Then, the GWFOPA method is applied to optimise power in a computationally effective way. The objective of TESA and GWFOPA method is to maximise the data rate of each class while maintaining interference constraint and fairness among the D2D users. Finally, the authors present simulation results to evaluate performance of TESA and GWFOPA in terms of throughput, user data rate, and fairness.
TL;DR: Simulation results showed that the use of TARCO leads to high network performance in terms of the packet delivery ratio, end-to-end delay and communication overhead.
Abstract: A traffic-aware routing protocol (TARCO) that considers integrated real-time traffic conditions for constructing delivery paths over a vehicular environment is presented. This goal was achieved through three mechanisms: cooperative traffic information collection, lightweight real-time road scoring and adaptable data route construction. An accurate overall view of the real-time traffic conditions was obtained from the cooperation between information aggregators at junctions and information collectors on road segments. Each road segment was then assigned a weight according to the overall view of the traffic conditions and updated periodically to reflect traffic variations. Finally, the road segments providing efficient and reliable data routes were used to construct a routing path with guaranteed connectivity and a short delivery delay to the destination. Simulation results showed that the use of TARCO leads to high network performance in terms of the packet delivery ratio, end-to-end delay and communication overhead.
TL;DR: This study develops an analytical framework for a D2D-enabled downlink cellular network with Nakagami- m fading between the D 2D communication links, and extends the coverage probability analysis to include interference-limited dedicated and shared networks.
Abstract: Device-to-device (D2D) communication, unlike conventional cellular communication, is described as the direct communication between devices bypassing the network infrastructure. This mode of direct communication, due to its advantages, is being proposed as an integral part of the next generation cellular networks with the additional interference between the users being a challenge. In this study, the authors develop an analytical framework for a D2D-enabled downlink cellular network with Nakagami-
m
fading between the D2D communication links. The authors derive tractable expressions for the coverage probability of D2D links and cellular users, considering different propagation conditions experienced by D2D and cellular links. Using stochastic geometry, the authors provide the coverage probability analysis for the dedicated network, having orthogonal frequency resource allocation, and for the shared network, where the frequency resources are reused. Furthermore, the authors extend the coverage probability analysis to include interference-limited dedicated and shared networks. Numerical results corroborate their analysis. The authors also derive the expressions for ergodic spectral efficiency of D2D links for both dedicated and shared networks. The results obtained are helpful in understanding the system behaviour and show the dependence of network performance on the system parameters.
TL;DR: The authors first combine NOMA with EH (NOMA-EH) to enhance system spectral efficiency and user fairness and show the correctness of the numerical analysis and confirm the superiority of the proposed NOMa-EH scheme.
Abstract: Non-orthogonal multiple access (NOMA), which uses the power domain for multiple users, has been considered as an emerging candidate for fifth generation downlink transmission. Energy harvesting (EH), a promising technology to prolong the lifetime of energy-constrained wireless networks, has attracted significant attention. In this study, the authors first combine NOMA with EH (NOMA-EH) to enhance system spectral efficiency and user fairness. An NOMA-based relaying network is analysed, where the relay node is equipped with EH device, and functions as the bridge between the base station and the multiple users. The outage performance of the NOMA-EH scheme-based relaying network is studied, where the transmitting antenna selection is applied at the base station and maximal ratio combining is applied at the multiple users. Furthermore, closed-form expression for the system outage probability is also derived. On the basis of the computer simulations, they show the correctness of the numerical analysis and confirm the superiority of the proposed NOMA-EH scheme.
TL;DR: A new algorithm called, EACO to route discovery problem in wireless sensor network after finding the cluster heads (CHs) using fractional artificial bee colony (FABC) algorithm, which found the optimal routes among CHs to transmit a data from any source node to base station.
Abstract: Owing to the extensive growth of wireless technology for sending and collecting a variety of information for the different applications, routing is a major challenge to find the optimal path for the data transmission In this study, the authors have developed a new algorithm called, exponential ant colony optimisation (EACO) to route discovery problem in wireless sensor network after finding the cluster heads (CHs) using fractional artificial bee colony (FABC) algorithm In the first step, CHs are found out using the FABC algorithm with fitness function considering the distance, energy and delay In the second phase, ACO algorithm is modified with exponential smoothing model for multi-path route discovery This new algorithm called, EACO found the optimal routes among CHs to transmit a data from any source node to base station with multiple objectives including energy, distance, intra-cluster delay and intercluster delay These objectives are effectively formulated as new fitness function to find the optimal route path From the experimentation, the outcome showed that the cumulative energy kept after 2000 round of experiments is 02039 for the proposed algorithm but the existing approach (threshold + ACO) kept only 00338
TL;DR: An enhanced discovery mechanism is proposed by employing a backoff strategy for BLE devices to reduce collisions during advertisement process and has shown its effectiveness in terms of discovery latency and energy consumption in crowded BLE networks.
Abstract: Bluetooth low energy (BLE) has received much attention from researchers as one of the prominent solutions for short-range communication The applications of BLE are growing rapidly and there are many issues to be resolved for establishing the deployment of it Practically, BLE devices may experience a lot of collisions during discovery process due to contention among devices, particularly in a crowded environment With an increasing number of BLE devices, discovery latency and energy consumption rise exponentially, which could degrade the quality of service required by user applications In this study, the authors propose an enhanced discovery mechanism by employing a backoff strategy for BLE devices to reduce collisions during advertisement process Through experimental and mathematical analysis, the proposed mechanism has shown its effectiveness in terms of discovery latency and energy consumption in crowded BLE networks
TL;DR: The authors propose to jointly select an analogue precoder and combiner pair for each data stream successively, which can maximise the channel gain as well as suppress the interference between different data streams.
Abstract: Millimeter wave (mmWave) communications have been considered as a key technology for future 5G wireless networks since it can provide orders-of-magnitude wider bandwidth than current cellular bands. To overcome the severe propagation loss of the mmWave channel, an economic and energy-efficient analogue/digital hybrid precoding and combining transceiver architecture is widely used in mmWave massive multiple-input multiple-output (MIMO) systems. The digital precoding/combining layer offers more freedom than pure analogue one and enables multi-stream transmission. In this study, the authors consider the problem of codebook-based joint hybrid precoder and combiner design for multi-stream transmission in mmWave MIMO systems. The authors propose to jointly select an analogue precoder and combiner pair for each data stream successively, which can maximise the channel gain as well as suppress the interference between different data streams. Then, the digital precoder and combiner are computed based on the obtained effective baseband channel to further mitigate the interference and maximise the sum-rate. Both fully-connected and partially-connected hybrid beamforming structures are investigated. Simulation results demonstrate that the proposed algorithms exhibit prominent advantages in combating interference between different data streams and offer satisfactory performance improvements compared with the existing codebook-based hybrid beamforming schemes.
TL;DR: This study proves that an exact potential game applies to the resource allocation problem and there exists the best Nash equilibrium (NE) which is the optimal solution of the optimisation problem.
Abstract: In this study, the authors address the downlink resource (subchannels and power) allocation problem for device-to-device communication with wireless power transfer technique in a cellular network to improve the energy efficiency (EE). The considered problem is formulated as maximising the weighted EE and is solved by leveraging a game-theoretic learning approach. Specifically, they first prove that an exact potential game applies to the resource allocation problem and there exists the best Nash equilibrium (NE) which is the optimal solution of the optimisation problem. Then, aiming to this optimisation problem with imperfect information, a robust and distributed learning algorithm is proposed and is proved that it can converge to the best NE. Finally, numerical results verify the effectiveness of the proposed scheme.
TL;DR: This study considers in-network caching combining with network slicing, and proposes an efficient caching resource allocation scheme based on chemical reaction optimisation (CRO) algorithm, which can significantly improve the caching resource utilisation.
Abstract: Network slicing has been considered as one of the key technologies in the next generation mobile network (fifth generation – 5G), which can create virtual network and provide customised services on demand. Most of the current work on network slicing mainly focuses on virtualisation technology, especially in virtual resource allocation. However, caching as a significant approach to improve the content delivery and quality of experience for end-users has not been well considered in network slicing. In this study, the authors consider in-network caching combining with network slicing, and propose an efficient caching resource allocation scheme for network slicing in 5G core network. They first formulate the caching resource allocation issue as an integer linear programming model, and then propose a caching resource allocation scheme based on chemical reaction optimisation (CRO) algorithm, which can significantly improve the caching resource utilisation. The CRO algorithm is a population-based optimisation metaheuristic, which has advantages in searching optimal solution and computation complexity. Finally, extensive simulation results are presented to illustrate the performance of the proposed scheme.