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A novel multistatic integrated sensing and communication (ISAC) system based on cellular network is proposed. It can make use of widespread base stations (BSs) to perform cooperative sensing in wide area. This system is important since the deployment of sensing function can be achieved upon the mobile communication network at low complexity and cost without modifying the architecture of BSs for full duplexing. In this work, the topology of sensing cell is first provided, which can be duplicated to seamlessly cover the cellular network. Each sensing cell consists of a single central BS transmitting signals and multiple neighboring BSs receiving reflected signals from sensing objects. Then an estimating approach is described for obtaining position and velocity of sensing objects that locate in the sensing cell. Joint data processing with an efficient optimization method is also provided. In addition, key issues in the cellular network based multistatic ISAC system are analyzed. Simulation results show that the multistatic ISAC system can reduce interference power by over 10 dBm and significantly improve position and velocity estimation accuracy of objects when compared with the monostatic ISAC system, demonstrating the effectiveness and promise of implementing the proposed system in the mobile network. [ABSTRACT FROM AUTHOR]

Abstract The Society of Automotive Engineers (SAE) J2945/1 standard for Dedicated Short Range Communication (DSRC) environmentutilizes transmit (Tx) power control and rate control elements for the periodic BSM transmissions, which are intended to work in a complementary manner. An equivalent standard for the cellular vehicle‐to‐everything (C‐V2X) communication environment is J3161/1, but it eliminates Tx power control and uses only rate control. However, the consequence is the degraded update delay of neighbouring vehicles’ kinematics, potentially undermineing driving safety. In this Letter, the authors propose to retain the dual‐mode control in the C‐V2X environment and find a policy through reinforcement learning (RL) to adjust the rate control function to maintain synergy. Moreover, the authors can extract the RL‐created policy from the neural network so that it can be explicitly specified in the standard, and downloaded and used more conveniently by vehicles. Finally, the RL‐generated policy achieves a better packet delivery frequency than J2945/1 or J3161/1.

The Society of Automotive Engineers (SAE) J2945/1 standard for Dedicated Short Range Communication (DSRC) environmentutilizes transmit (Tx) power control and rate control elements for the periodic BSM transmissions, which are intended to work in a complementary manner. An equivalent standard for the cellular vehicle‐to‐everything (C‐V2X) communication environment is J3161/1, but it eliminates Tx power control and uses only rate control. However, the consequence is the degraded update delay of neighbouring vehicles' kinematics, potentially undermineing driving safety. In this Letter, the authors propose to retain the dual‐mode control in the C‐V2X environment and find a policy through reinforcement learning (RL) to adjust the rate control function to maintain synergy. Moreover, the authors can extract the RL‐created policy from the neural network so that it can be explicitly specified in the standard, and downloaded and used more conveniently by vehicles. Finally, the RL‐generated policy achieves a better packet delivery frequency than J2945/1 or J3161/1. [ABSTRACT FROM AUTHOR]

This article outlines the proposed open-radio access network (O-RAN) deployment for fifth-generation (5G) wireless networks. O-RAN seeks to supplant hardware-specific radio access network (RAN) components with generic hardware, specialized software, and open signaling interfaces. The virtualization and network slicing features of 5G allow for software to replace previously hardware-specific functions. The software further provides faster analytics, thus supporting 5G's latency requirements and advanced usage scenarios (i.e., enhanced mobile broadband, massive machine type communications, and ultra-reliable low latency communications). Furthermore, as software annexes control of the RAN, there is the freedom to integrate artificial intelligence/machine learning algorithms into RAN management (particularly at the user plane). This integration is one of the goals of O-RAN. Finally, relying on generic hardware and specialized, open-source software eliminates reliance upon specific device manufacturers. This article will provide questions regarding O-RAN's future, with a focus on 5G network device security. [ABSTRACT FROM AUTHOR]

Abstract As the world is entering the era of 5G, we are witnessing exponential growth in the volume of data traffic generated and consumed by mobile devices. Mobile data offloading handles the surge in mobile data traffic by offloading part of the traffic onto the Wi‐Fi network. In this context, we design and analyse a quality of service (QoS) enhancement scheme for delayed mobile data offloading. We first consider prioritised queuing of traffic as a scheme for QoS provisioning. Using the concepts of virtual waiting time, renewal process, and level crossing arguments, we derive the average transmission delay of the offloaded and reneged packets of high priority. Next, we mathematically validate the benefit of balking all such packets whose expected virtual waiting time exceeds their deadline. Using a three‐dimensional Markov chain model, we derive the required balking probability. Moreover, we merge the technique of balking with prioritisation for improving QoS in delayed offloading. Through an extensive simulation, we validate our analysis and demonstrate how the proposed scheme reduces the transmission delay without sacrificing offloading efficiency. Our investigation has the potential to be adopted in future mobile data offloading standards for improving QoS.

Abstract The trend towards cities and urbanisation, which increases the number of people living in urban areas, requires local authorities to provide services and natural resources more efficiently and effectively and develop some strategies for a sustainable environment. The more effective use of resources, growing awareness of sustainable environment, climate confidence and motivation to make cities more livable is a new concept called Smart City. In this study, the proposed system supports the garbage collection of the city government and works with low budget, low energy, and free radio frequencies. The Internet of Things (IoT) sensor node is assembled, and the network is set up based on the long range wide area network protocol to connect it to the sample garbage bin and collect data. Instant data collection by this network is carried out through the IoT and is designed based on the collected data. The goal is to build an ideal system for smart garbage collection in cities and support sustainability in cities by integrating with the city government's information systems. The data received from the sensor nodes and the efficiency of the system were demonstrated for local governments. The main outcome of this research is to develop a practical smart city application with minimal resources and support local governments in their daily work. Moreover, how a low power wide area network communication network with a frequency of 868 MHz works in Istanbul (Turkey) will be investigated further and which alternative to cellular networks is the most suitable for excellent communication in smart cities will be studied.

Stochastic geometry is emerging as tractable solution and attractive approach to evaluate the performance of 5G heterogeneous network (5G‐Hetnet) such as coverage, outage and rate probability. The base stations (BSs) and fading distribution in 5G‐Hetnet are an almost ubiquitous assumption for analytical study, requiring flexible and scalable approaches. However, the β‐Ginibre point process (β‐GPP) has been proposed as a new method to model wireless network. This study provides a general framework to analyse downlink mmWave cellular network with Nakagami‐m fading and directional beamforming. First, cell association scheme in both line‐of‐site and non‐line‐of‐site is considered based on the strongest average received power. After deriving cell association probability between user equipment and BS, the computationally coverage probability expression is obtained depending on signal‐to‐interference‐plus‐noise ratio. Furthermore, the impact of biasing factor on rate coverage probability is investigated. Finally, considering inter‐cell‐interference coordination, most performances metrics will be re‐evaluated to determine their influence on the network. Recommended approaches produce satisfactory results when biasing factor and antenna beamforming are used. [ABSTRACT FROM AUTHOR]

Mobile users are interested in utilising high network capabilities without time and place constraints. However, with a high level of interest in the usage of mobile phones and internet facilities, the limited capacity of terrestrial base stations (BSs) is unbalanced. As a potential alternative to BSs, unmanned aerial vehicles (UAVs) are emerging as a means of transmitting wireless data to ground mobile users. As an air‐to‐ground communication network, the real UAVs deployed and collected communication data from ground mobile users. The main objective of this study is to analyse and evaluate user throughput, interference, and power transmission when the UAVs are at different heights. The parameters used include the locations of the UAVs and users, the altitudes and elevation angles from the users to UAVs, signal‐to‐noise‐ratio, throughput values, the categories of line‐of‐sight, and non‐line‐of‐sight links. Furthermore, K‐means used as a clustering method for class identification, long short‐term memory (LSTM), and gated recurrent unit (GRU) to analyse and evaluate system performance. The system's performance was compared with a multi‐layer perceptron approach. The evaluation results show that the proposed LSTM–GRU provides reliable and encouraging performance with low computational complexity, which is appropriate for heterogeneous networks. [ABSTRACT FROM AUTHOR]

A multi‐cell network that uses orthogonal frequency division multiplexing access (OFDMA) is studied here. Unlike prior works, the proposed network consists of both (i) legacy data users that do not have energy harvesting capability and have a minimum data rate requirement and (ii) radio frequency (RF)‐energy harvesting devices with a minimum energy requirement. It studies sub‐band allocation to users and transmits power allocation at base stations. The authors formulate a mixed‐integer non‐linear program and also present two heuristics to assign sub‐band to base stations. Numerical results show that RF energy harvesting devices will not affect network capacity if legacy data users require a high data rate. In addition, the results obtained from the two proposed heuristics are ∼95% of the optimal solution. [ABSTRACT FROM AUTHOR]

In order to solve the problem of network congestion caused by a large number of data requests generated by intelligent vehicles in LTE-V network, a brand-new fog server with fog computing function is deployed on both the cellular base stations and vehicles, and an LTE-V-fog network is constructed to deal with delay-sensitive service requests in the Internet of vehicles. The weighted total cost combines delay and energy consumption is taken as the optimisation goal. First a reinforcement learning algorithm Q-learning based on Markov decision process is proposed to solve the problem for minimising weighted total cost. Furthermore, this study specifically explains the setting method of three elements for reinforcement learning-state, action and reward in the fog computing system. Then for reducing the scale of problems and improving efficiency, the authors set up a pre-classification process before reinforcement learning to control the possible values of actions. However, considering that as the number of vehicles in system increases, Q-learning method based on recorded Q values may fall into a dimensional disaster. Therefore, the authors propose a deep reinforcement learning method, deep Q-learning network (DQN), which combines deep learning and Q-learning. Experimental results show that the proposed method has advantages.

This paper presents a quad-band frequency agile antenna, with independent and concurrent frequency tunability in each band, for a tunable, concurrent, quad-band single chain radio receiver for 5G New Radio (NR). More specifically, the antenna comprises of four planar slots etched in a ground plane and fed through a single microstrip feedline, without any impedance matching network. The structure is optimized to maximize isolation between the individual slots and their respective resonant frequencies. Furthermore, a novel high order harmonic suppression method is demonstrated, which controls the current distribution via creating a fictitious short circuit in the slot antenna-enabling the antenna to achieve a much wider tuning range. Numerical simulations are verified using experimental implementation and measurements, with good agreement observed. The four slots resonate around the 830 MHz, 1.8 GHz, 2.4 GHz and 3.4 GHz frequency bands, which are independently tuned (using a varactor diode in each slot) to achieve tuning ranges of approximately 64%, 66%, 27% and 33%, respectively. More importantly, the contiguous four bands covers a total frequency tuning from 0.6 to 3.6 GHz i.e. a tuning range of approximately 143%. Finally, far-field measurements are performed and the antenna is evaluated in over-the-air testbed (quad-band radio receiver), which measures the Error Vector Magnitude performance for the individual channels. Good performance is observed, confirming acceptable isolation performance between the four bands. The data reported in this paper is available, from ORDA-The University of Sheffield Research Data Catalogue and Repository, at https://doi.org/10.15131/shef.data.11219000.v1.

For the problem that mobile devices that are far away from the base station obtain limited wireless resources, which causes high transmission delays, the study proposes a multi-hop path to assist users who are far away from the base station to use edge computing resources. And it combines cloud radio access network and wireless self-organising network. The modelling aims to minimise the total energy consumption under the constraints of task delay considering the mobility of mobile devices. Meanwhile, it selects the joint optimisation problem of the path for data transmission and the virtual machine for calculation. This study also introduces the krill herd algorithm and analyses its advantages and disadvantages. The author enhances the global search ability of the algorithm by defining perturbation factors in the random diffusion behaviour and introduces a new strategy of elite selection and retention into the iterative process to improve the convergence accuracy. Finally, the improved krill herd algorithm is used to solve the joint optimisation problem and a better allocation result than the separate resource allocation of calculation and communication is obtained. The experiment proves that the selection algorithm combining virtual machine and routing proposed in this study can achieve the expected results.

Stochastic geometry is emerging as tractable solution and attractive approach to evaluate the performance of 5G heterogeneous network (5G‐Hetnet) such as coverage, outage and rate probability. The base stations (BSs) and fading distribution in 5G‐Hetnet are an almost ubiquitous assumption for analytical study, requiring flexible and scalable approaches. However, the β‐Ginibre point process (β‐GPP) has been proposed as a new method to model wireless network. This study provides a general framework to analyse downlink mmWave cellular network with Nakagami‐m fading and directional beamforming. First, cell association scheme in both line‐of‐site and non‐line‐of‐site is considered based on the strongest average received power. After deriving cell association probability between user equipment and BS, the computationally coverage probability expression is obtained depending on signal‐to‐interference‐plus‐noise ratio. Furthermore, the impact of biasing factor on rate coverage probability is investigated. Finally, considering inter‐cell‐interference coordination, most performances metrics will be re‐evaluated to determine their influence on the network. Recommended approaches produce satisfactory results when biasing factor and antenna beamforming are used. [ABSTRACT FROM AUTHOR]

Mobile users are interested in utilising high network capabilities without time and place constraints. However, with a high level of interest in the usage of mobile phones and internet facilities, the limited capacity of terrestrial base stations (BSs) is unbalanced. As a potential alternative to BSs, unmanned aerial vehicles (UAVs) are emerging as a means of transmitting wireless data to ground mobile users. As an air‐to‐ground communication network, the real UAVs deployed and collected communication data from ground mobile users. The main objective of this study is to analyse and evaluate user throughput, interference, and power transmission when the UAVs are at different heights. The parameters used include the locations of the UAVs and users, the altitudes and elevation angles from the users to UAVs, signal‐to‐noise‐ratio, throughput values, the categories of line‐of‐sight, and non‐line‐of‐sight links. Furthermore, K‐means used as a clustering method for class identification, long short‐term memory (LSTM), and gated recurrent unit (GRU) to analyse and evaluate system performance. The system's performance was compared with a multi‐layer perceptron approach. The evaluation results show that the proposed LSTM–GRU provides reliable and encouraging performance with low computational complexity, which is appropriate for heterogeneous networks. [ABSTRACT FROM AUTHOR]

A multi‐cell network that uses orthogonal frequency division multiplexing access (OFDMA) is studied here. Unlike prior works, the proposed network consists of both (i) legacy data users that do not have energy harvesting capability and have a minimum data rate requirement and (ii) radio frequency (RF)‐energy harvesting devices with a minimum energy requirement. It studies sub‐band allocation to users and transmits power allocation at base stations. The authors formulate a mixed‐integer non‐linear program and also present two heuristics to assign sub‐band to base stations. Numerical results show that RF energy harvesting devices will not affect network capacity if legacy data users require a high data rate. In addition, the results obtained from the two proposed heuristics are ∼95% of the optimal solution. [ABSTRACT FROM AUTHOR]

Due to the tremendous propagation loss of millimeter wave (mmWave) communication, device‐to‐device (D2D) communications are widely used over directional mmWave networks to improve network throughput. Most of existing works are mainly focused on concurrent transmission among D2D pairs that have no mutual interference. However, considering the propagation loss and directional interference features, the D2D pairs that interfere with each other can be used to improve network throughput. In this paper, we propose a time resource sharing scheme based on Stackelberg game for D2D pairs to further enhance network throughput. The interference D2D pairs can access to the time resource through paying the price for the interference caused by them. At the same time, the non‐interference D2D pairs can be scheduled. Concurrent transmission scheduling among interference D2D pairs is formulated as a non‐cooperative game, which enables a distributed transmission power control for interference D2D pairs. Moreover, the price strategy can be adjusted by setting interference threshold such that the transmission quality can be guaranteed. Simulation results show that the proposed scheme can achieve significant performance gains compared with classical concurrent transmission in terms of network throughput and energy efficiency. In addition, the convergence and utility of the game are also verified. [ABSTRACT FROM AUTHOR]

Achieving high quality of service (QOS) at the end‐users while maintaining the low interference power at the primary users is the main goal in underlay cognitive radio networks. This goal becomes a more difficult task in the designing of beamforming vectors where all channels state information (CSIs) in the secondary network, as well as the interference CSIs, are uncertain. This task is addressed in this study using an iterative optimization technique. In this technique, the original CSI problem, which is difficult to solve as a single optimization problem, is instead separated into two sub‐problems. The first subproblem is the interference power problem, which can be solved either sub‐optimally or optimally using Lagrange duality. The second sub‐problem is the QOS problem, which can be solved either sub‐optimally or robustly using non‐monotone spectral projected gradient method. The two sub‐problem solutions are then recombined into a single problem to extract beamforming vectors. Two methods are invoked to extract the beamforming vectors: either the successive convex approximation (SCA) method or the bisection search method. Theoretical analysis and simulation results indicate that the two methods can offer a tradeoff between better QOS (using bisection search method) or less computational complexity (using SCA method) [ABSTRACT FROM AUTHOR]

Energy efficiency (EE) maximisation is one of the most important necessities of the fifth‐generation (5G) wireless networks. In this study, both power allocation and channel assignment issues for the cellular network underlaid with device to device (D2D) communication are introduced. The main objective is to assign the users' resources in order to maximise the total EE of the network. The distributions of both the D2D users (DUs) and the cellular users (CUs) are based on the stochastic geometry theory. Hence, the mathematical formula for the optimisation problem is demonstrated. Additionally, the resource allocation link admission (RALA) algorithm is proposed to achieve the maximum EE. Moreover, it assigns the optimal powers for each CU and DU in the system. Furthermore, the best channel assignment for each new D2D link request is determined. The optimisation problem in the RALA scheme is solved by utilising a proposed modified Cuckoo search algorithm. Furthermore, the complexity analysis for the proposed scheme is introduced. From simulation results, the proposed RALA scheme is efficient to assign the resource allocation for the users to achieve the near‐optimal EE. [ABSTRACT FROM AUTHOR]

To meet the requirement of constrained delay and computation resource of the future vehicular networks, it is imperative to develop efficient content caching strategy and computation resource allocation strategy in mobile edge computing (MEC) servers. In the proposed network framework, since the caching capacity and computing resource of each MEC are limited, and the coverage areas of MECs are overlapped, the vehicular networks have to decide what contents to cache, how to offload tasks and how much computing resource needs to be allocated for each task. In this study, in order to jointly tackle these issues, we formulate caching strategy, offloading decision and computing resource allocation coordinately as a mixed integer non‐linear programming (MINLP) problem. To solve the MINLP problem, we divide it into two subproblems. Firstly, we investigate a balanced and efficient caching strategy based on similarity in vehicular networks. Secondly, we apply McCormick Envelopes to convert MINLP problem into LP problem, and then adopt improved branch and bound algorithm to obtain the optimal offloading decision and computing resource allocation strategy. Simulation results indicate that the proposed schemes have a good performance in reducing economic cost under the deadline of each task. [ABSTRACT FROM AUTHOR]

In order to solve the problem of network congestion caused by a large number of data requests generated by intelligent vehicles in LTE-V network, a brand-new fog server with fog computing function is deployed on both the cellular base stations and vehicles, and an LTE-V-fog network is constructed to deal with delay-sensitive service requests in the Internet of vehicles. The weighted total cost combines delay and energy consumption is taken as the optimisation goal. First a reinforcement learning algorithm Q-learning based on Markov decision process is proposed to solve the problem for minimising weighted total cost. Furthermore, this study specifically explains the setting method of three elements for reinforcement learning-state, action and reward in the fog computing system. Then for reducing the scale of problems and improving efficiency, the authors set up a pre-classification process before reinforcement learning to control the possible values of actions. However, considering that as the number of vehicles in system increases, Q-learning method based on recorded Q values may fall into a dimensional disaster. Therefore, the authors propose a deep reinforcement learning method, deep Q-learning network (DQN), which combines deep learning and Q-learning. Experimental results show that the proposed method has advantages. [ABSTRACT FROM AUTHOR]

The opportunistic network has become an appealing paradigm since it can reduce the energy consumption and cost on cellular network connections and relieve the communication burden of cellular networks. The probabilistic transmission scheme has been proposed as one of the typical opportunistic transmission schemes. However, most existing probabilistic transmission schemes neglect that, opportunistic transmission tasks in some applications have transmission time and cost budgets, and to set proper delay and hop count thresholds on encountering probabilities between relay nodes and their destination nodes can help to filter redundant long‐delay and high‐cost opportunistic paths for packets. In this study, the authors proposed a delay‐aware and cost‐efficient probabilistic transmission method for opportunistic networks. In this method, direct and indirect encountering probabilities related to delay and hop count are defined, and accordingly, a relay node selection algorithm is provided with preset encountering delay and hop count thresholds to compare probabilities of nodes to encounter the destination node within the preset thresholds as their transmission quality metrics. The simulation results verify that the proposed method can reduce transmission delay and cost efficiently. [ABSTRACT FROM AUTHOR]

Owing to the rapid and facile deployment of unmanned aerial vehicles (UAVs), the third-generation partnership programme has recently shown considerable interest in UAVs for assisting current terrestrial base stations. Hence, the feasibility of using UAVs has been vigorously investigated for enhancing the performance of traditional ground-based communications, e.g. coverage and quality-of-service enhancement under natural disaster or overwhelming data requirement conditions. Here, however, the energy-efficient operation of the UAV is necessary to obtain the essential benefits. To strengthen the base of operation and management of UAVs in cellular systems, the authors consider in this Letter a single mission in which a small-size UAV transmits a given data volume to a cell boundary user. They design the transmit power and altitude of the UAV to complete the mission with high-energy efficiency. From the numerical results, it is verified that the UAV transmitting data with the designed transmit power at the designed altitude can complete the mission with near-optimal, i.e. maximum, energy efficiency. [ABSTRACT FROM AUTHOR]

In this study, the authors present results of a call testing campaign using voice over long term evolution (VoLTE) technology on the radio access network of the operator Telecom Italia mobile. The quality of the voice call is expressed by means of the mean opinion score (MOS). The electromagnetic propagation environment has been reproduced within a reverberation chamber, and its effect on MOS has been evaluated by varying the signal strength, i.e. the reference signal received power and the signal‐to‐interference noise ratio. The aim is to find a correlation between the radio propagation environment and the perceived quality of the speech. Regardless of the networks technology, voice quality could be impacted by several factors: traffic load of LTE evolved Node B, quality of service, radio pathloss, mutual radio interference, multipath and so on. Interference and multipath are added to the useful signal in order to deteriorate the MOS, until the VoLTE calls dropped. Target of such work is to properly set the thresholds that trigger a handover of single radio voice call continuity to other radio access technologies (UMTS or GSM). Tests take also into account the adaptive multi‐rate CoDec selected by the network. [ABSTRACT FROM AUTHOR]

A dual‐frequency band low input power rectenna is proposed in this study. The rectenna is comprised of a co‐planar waveguide (CPW) rectifier integrated with a rectangular split ring antenna loaded by a spiral strip line. A single diode series connection topology is used to miniaturise the losses at low input power. A spiral coil in addition to two short circuit stubs are used as a matching network for maximum power transfer between the antenna and the rectifying circuit. The proposed rectenna operates at low input power with relatively high measured RF‐DC conversion efficiency up to 74% at input power of −6.5dBm at the first resonant frequency f1=700MHz and 70% at −4.5dBm at the second operating frequency f2=1.4GHz with a resistive load of 1.9kΩ. The measured rectenna sensitivity (the rectenna ability to receive low power with acceptable conversion efficiency) reaches up to −20dBm with a conversion efficiency of 47 and 36% at f1 and f2, respectively, and a DC output voltage of 0.18V. The measured efficiency is over 50% from −18 to −3.5dBm and from −15 to −1.5dBm at f1 and f2, respectively. [ABSTRACT FROM AUTHOR]

Many problems in cellular communications cannot be solved classically. Due to its robustness, quantum computing can enrich the classical with other dimensions, security and cryptic‐natured. However, the awareness about how to fully bridge the classical and quantum communications is not fully realised. In other words, the quantum phenomena are not totally utilised within the classical dimension. This work rather discusses directions and evaluations for future quantum solutions to traditional cloud mobile networks. Particularly, using quantum correlation phenomena to enhance the performance of X2 application protocol (X2‐AP) by reducing the signalling overhead regarding the delay and power consumption that classical cloud encounter. Through modelling the latency of both paradigms using 'MATLAB', this work promises a delay reduction when adapting quantum method into the cloud. This study also models the power consumption and energy efficiency of traditional and quantum‐based cloud networks. This work also shows, via modelling the power consumption, that installing a quantum‐based paradigm is not a power costly method; rather, it shows identical power and energy efficiency figures with a possibility of improvement. [ABSTRACT FROM AUTHOR]

A key concern in the design of 5G is the radio access network, which is expected to be significantly denser and more advanced, with considerably higher infrastructure and power consumption cost than that of conventional mobile network standards. Novel algorithms/approaches for optimal planning of the radio access network are required for tackling the additional complexity of the problem of cost‐efficient radio access planning in 5G, which cannot be properly handled by conventional approaches. This study proposes a novel optimisation framework for the cost‐efficient deployment and configuration of 5G base stations. The main idea of the proposed optimisation framework is to exploit heterogeneity in three key 5G technologies, heterogeneous base station architecture, cell range extension and multiple‐input–multiple‐output spatial multiplexing, by jointly optimising their configurations during network design. In addition, the proposed optimisation framework includes generic steps for applying meta‐heuristic algorithms to the problem, which are necessary to overcome the problem's complexity, especially for large problem instances. The authors' results show that their novel optimisation framework improves the cost efficiency of the network planning both in terms of power and infrastructural cost to operators. [ABSTRACT FROM AUTHOR]

For the problem that mobile devices that are far away from the base station obtain limited wireless resources, which causes high transmission delays, the study proposes a multi-hop path to assist users who are far away from the base station to use edge computing resources. And it combines cloud radio access network and wireless self-organising network. The modelling aims to minimise the total energy consumption under the constraints of task delay considering the mobility of mobile devices. Meanwhile, it selects the joint optimisation problem of the path for data transmission and the virtual machine for calculation. This study also introduces the krill herd algorithm and analyses its advantages and disadvantages. The author enhances the global search ability of the algorithm by defining perturbation factors in the random diffusion behaviour and introduces a new strategy of elite selection and retention into the iterative process to improve the convergence accuracy. Finally, the improved krill herd algorithm is used to solve the joint optimisation problem and a better allocation result than the separate resource allocation of calculation and communication is obtained. The experiment proves that the selection algorithm combining virtual machine and routing proposed in this study can achieve the expected results. [ABSTRACT FROM AUTHOR]

Caching is a promising solution for the cloud radio access network (Cloud‐RAN) to mitigate the traffic load problem in the fronthaul links. Multiuser downlink beamforming plays an important role in efficient utilisation of spectrum and transmission power while satisfying the user's quality of service requirements. When the number of users exceeds the serving capacity of the network, certain users will have to be dropped or rescheduled. This is normally achieved by appropriate admission control mechanisms. Introducing local storage or cache at the remote radio heads where some popular contents are cached, the authors propose beamforming and admission control techniques for cache‐enabled Cloud‐RAN in the downlink. This minimises the total network cost including power and fronthaul cost while admitting as many users as possible. They formulate this multi‐objective optimisation problem as a single objective optimisation problem. The original problem, which is a mixed‐integer non‐linear programme, is first converted to the mixed‐integer second‐order cone programming form. The branch and bound algorithm is then used to determine the optimal and suboptimal solutions. A simulation study has been conducted to assess the performance of both methods. [ABSTRACT FROM AUTHOR]

To solve the inefficient use of internet protocol (IP) addresses in the current host‐centric internet, the content‐centric networking (CCN) replaces the IP address with the content name and the cache memory is used to store data temporarily on each router. One of the key components in CCN is the pending interest table (PIT). When an interest arrives at a CCN node, the node searches the PIT entries for the same request. If no, the node searches the PIT for an idle entry and a request is sent. If there is no idle entry, the request is blocked. If yes, the aggregation mechanism is performed. To prevent the request from becoming out‐of‐date, the timeout mechanism is adopted. In this work, the authors focus on the performance analysis of PIT in the cellular network with two classes of interests, new and handoff interests. To provide service differentiation, a reservation mechanism is adopted. Furthermore, interests may enter the retrial queue and wait to retry later. First, the authors derived the analytical model for the system considered. Second, the impact of various system parameters on the performance measures is studied. Last but not least, computer simulation is written to verify the accuracy of the analytical results. [ABSTRACT FROM AUTHOR]

This work proposes a cluster oriented channel assignment and difference of two convex functions (d.c.) programming based power optimisation algorithm for the downlink device‐to‐device (D2D) communication underlaying cellular networks. The authors' objective is to maximise D2D throughput while protecting the performance of existing cellular users (CUs) whose channel is reused among multiple D2D pairs, by imposing a minimum rate requirement constraint on each CU. The joint channel and power optimisation problem is a mixed integer non‐linear programming problem that is NP‐hard to solve. Therefore, a three stage solution is proposed: cluster formation to minimise the interference among the D2D pairs followed by an optimal channel assignment using the Hungarian algorithm and then an iterative power optimisation algorithm based on d.c. programming. Moreover, the transmission power of base station and D2D users is optimised on the same channel while considering the mutual interference among D2D pairs. Numerical results verify the effectiveness of the proposed resource allocation scheme in terms of the D2D sum rate and the number of successful transmission of D2D users. Moreover, the iterative power optimisation algorithm shows a fast convergence behaviour. In addition to this, the energy efficiency is also analysed with respect to various parameters. [ABSTRACT FROM AUTHOR]

In this study, the authors present an energy-efficient technique for the fog-networks, where a node can communicate to other users using limited network infrastructure support. The authors' contribution is central to node mobility and lower energy consumption rates. They propose an energy-efficient cellular communication model for fog-networks. To establish the connection between the source and the destination node, the next generation involves node base station imports required information from nearby fog nodes and performs the network management with the help of data analytic units. A system-level optimisation for the energy consumption model is also proposed, which supports a high degree of node mobility. They compared their results with 4G/LTE and observed that the proposed work provides the least energy consumption as compared to the legacy of the networks. [ABSTRACT FROM AUTHOR]

Non-orthogonal multiple access (NOMA) has been considered a key technology to address the increasing traffic demands for fifth-generation (5G) cellular wireless communication networks and internet of things. The NOMA technique offers efficient bandwidth utilisation, low latency, and support for the massive connectivity of devices in 5G networks. In the conventional NOMA system, orthogonal frequency division multiplexing (OFDM) is used as a pulse-shaping technique that causes high peak to average power ratio (PAPR) due to the superposition of signals of multiple users after passing through inverse fast Fourier transform and spectral inefficiency due to the cyclic prefix insertion. Therefore, an alternate methodology using wavelet OFDM is proposed in this research work, as a pulse-shaping technique for NOMA-based communication systems to improve spectral efficiency and system capacity The main contribution of this study is the analysis of the bit error rate (BER) performance and the effect of carrier frequency offset on system performance of wavelet NOMA (W-NOMA) technique in 5G networks. The simulation results demonstrate that W-NOMA outperforms the conventional NOMA with reference to PAPR and BER. [ABSTRACT FROM AUTHOR]

This study concentrates on the study of a downlink cooperative cellular (DCC) network in which an access point is located in the centre of each cell and two relay stations are installed in the border between both sectors of a cell to obtain higher cell-edge throughput. To optimise the network efficiency, a joint optimal subcarrier and power allocation scheme is proposed which initially derives the highest achievable rate for a single-legacy user (LU), then, through further evaluation and analysis, this is generalised to the case of a multiple-LU environment. Next, to maximise the overall throughput and ensure fairness, a multi-objective lexicographical optimisation problem (MLOP) is formulated to maximise the minimum LUs rate while improving the overall throughput. As the proposed MLOP is a mixed-integer non-linear problem, finding optimal solutions is impractical and in general, there is no standard method for optimally obtaining a solution. Hence, two efficient algorithms are introduced in this study. Simulation results confirm that the proposed algorithms achieve a fair and near-optimal performance for the multi-LU DCC network based on two relay channels, which makes them desirable in practice compared to some of the sub-optimal well-known algorithms investigated in this study. [ABSTRACT FROM AUTHOR]

Over the last 5–7 years, with the proliferation of mobile computing devices, there has been a tremendous increase in data usage by mobile subscribers. This has quite often resulted in network congestion, forcing the operators to either increase the available bandwidth or reduce the data-rate per subscriber. To overcome this problem, network operators have been deploying different radio access networks, including Wi-Fi and small cells across their coverage areas. In order to remain always best connected, several techniques have been proposed over the period for efficient network selection. All these techniques can be broadly categorised into either device-centric or network-centric solutions. However, both device-centric and network-centric solutions have their disadvantages. In this study, a 'dual priority' scheme is proposed and developed that takes into account the preferences of both the subscribers and the network operator. Notably, the proposed 'dual priority' scheme offers a combined decision for the efficient handover of subscribers from cellular to Wi-Fi. In this work, every device has its own mechanism of ranking its preferred networks, after which the network takes the decision for offload based on the preferences and its resource availability. It has been observed that the proposed dual priority scheme results in up-to three times reduction in the time taken for offloading decision as compared to state-of-the-art network-centric solutions. [ABSTRACT FROM AUTHOR]

Due to the characteristics of measurement datum distribution, the altitude positioning error of GPS (Global Positioning System) is relatively large. This study discusses a differential barometric altimetry (DBA) system from systematic implementation level and provides a key technical solution for the continuous and precise altitude measurement from the DBA systematic implementation aspect, which can provide a good supplement and enhancement for GPS. The structure of signal message is designed; the power spectrum of spread spectrum ranging signal is given, and the fusion of navigation and communication is realised. The two dimensional curved surface fitting function of pressure and temperature (P, T) is constructed, and the fitting parameters are calculated by the least‐square solution, which can realise calibration compensation and measurement correction of sensor. The influence of the system noise variance matrix Qk and the measurement noise variance matrix Rk on the filtering effect in Kalman filter is analysed. An algorithm of multi‐base station (BS) correction is proposed, which can realise the height information correction calculation in measuring station (MS) via seamless handover between multi‐BSs. The experimental results show that the key technology solutions in DBA system can achieve a well systematic performance.. [ABSTRACT FROM AUTHOR]

For wireless networks, it is highly desirable to design a quality‐of‐service‐promotion strategy to allocate the transmission power. In this study, the authors apply the deep learning methodology to solve such a problem in a duplex device‐to‐device network. The model is formulated as a constrained non‐linear programming problem. The training data are generated by a standard optimisation tool. Then, an artificial neural network is designed to learn the system from the training data. Simulation results show the effectiveness of deep leaning. [ABSTRACT FROM AUTHOR]

In today's world, power is one of the resources that needs effective utilisation similar to the bandwidth utilisation. As the battery life of the nodes in the cellular networks is not a problem, there is not much extensive research toward energy consumption in the cellular networks. Nevertheless, currently the focus is toward conserving the power being utilised by various components in the cellular network. Hence, an energy‐efficient channel allocation (E2CA) procedure for cellular networks with fifth‐generation network characteristics is proposed in this study, where the energy consumption is reduced with the concept of sleep mode for base station (E2CA‐SM). The SM is more popular in sensor networks when compared with cellular networks. The proposed E2CA‐SM algorithm shows low‐energy consumption during peak and non‐peak hours of cellular traffic. It is shown that the energy consumption per packet is 35.5% less when compared with multi‐traffic, with queue, learning automata‐based reservation, 32% when compared with E2CA. The system is modelled using single‐dimension Markov's model. There will be a trade‐off between blocking, dropping probability, and energy consumption, which is tackled in this study. [ABSTRACT FROM AUTHOR]

This work studies the direct wave suppression technology of passive radar system based on ‘global system for mobile (GSM)’ communication. In order to suppress direct waves, this study proposes an adaptive suppression algorithm based on NLMS criterion. Achieves great suppression of the strong interference signal, and finally realised target positioning and velocity measurement to the actual measured GSM signal.

An antenna capable of directly phase modulating a radio frequency (RF) carrier is discussed, designed, and measured as both an antenna and a modulator. Access point densification for the Internet of Things will be expensive in part due to the cost and inefficiency of amplifying waveforms with large peak-to-average power ratios for downlink transmission. Directly modulating at the antenna means only a carrier wave has to be amplified, reducing the cost of densification. Here, reconfigurable frequency selective surfaces are suggested as phase modulators. The design process for producing a phase modulating antenna is detailed, and a prototype is fabricated that is capable of up to 8-PSK modulation with 5.3 dB variation in constellation points and a peak gain of 2.3 dB. When implemented in an end-to-end communications system, the antenna exhibits only 1.5 dB drop in performance compared with instrument grade modulation in an additive white Gaussian noise (AWGN) channel. [ABSTRACT FROM AUTHOR]

A new power allocation algorithm is proposed based on the Glicksberg game for cellular downlink non‐orthogonal multiple access (NOMA) networks. First, a price‐based user's utility function is proposed, and shown that it is effective and restrictive. Secondly, the Hessian matrix is used to derive an expression for power price based on the restricted transmission power and number of the served users in the cell. Then, the existence of a unique Nash equilibrium is proven and the optimum solution that maximises the utility function is presented. Finally, simulation results show that the proposed power allocation mechanism outperforms existing algorithms in terms of sum data rate and average data rate of the users. [ABSTRACT FROM AUTHOR]

Shotgun cellular systems (SCSs) are wireless communication systems with randomly placed base stations (BSs) over the entire plane according to a two-dimensional Poisson point process. Such a system can model a dense cellular or wireless data network deployment, where the BS locations end up being close to random due to constraints other than optimal coverage. SCSs have been studied by considering path-loss and independent shadowing paths between BS to mobile station (MS) pairs in the channel models. In this paper, we consider correlated shadowing paths between BS to MS pairs as a most important factor, and analyze the carrier to interference ratio (CIR), in a SCS over this correlation, and determine an expression for distribution of CIR, and obtain the tail probability of the CIR. [ABSTRACT FROM AUTHOR]

This work studies the direct wave suppression technology of passive radar system based on 'global system for mobile (GSM)' communication. In order to suppress direct waves, this study proposes an adaptive suppression algorithm based on NLMS criterion. Achieves great suppression of the strong interference signal, and finally realised target positioning and velocity measurement to the actual measured GSM signal. [ABSTRACT FROM AUTHOR]

To cope with the explosion of video traffic, mobile edge computing (MEC) has been introduced as a promising technology in fifth generation networks to enable caching and computing resources to transcode video contents and cache them within the edge of mobile networks. In this study, a joint caching and computing resource allocation mechanism is proposed to effectively schedule the resources of the mobile edge networks. The authors formulate a Stackelberg game to analyse the allocation problem between the MEC server and multiple base stations (BSs). The MEC server aims to impose the prices to the BSs to maximise its revenue, while the BSs compete to determine the caching/computing space that they can occupy at the MEC server to improve the quality of experience of their service users. The competition between the BSs is formulated as a non‐cooperative subgame where each BS is designed to maximise the request rate that can be served by the MEC server. Then, the proposed games are proved to converge to a unique Stackelberg equilibria. Numerical simulations are presented to verify the proposed scheme. It is shown that the proposed schemes are effective in resource allocation for both storage and computational capacities in mobile edge networks. [ABSTRACT FROM AUTHOR]

Device‐to‐device (D2D) communication system is considered one of the most effective technology directions for solving the spectrum scarcity problem in 5G wireless communication. In this study, an electronic relay is proposed to be utilised in D2D communication. The electronic relay is a hybrid cooperative relay consisting of compress and forward relay with and without coding techniques, decode and forward relay and amplify and forward relay with variable gain. The selection of the most appropriate one has performed automatically according to the feedback channel state information. Additionally, the multiple‐input multiple‐output (MIMO) electronic relay with the multi‐user and massive MIMO destination is introduced. The closed formulas of the outage probability for both cellular user and D2D transmission are derived. Furthermore, the analytical discussions for the proposed electronic relay are executed. Extensive MATLAB simulation programmes are executed to study the performance of the proposed system and to compare it with the conventional one. Moreover, the average sum rate is derived in terms of a number of electronic relay antennas and the D2D density through cellular networks. [ABSTRACT FROM AUTHOR]

In device‐to‐device (D2D) communication underlaying cellular networks, the D2D user equipments (DUEs) can communicate by sharing the radio resources assigned to cellular user equipments. D2D communication is expected to improve the network throughput and save more energy for the user equipments. However, D2D communication causes severe interference to both the cellular users and other DUEs which is a challenge to radio resource allocation. The authors propose joint channel and power allocation algorithm to maximise the network achievable throughput, control the interference from the DUEs transmissions to cellular users and improve the energy efficiency of the user equipments. The authors formulate the problem and solve it using convex optimisation methods to select DUEs and set their powers in each channel. Simulation results show that the proposed algorithm can offer near‐optimal performance and outperforms the comparable algorithms especially in terms of achievable throughput even with markedly reduced complexity levels. [ABSTRACT FROM AUTHOR]