This paper explores the utilization of Reconfigurable Intelligent Surfaces (RISs) within multi-cell vehicular open radio access networks to redirect signals toward users with wireless link blockages. To address this, a stochastic optimization problem is formulated to determine the optimal transmit precoding for Road Side Units (RSUs) and adjust the phase shifts of corresponding RISs, considering random obstacles in wireless links. The objective is to enhance long-term data throughput while guaranteeing the Quality of Service (QoS) for each user. To solve the problem, a federated learning framework is introduced that employs multi-agent Deep Reinforcement Learning (DRL) and aligns with the O-RAN architecture. Specifically, deep learning agents are deployed at network edge servers, integrated within the Near-Real-Time Radio Access Network Intelligent Controller (Near-RT RIC), where they gather network information, train local models, and perform online executions. A global model is constructed in the Non-Real-Time RIC, which resides on a central server, by aggregating the local models received from edge servers. Simulation results confirm that the proposed method significantly improves average network data rates while ensuring users receive adequate link quality.

The evolution of 6G networks has led to the development of open, intelligent, and decentralized architectures. Nevertheless, protecting data privacy and security across systems with multiple vendors remains a critical challenge. Although Secure Multi-Party Computation (SMPC) and the Open Radio Access Network (O-RAN) have emerged as promising candidates, existing articles have evaluated their performance in isolation. It implies that their combined impact on system performance has not yet been explored. Consequently, this article presents an integrated, deployment-oriented synthesis that maps lightweight and scalable SMPC protocols to O-RAN components such as the RAN Intelligent Controller (RIC), xApps, and open interfaces. Particularly, this article identifies four key research challenges: SMPC protocol scalability, architectural integration, secure AI optimization, and multi-vendor data confidentiality. To address these identified challenges, a comprehensive performance evaluation of state-of-the-art SMPC schemes is performed. The evaluation focuses on latency, bandwidth, and computational overhead of SMPC schemes in 6G-enabled O-RAN systems. Thus, by linking SMPC techniques with O-RAN architectures, this article provides practical insights and quantitative evidence to support the development of secure, efficient, and interoperable 6G wireless technologies.

OpenRAN is revolutionizing wireless telecommunications, enabling more flexible and innovative network architectures. Within this framework, near-real-time applications in RAN Intelligent Controllers (near-RT RIC) are pushing the boundaries of ultra-reliable low latency communications. However, security concerns challenge their adoption. This paper investigates vulnerabilities in near-RT RIC AI xApps through systematic experiments, focusing on a Handover AI xApp. Using four distinct attack strategies, we demonstrate that current security measures are inadequate, exposing these Ultra-Reliable Low Latency Communications (URLLC) AI xApps to various attacks. Our findings highlight the potential for malicious exploitation, emphasizing the need for robust security frameworks in OpenRAN deployments utilizing near-RT applications.

The contemporary era experiences an unprecedented dependence on data generated by individuals via an array of interconnected devices constituting the Internet of Things (IoT). The information amassed through IoT devices serves many objectives, including prescriptive analytics and predictive maintenance, preemptive healthcare measures, disaster mitigation, operational efficiency, and increased yield. In contrast, most applications or systems that rely on user-generated data to fulfill their business objectives face challenges in adhering to privacy protocols. Consequently, users are exposed to many privacy risks. Such infringements upon privacy provisions give rise to apprehensions regarding the authenticity of the processed data. Hence, this paper presents weaknesses and challenges in current practices and proposes “PrivySeC,” a distributed ledger technology (DLT) based framework for privacy-preserving and secure sharing of personally and non-personally identifiable information. The security analysis indicates that the proposed solution ensures data privacy by design and complies with most of the requirements mandated by various privacy regulations. Similarly, PrivySeC promises low transaction latency and provides high throughput. Although we have created a privacy-preserving solution for sharing smart farm data, it can be customized to meet the specific privacy requirements of individual applications.

The growth of wireless communications facilitates advanced technologies like Tactile Internet and robotics, requiring ultra-reliable low-latency communications (URLLC). Effective user equipment (UE) handover between access points (AP) is crucial for URRLC to enhance Quality of Experience (QoE). However, HO failures can occur due to various reasons, impacting URRLC use cases reliant on service reliability. This paper introduces HORLA, a multi-objective reinforcement learning model that enhances received signal strength and reduces outage probability during AP selection for UE. HORLA surpasses the conventional HO algorithm, reducing failure attempts by over 40% and cutting energy consumption for reattempted HO requests by nearly 57%.

The reliability of any IoT system's operation depends upon the accuracy of sensor data. Numerous sensing devices are also embedded in autonomous systems. The adversary can manipulate the output of an IoT device, such as a speed sensor or a temperature sensor, by altering its hardware, software modules, network parameters, or device configuration. These unauthorized changes may affect the legitimate operation of the autonomous system and cause a malfunction or a safety hazard. In addition, the corrupt sensor data may also affect the machine learning models by introducing false training data or biasing the model towards certain decisions to cause the autonomous system to make incorrect decisions. The existing techniques mostly perform memory attestation or ensure the secure execution of an application. In addition, current approaches have unrealistic assumptions about adversaries’ capabilities and rely on trusted parties to initiate and run the attestation protocol. No existing technique provides all the required security features, including protection against return-oriented programming and network attacks, including interference, rainbow, and physical compromise. Hence, this research presents a secure and efficient version of a unique hybrid attestation scheme "I2Map" that detects a malicious or malfunctioning IoT device based on an integrity map. The performance analysis infers that I2Map performs better in transaction commit time and transaction costs with more device parameters than its predecessor.

Industrial Internet of Things (IIoT) applications generate data in varying amounts with diverse quality of service requirements. The adaptive network access approach and distributed resource management in IIoT networks can reduce the communication overheads caused by centralized resource management approaches. In this regard, statistical learning is a promising tool for addressing decision-making problems in a dynamic environment. This article considers uplink dominant IIoT networks in which massive devices generate delay-sensitive and delay-tolerant data and communicate over shared radio resources. We propose a novel grant-free access scheme using a statistical learning approach that enables IIoT entities to perform delay-sensitive and delay-tolerant transmissions over dynamically partitioned resources in a prioritized manner. In order to improve utilization of available radio resources, we design an adaptive network access mechanism operating in a semi-distributed manner. This mechanism enables end devices to use their transmission history to choose between static and dynamic resource allocation-based grant-free schemes in a dynamic environment. Simulation results show that average latency and resource utilization vary in grant-free access schemes employing static and dynamic resource allocations. Thus, compared to a single transmission scheme, the proposed adaptive network access offers better channel utilization while meeting the application-specific latency bound in IIoT networks.

This article presents a multiservice pixelated stacked antenna for dual-band application at 5.2 and 5.8-GHz bands. An efficient method for designing multilayer or stacked antennas for multistandard Internet of Things (IoT) applications is proposed in this article. The proposed antenna topology is based on two different pixel shapes and offers essential aspects, such as flexibilities in the design of low-profile single-band or multiband antennas for wireless systems. The antenna design consists of two pixelated layers of radiating patch, consisting of different shaped pixels. The V-shaped binary particle swarm optimization (VBPSO) algorithm has been implemented for the optimization of pixel positions. Only by considering the predefined regions, the antenna can be designed and optimized for various design goals. In the design procedure, triangular-shaped pixels are used to form the principal radiating patch, while square-shaped pixels are implemented on the stacked parasitic patch. Measurement and simulation results are in good agreement which proves the accuracy of the design and simulation procedure. The antenna operates at 5.16–5.21 GHz and 5.79–5.86 GHz. With a compact design, the proposed antenna achieves 4.7 and 4.4-dBi gain at 5.2 and 5.8 GHz, respectively. The proposed antenna design methodology offers great potentials to be aligned with specific design requirements of wireless low-profile IoT devices.

The Software Defined Network paradigm deviates from traditional networks by logically centralising and physically separating the control plane from the data plane. In this work, we present the idea of a modular, agent-based SDN controller. We first highlight issues with current SDN controller designs, followed by a description of the proposed framework. We present a prototype for our design to demonstrate the controller in action using a few common use-cases. We continue the discussion by highlighting areas that require further research.

Utilizing the millimeter-wave (mmWave) frequency is a promising solution to meet fast-growing traffic demand over wireless networks. However, mmWave communications are sensitive to physical obstructions on signal propagation. In this paper, the reconfigurable intelligent surfaces (RISs) are investigated to overcome the limitations of mmWave communications. Particularly, an RIS is deployed to reflect the mmWave signals towards vehicular users who experience direct link blockages that may occur due to static or dynamic obstacles. To this end, a risk-averse optimization problem is designed to optimize the Base Station (BS) precoding matrix and the RIS phase shifts under stochastic link blockages. A solution approach is developed in two phases: the BS precoding optimization and the RIS phase shift control phases. In the first phase, a Decomposition and Relaxation-based Precoding Optimization (DRPO) algorithm is developed to obtain the optimal precoding matrix. In the second phase, a learning-based method is introduced to dynamically adjust the direction of reflected signals under channel uncertainty. Extensive simulations are presented to validate the efficacy of the developed algorithms. The obtained results show that the developed algorithms can ensure reliable transmissions to users in non-LoS areas and improve network performance.

In this paper, we propose a novel mobility model providing train traffic traces essential for train-to-train communication models. As the proposed mobility model works only based on trip timetables and train timetables are currently available in real-time, the produced mobility traces will be also in real-time. Additionally, as no GPS module is used in this method, our proposed model can provide a practical solution when signal from GPS or Assisted GPS is poor or unavailable such as in urban area or inside tunnels. Furthermore, as we used an energy optimization function, the proposed mobility model will provide a guidance trajectory for trains to have an energy-optimized operation. We also develop an algorithm that can determine the specifications of contacts between trains based on the traffic traces obtained from the mobility model. Such specifications includes duration, rate and location of train contacts used for estimation of data exchange capacity between trains through train-to-train communications. We validate our proposed model using data collected from Sydney Trains of Australia. The results obtained from our proposed model show over 98 percent accuracy in comparison with the real data collected via a GPS module from Sydney Trains.

Future Internet of Things (IoT) devices are expected to be fully ubiquitous. To achieve this vision, a new generation of IoT devices needs to be developed, which can operate autonomously. To achieve autonomy, IoT devices must be completely wireless, both in terms of transmission and power. Further, accurate sensing is another crucial parameter of autonomy. Several wireless standards have been developed for improving the efficiency of IoT applications. However, the powering of IoT devices, sensor accuracy, and efficiency of electronic devices are open research problems in literature. With the advent of metamaterial perfect absorbers (MPAs), electromagnetic waves can be used as a source of energy, to enable sensing of the phenomenon and as a carrier for exchanging data. In this article, an extensive application-based investigation has been conducted on design principles and various methods of enhancing MPA characteristics. Moreover, the current applications that benefit from MPA, such as absorption of undesired frequencies, optical switching, energy harvesting, and sensing, are investigated. Finally, some implemented examples of MPA in industrial applications are provided along with possible directions for future work and open research areas.

The existing lottery-based consensus algorithms, such as Proof-of-Work, and Proof-of-Stake, are mostly used for blockchain-based financial technology applications. Similarly, the Byzantine Fault Tolerance algorithms do provide consensus finality, yet they are either communications intensive, vulnerable to Denial-of-Service attacks, poorly scalable, or have a low faulty node tolerance level. Moreover, these algorithms are not designed for the Internet of Things systems that require near-real-time transaction confirmation, maximum fault tolerance, and appropriate transaction validation rules. Hence, we propose "Pledge," a unique Proof-of-Honesty based consensus protocol to reduce the possibility of malicious behavior during blockchain consensus. Pledge also introduces the Internet of Things centric transaction validation rules. Initial experimentation shows that Pledge is economical and secure with low communications complexity and low latency in transaction confirmation.

Mission-critical machine type communication (MC-MTC) systems in which machines communicate to perform various tasks such as coordination, sensing, and actuation, require stringent requirements of ultra-reliable and low latency communications (URLLC). Edge computing being an integral part of future wireless networks, provides services that support URLLC applications. In this paper, we use the edge computing approach and present a statistical learning-based dynamic retransmission mechanism. The proposed approach meets the desired latency-reliability criterion in MC-MTC networks employing framed ALOHA. The maximum number of retransmissions Nr under a given latency-reliability constraint is learned statistically by the devices from the history of their previous transmissions and shared with the base station. Simulations are performed in MATLAB to evaluate a framed-ALOHA system's performance in which an active device can have only one successful transmission in one round composed of (Nr + 1) frames, and the performance is compared with the diversity transmission-based framed-ALOHA.

Frost damage in broadacre cropping and horticulture (including viticulture) results in substantial economic losses to producers and may also disrupt associated product value chains. Frost risk windows are changing in timing, frequency, and duration. Faced with the increasing cost of mitigation infrastructure and competition for resources (e.g., water and energy), multiperil insurance, and the need for supply chain certainty, producers are under pressure to innovate in order to manage and mitigate risk. Frost protection systems are cyber-physical systems (CPSs) consisting of sensors (event detection), intelligence (prediction), and actuators (active protection methods). The Internet-of-Things communication protocols joining the CPS components are also evaluated. In this context, this article introduces and reviews existing methods of frost management. This article focuses on active protection methods because of their potential for real-time deployment during frost events. For integrated frost prediction and active protection systems, prediction method, sensor types, and integration architecture are assessed, research gaps are identified and future research directions proposed.

This paper introduces a new framework into future data-driven railway condition monitoring systems (RCM). For this purpose, we have proposed an edge processing unit that includes two main parts: a data classification model that classifies Internet of Things (IoT) data into maintenance-critical data (MCD) and maintenance-non-critical data (MNCD) and a data transmission unit that, based on the class of data, employs appropriate communication methods to transmit data to railway control centers. For the transmission of MNCD, we propose a travel pattern method that employs train stations as points of data offloading so that trains can deliver data as well as passengers at stations. The performance of our proposed solution is successfully validated via three various data sets under different operating conditions.

This paper presents a new Multi-hop Device-to-Device (MD2D) routing protocol, referred to as SMDRP (SDN-based Multi-hop D2D Routing Protocol), for SDN-based wireless networks. Our proposed protocol can be considered as a semi-distributed routing protocol, where an SDN controller manages and controls part of the overall MD2D routing functionality to increase scalability while enabling network operators to control and maintain the out-of-band packet forwarding network. This paper also extends prior work on the Hybrid SDN Architecture for Wireless Distributed Networks (HSAW) [1] and is adapted to the framework presented in this paper. In HSAW, since all link state information is flooded by the controller to the nodes, the network will experience scalability problem. In our approach, this problem is overcome by only passing the next hop for each active route to the mobile nodes. To investigate this, we performed a theoretical and simulation studies comparing HSAW with SMDRP. From our result, it can be seen that for larger density populated networks, SMDRP shows better scalability than HSAW. In addition, mobile nodes need less memory and energy for their communications.

Green cellular network helps to decrease environmental pollution. In contrast, massive connectivity and demand for higher data rate promise the presence of new generation of cellular system (5G) and small cell networks. Hence, expectation on increasing the number of base stations (BSs), which leads to increase in energy usage. One way to improve energy consumption is by shutting down the redundant BSs while sustaining the Quality-of-Service (QoS) for each user. In this paper, we propose a dynamic structural algorithm based on transportation problem, to switch on/off the BSs in cellular networks without compromising its coverage, and maintain the networks load by neighboring cells. We use weighted graphs to translate our problem as a transportation problem and then use linear programming to solve it. The cost of transport, turning a BS into sleep mode, is illustrated as a function of energy usage, coverage area and load on the BSs. Running the proposed method consecutively provides the maximum number of BSs whom are at sleep mode. The methodology explained in this paper reduces energy consumption to almost 40%, whereas maintaining all the existing loads in the network.

As a new research concept for both academia and industry, there are several challenges faced by the Network Function Virtualization (NFV). One such challenge is to find the optimal mapping and scheduling for the incoming service requests which is the focus of this study. This optimization has been done by maximizing the number of accepted service requests, minimizing the number of bottleneck links and the overall processing time. The resultant problem is formulated as a multi- objective optimization problem, and two novel algorithms based on genetic algorithm have been developed. Through simulations, it has been shown that the developed algorithms can converge to the near to optimal solutions and they are scalable to large networks.

In this paper, we propose an offloading scheme to transfer massive stored sensor data from rolling stock to railway data centers. We apply a delayed offloading strategy for non-critical stored data assuming that the critical data has been already separated through an appropriate edge processing task and has been sent via a real-time communication such as cellular networks. We propose train stations as potential and feasible spots for data offloading via available wireless local area networks (WLAN) such as existing WiFi network at stations. Thus, stations will not only be the places of passenger exchange but also data exchange. We develop an analytical model customized for the proposed offloading strategy in rail applications. Then we validate the performance of our model through simulation in various scenarios in Omnet. The simulation results shows an accuracy of %98.67 for the proposed analytical model with reference to the simulation results in Omnetpp. Additionally, by using our proposed scheme, we can theoretically offload up to 5.43 GB per each stopping station.

The growth of technical revolution towards 5G Next generation networks is expected to meet various communication requirements of future Intelligent Transportation Systems (ITS). Motivated by the consumer needs for variety of ITS applications, bandwidth, high speed and ubiquity, researches are currently exploring different network architectures and techniques, which could be employed in Next generation ITS. To provide flexible network management, control and high resource utilization in Vehicular Ad-hoc Networks (VANETs) on large scale, a new hierarchical 5G Next generation VANET architecture is proposed. The key idea of this holistic architecture is to integrate the centralization and flexibility of Software Defined Networking (SDN) and Cloud-RAN (CRAN), with 5G communication technologies, to effectively allocate resources with a global view. Moreover, a fog computing framework (comprising of zones and clusters) has been proposed at the edge, to avoid frequent handovers between vehicles and RSUs. The transmission delay, throughput and control overhead on controller are analyzed and compared with other architectures. Simulation results indicate reduced transmission delay and minimized control overhead on controllers. Moreover, the throughput of proposed system is also improved.

Device-to-device (D2D) communications are set to form an integral part of future 5G wireless networks. D2D communications have a number of benefits such as improving energy efficiency and spectrum utilization. Until now much of the D2D research in LTE and 5G-type network scenarios have focused on direct (one-hop) communications between two adjacent mobile devices. In this paper, we propose a new routing framework called virtual ad hoc routing protocol (VARP). This framework introduces significant advantages such as better security, lower routing overheads, and higher scalability, when compared to conventional ad hoc routing protocols. It also reduces traffic overhead in LTE networks using multi-hop D2D communications under management of a software defined networking (SDN)controller. Further, it enables the development of various types of routing protocols for different networking scenarios. To this end, a source-routing based protocol was developed on top of VARP, referred to as VARP-S. We present a detailed analytical study of routing overhead in the VARP-S protocol, as compared to overhead analysis of our previous proposed hybrid SDN architecture for wireless distributed networks (HSAW) Our results show that VARP-S, compared to HSAW, achieves higher network scalability and lower power consumption for mobile nodes.

Wireless Body Area Networks (WBANs) are seen as the enabling technology for developing new generations of medical applications, such as remote health monitoring. As such it is expected that WBANs will predominantly transport mission-critical and delay sensitive data. A key strategy towards building a reliable WBAN is to ensure such networks are highly immune to interference. To achieve this, new and intelligent wireless spectrum allocation strategies are required not only to avoid interference, but also to make best-use of the limited available spectrum. This article presents a new spectrum allocation scheme referred to as Smart Channel Assignment (SCA), which maximizes the resource usage and transmission speed by deploying a partially-orthogonal channel assignment scheme between coexisting WBANs as well as offering a convenient tradeoff among spectral reuse efficiency, transmission rate, and outage. Detailed analytical studies verify that the proposed SCA strategy is robust to variations in channel conditions, increase in sensor node-density within each WBAN, and an increase in number of coexisting WBANs.

Wireless Sensor Networks (WSNs) are the key part of Internet of Things, as they provide the physical interface between on-field information and backbone analytic engines. An important role of WSNs-when collecting vital information-is to provide a consistent and reliable coverage. To Achieve this, WSNs must implement a highly reliable and efficient coverage recovery algorithm. In this paper, we take a fresh new approach to coverage recovery based on evolutionary algorithms. We propose EMACB-SA, which introduces a new evolutionary algorithm that selects coverage sets using a fitness function that balances energy efficiency and redundancy. The proposed algorithm improves network's coverage and lifetime in areas with heterogeneous event rate in comparison to previous works and hence, it is suitable for using in disaster management.

Device-to-device communication (D2D) will be an integral part of 5G wireless networks. Device-to-Device (D2D) communication provide the additional resources to the cellular users for spatially reusing licensed/unlicensed spectrum by establishing direct communication. Although, D2D communication is gaining significant attention towards offloading traffic in heterogeneous networks in licensed band, no attention has been given to offload traffic in an unlicensed band in a centralized manner. However, a major challenge of D2D communication is managing resources in an efficient manner in a heterogeneous network. This paper will direct a new approach to D2D Communication and will present a scalable MAC protocol for D2D communications based on Point Coordination Function (PCF) access mechanism. The importance of PCF access mechanism is that it operates in a centralized manner and highly suitable for the dense environment, hence, can create a centralized control in a distributive manner. In this article, we propose an innovative three tier 5G architecture for D2D communication, which will offload cellular traffic from the cellular network to the WLAN in a dense environment. Moreover, we will present a new centralized scalable MAC protocol for D2D communication between WLAN users, based on the IEEE 802.11 Point Coordination Function (PCF) access mechanism. Our simulation results show that the proposed MAC scheme can increase the capacity of the network and perform better relative to the legacy Distributed coordination Function (DCF) defined in IEEE 802.11.

In a rechargeable wireless sensor network, the data packets are generated by sensor nodes at a specific data rate, and transmitted to a base station. Moreover, the base station transfers power to the nodes by using Wireless Power Transfer (WPT) to extend their battery life. However, inadequately scheduling WPT and data collection causes some of the nodes to drain their battery and have their data buffer overflow, while the others waste their harvested energy, which is more than they need to transmit their packets. In this paper, we investigate a novel optimal scheduling strategy, called Scheduled WPT (SWPT), aiming to minimize data packet loss from a network of wireless powered sensor nodes by jointly considering the sensor nodes' energy consumption and data queue state information. The scheduling problem is formulated by a MDP model, assuming that the complete states of each sensor node are well known by the base station. This presents the best effort performance of the scheduling that can be collected in a wireless powered sensor network. The simulation results show that, in terms of network throughput and packet loss rate, the proposed scheduling model significantly improves the network performance.

This paper presents a node-level self-organizing interference avoidance scheme (SIAC) between multiple coexisting wireless body area networks (WBANs) that incorporates self-organization and smart spectrum allocation. It follows a biologically inspired approach based on the theory of pulse-coupled oscillators for self-organization. The proposed scheme makes three major contributions as compared to the current literature. Firstly, it considers node-level interference for internetwork interference mitigation rather than considering each WBAN as a whole. Secondly, it allocates synchronous and parallel transmission intervals for interference avoidance in an optimal manner and dynamically adapts to changes in their coexistence. Finally, it achieves collision-free, self-organized communication with only information of the firing signal of each WBAN and does not require a global coordinator to manage its communications. It operates on a nodes traffic priority, signal strength, and density of sensors in a WBAN. Simulation results show that our proposal achieves a fast convergence time despite the little information it receives. Moreover, SIAC is shown to be robust to variations in signal strength, number of coexisting WBANs and number of sensor nodes within each WBAN.

Wireless Body Area Networks (WBANs) were designed to collect and transfer vital physiological parameters within a short distance of the human body by employing low-power, light-weight, small-sized and smart implantable or wearable sensor devices. Lately, WBANs are expected to support various types of applications with data rates from a few Kbps upto 10 Mbps and satisfy the heterogeneous requirements of both medical and consumer electronics applications. Hence, novel communication protocols that consider a unique set of constraints and demands of these networks need to be developed to provide optimum system efficiency and data transmission reliability. As the IEEE 802.15.6 Medium Access Control (MAC) protocol based on the latest WBANs standard, cannot maintain the balance between the strict energy limitation and Quality of Service (QoS) requirements of such networks, this paper focuses on developing MAC protocols to improve the performance of WBANs specifically in the saturation condition. Two IEEE802.15.6-based MAC protocols are proposed to enhance channel access for the highest user priority and the other user priorities in saturated networks. The simulation results show better network performance as well as lower energy consumption in the proposed MAC protocols compared to the IEEE 802.15.6 MAC protocol.

Due to the rapid increase in data traffic, one of the solutions provided by mobile operators is to operate Long Term Evolution (LTE) in the unlicensed 5GHz band, as the licensed spectrum is becoming scarce. Mobile operators can expand their network capacity by operating LTE in the unlicensed band at lower cost when compared with using other licensed bands. Device to Device (D2D) communication, proven to be another effective way to enhance the capacity of a network, enables direct data exchange of localized traffic of users in proximity. Applying D2D communication to LTE unlicensed 5GHz band will further improve the network performance and user experience. In this article, we will discuss the new type of solutions that have been proposed for LTE operating in an unlicensed 5GHz band that includes; LTE-Unlicensed (LTE-U), LTE-License Assisted Access (LTE-LAA), LTE WiFi Link Aggregation (LWA), and MuLTEfire. We will discuss the important features along with their advantages and disadvantages and compare these technologies as well. We simulate LTE-LAA, LWA and MuLTEfire technologies in the presence of Wi-Fi hotspot and compare their results. Furthermore, we apply D2D communication to these technologies and from the results we conclude that MuLTEfire can increase the throughput drastically but network saturates quickly. Whereas, applying D2D communication with LWA is beneficial for a scalable network as it will not only increase the network throughput but will increase the network capacity as well.

The CORNER propagation model, first proposed in 2010, has been previously validated and found to be a reasonably accurate representation of propagation scenarios in urban Vehicular Ad Hoc Networks (VANETs). This paper considers the impact of the propagation environment on routing performance and reveals a pressing need to consider more accurate propagation models when designing urban VANET routing protocols. A greedy routing protocol, which uses CORNER's propagation estimates for neighbour selection, is then presented. The new protocol, named Corner Propagation Stateless Routing (CPSR) is compared to GPSR, a benchmark protocol for VANETs, showing between 87% and 300% improvement in packet delivery ratio at higher network loads.

Cooperative retransmission can significantly improve link reliability over lossy and time-varying wireless links. However, comparing retransmission protocols is challenging, and generally requires simplistic assumptions specific to each protocol. In this paper, we develop a general model to evaluate cooperative retransmission protocols with distributed, slot-based contention algorithms. Specifically, we propose to calculate the relay time-out probabilities at a MAC time-slot scale, formulate retransmission outcomes as functions of the time-out probabilities, and derive the probability of a retransmission process for every data frame. We also propose a Markov extension of our model to characterise the dependency between retransmissions of multiple frames. This enables our model to analyse continuous retransmissions of successive frames. Validated by QualNet simulations, our model can analytically predict the probabilities of cooperative retransmissions with an accuracy of ±1%. As a result, direct comparisons between cooperative retransmission protocols become tangible, without implementing the full protocol in a state-based simulator.

In this paper, we propose a prediction algorithm for dynamic channel allocation amongst coexisting Wireless body area networks (WBANs). Variations in channel assignment due to mobility scenarios within each WBAN as well as the movement of WBANs towards each other is investigated. The proposed scheme is further optimized to allocate the optimum transmission time with synchronous and parallel transmissions such that interference is fully avoided. This reduces the number of interfering nodes and leads to better usage of the scarce limitation of resources in these networks, larger network lifetime, higher energy savings and higher throughput. In fact, the aim of this protocol is to mitigate interference along with maintaining minimum power consumption in order to maximize network lifetime and increase the spatial reuse and throughput of each WBAN. Simulation results show that our approach achieves a much higher spatial reuse using the smart spectrum allocation scheme for interference mitigation in collocated WBANs. We conduct extensive simulations for coexistence prediction in different mobility scenarios using the NS-2 simulator. Consequently, we demonstrate the efficiency of the proposed protocol in providing interference-free channel assignments and higher energy savings.

This paper presents a novel primitive for self-organization amongst multiple coexisting Wireless Body Area Networks (WBANs). It follows a biologically inspired approach based on the theory of pulse-coupled oscillators. Our proposal allows for coexisting WBANs to use delayed information from previous transmissions to adjust to a collision-free TDMA schedule amongst each other for future communications. Most importantly, it does not require a global coordinator as all nodes achieve synchronization in a completely self-organized manner. Simulation results show that our protocol achieves a significantly fast convergence time despite little information from its coexisting networks. Moreover, the proposed approach is shown to be robust to variations in channel conditions, density of sensor nodes within each network and the number of coexisting WBANs. We conduct extensive simulations to evaluate the efficiency of the proposed protocol using the NS-2 simulator.

To maximize power transfer for inductively charging electric vehicles (EVs), charger and battery coils must be aligned. Wireless sensors can be installed to estimate misalignments; however, existing ranging techniques cannot satisfy the precision requirements of the misalignment estimation. We propose a high-precision wireless ranging and misalignment estimation scheme, where high precision is achieved by iteratively measuring, estimating, and aligning the coils. Another key aspect is to convert the nonconvex misalignment estimation to a more tractable problem with a convex objective. We develop a conditional gradient descent method to solve the problem, which performs gradient descent (or conditional gradient descent on the boundary of the search space) and projects out-of-boundary points back into the space. Employing experimentally validated models, we show that our scheme can achieve 92% of the efficiency of perfectly aligned coils in 90% of operations, and tolerate correlated distance measurement errors. In contrast, the prior art is susceptible to correlation, undergoing a significant efficiency degradation of 18.5%.

This paper proposes a novel adaptive internetwork interference mitigation scheme, namely AIM, for environments with multiple coexisting Wireless Body Area Networks (WBANs). The proposed scheme, operating on a nodes' traffic priority, packet length, signal strength and density of sensors in a WBAN, makes three major contributions as compared to the current literature. Firstly, it considers node-level interference for internetwork interference mitigation rather than considering each WBAN as a whole. Secondly, it allocates synchronous and parallel transmission intervals for interference avoidance in an optimal manner. Finally, it significantly reduces the number of orthogonal channels assigned to achieve a higher throughput as well as better usage of the scarce limitation of resources in WBANs. Simulation results show that our protocol achieves a significantly higher spatial reuse compared to existing approaches for interference mitigation in WBANs.

A method of approximating the Rician K-Factor with considerations of the local human-built environment is proposed for urban VANETs. The model is validated experimentally on a busy street in Australia, in the presence and absence of other vehicles. The model is found to accurately predict actual channel measurements in close-range communications scenarios.

In this paper, a dynamic resource allocation scheme is proposed to avoid interference amongst coexisting Wireless Body Area Networks (WBAN). In the proposed scheme, each WBAN generates a table consisting of interfering nodes from coexisting WBANs in its vicinity. Then each WBAN broadcasts this table to its neighbors, which allows for efficient interpretation of an Interference Region (IR) between each pair of WBANs. The nodes in the IR are later allocated orthogonal sub-channels; whilst nodes that do not exist in the IR can potentially transmit in the same time interval. We further demonstrate a precise tradeoff between the minimum interference level and spatial reuse. Simulation results show that our proposed scheme has far better spectral efficiency compared to the conventional orthogonal schemes, whilst maintaining an acceptable interference level. We also provide mathematical analysis on the proposed scheme to validate its efficiency for increasing spectral efficiency and avoiding interference. To further reduce the interference level, we propose a probabilistic approach, and analytically show that the outage probability can be effectively reduced at the cost of very small change in the spatial reuse factor.

In this paper, we derive the random coding error exponent of amplify-and-forward (AF) relay networks in presence of arbitrary number of independent and identically distributed (i.i.d.) interferers both at the relay and the destination. Multiuser networks are common examples of interference limited networks. We derive the ergodic capacity of the network and present simulation results on the performance of the network where we compare the capacity and error exponent performance of interference limited networks with noise limited networks. Numerical results show that noise limited networks outperform interference limited networks even when only a very few interferers exist in the network.

This is a simulation study of weight-based and precedence-based clustering paradigms in VANETs under an experimentally-derived channel model. The study reveals that CH election schemes accounting for driver intention form more stable and long-lived clusters. The results also show that ignoring elements of the VANET channel (such as vehicular shadowing) results in an unreliable comparative analysis of protocol performance.

In this paper, a hybrid scheme incorporating graph coloring and cooperative scheduling schemes is proposed for interference mitigation amongst coexisting wireless body area networks (WBANs). The proposed approach pairs every two WBANs into a cluster and uses cooperative scheduling amongst the pairs in each cluster to minimize interference. A color based approach is used to allocate different colors to coexisting WBANs in a manner such that none of the two interfering WBANs have the same color. Simulation results show that our proposed scheme has far better spatial reuse when compared to the fully color-based scheme. We also provided theoretical analysis of our proposed scheme to validate its efficiency in avoiding interference and increasing spatial reuse.

Cooperative retransmission schemes can significantly improve transmission reliability and performance over high loss and time-varying links. However, analytically comparing performance between retransmission strategies is challenging and generally requires simplistic assumptions. This paper presents a general model for the performance of distributed, slot-based contention algorithms for opportunistic decode and forward retransmission algorithms. The model is independent of specific modulation or coding schemes and may be adapted to suit state-based transmission probability models. The model is validated through QualNet simulations.

In this paper we analyze the outage performance of a multihop cooperative relay network where relays in the system can change positions dynamically and use all possible links to forward the message to the next hop over Rayleigh fading channels. We derive the general closed form expression of outage probability and asymptotic coding gain of the network.

In this paper, a novel cooperative transmission scheme via network coding has been proposed for Wireless Body Area Networks (WBANs) to enhance reliability and throughput. In the proposed scheme, namely Random XOR Network Coding (RXNC), each relay demodulates the received signal from each sensor node and then selects d different coded symbols amongst them and XORs them to generate a network coded symbol. We have found the optimum value of d through an analytical approach by minimizing the probability that an XOR network coded symbol is incorrectly generated. Simulation results show that the proposed RXNC scheme outperforms the no-cooperation and conventional bitwise network coding schemes in all channel signal to noise ratios (SNRs) from 0 dB to 18 dB.

In this paper, we propose a practical network coding approach for wireless body are networks (WBANs) using decode-and-forward relays. In this scheme, namely decode and forward-network coding (DF-NC), each relay linearly combines different messages from different sources to generate one message, and then transmits that message to the destination. Each relay node in DF-NC requires only one transmission time slot to forward its message. Thus, in this approach, energy usage at each relay is minimized compared to existing cooperative schemes without network coding, which require Nstime slots per relay for relay transmissions; where Nsis the number of source nodes. Simulation results show that the proposed DF-NC scheme can achieve near optimal outage probability while minimizing the number of transmissions per node, maximizing the energy efficiency of WBANs, and minimizing the delay.

In this paper we analyze the error performance of a cooperative multihop parallel relay network over Nakagami-m fading channels using M-ary Phase-shift keying (MPSK) modulation. We derive the general closed form expression of the symbol error probability (SEP) and present numerical results on the performance of the network.

In harsh and hostile environments, swift relocation of currently deployed nodes in the absence of centralized paradigm is a challenging issue in WSNs. Reducing the burden of centralized relocation paradigms by the distributed movement models comes at the price of unpleasant oscillations and excessive movements due to nodes' local and limited interactions. If the nodes' careless movements in the distributed relocation models are not properly addressed, their power will be exhausted. Therefore, in order to exert proper amount of virtual radial/angular push/pull forces among the nodes, a fuzzy logic relocation model is proposed and by considering linear combination of the presented performance metric(s)(i.e. coverage, uniformity, and average movement), its parameters are locally and globally tuned by particle swarm optimization(PSO). In order to tune fuzzy parameters locally and globally, PSO benefits respectively from nodes' neighbours within different ranges and all the given deployed area. Performance of locally and globally tuned fuzzy relocation models is compared with one another in addition to the distributed self-spreading algorithm (DSSA). It is shown that by applying PSO to the linear combinations of desired metric(s) to obtain tuned fuzzy parameters, the relocation model outperforms and/or is comparable to DSSA in one or more performance metric(s).

CORNER is an urban propagation model which simulates the presence of buildings in city scenarios and models radio propagation as a series of reflections and diffractions around buildings. CORNER was validated in the original publication with a series of packet-delivery-ratio measurements. However, the accuracy of these measurements is limited by interference from nearby networks. This paper independently evaluates the CORNER model using signal strength measurements across three separate sites in Sydney and Wollongong. The measurements are analysed and compared with the predicted analytical estimates. The fading model is also analysed with direct measurements. A new CORNER link classification algorithm is also proposed in this paper.

Research on routing in a network of intelligent, lightweight, micro and nano-technology sensors deployed in or around the body, namely Body Area Network (BAN), has gained great interest in the recent years. In this paper, we present an energy efficient, thermal and power aware routing algorithm for BANs named Energy Efficient Thermal and Power Aware routing (ETPA). ETPA considers a node's temperature, energy level and received power from adjacent nodes in the cost function calculation. An optimization problem is also defined in order to minimize average temperature rise in the network. Our analysis demonstrates that ETPA can significantly decrease temperature rise and power consumption as well as providing a more efficient usage of the available resources compared to the most efficient routing protocol proposed so far in BANs, namely PRPLC. Also, ETPA has a considerably higher depletion time that guarantees a longer lasting communication among nodes.

Accurate modelling of the radio channel is often the most difficult aspect of a Vehicular Ad Hoc Network (VANET) simulation due to the large variability present in vehicular terrain. CORNER is a propagation model that calculates path-loss in an urban terrain with a large concentration of buildings, based on the position of the transmitter and receiver on a street map. This paper proposes additions to the CORNER propagation model to take selective multi-path fading into account and investigates the performance of the GPSR routing protocol under the CORNER propagation model in a realistic city environment.

Each node in a Body Area Network (BAN) needs to be assigned with a free IP address before it may participate in any sort of communication. This paper evaluates the performance of an IP address allocation scheme, namely Prophet allocation to be used for BANs. This allocation scheme is a fully decentralized addressing scheme which is applicable to BANs as it provides low latency, low communication overhead and low complexity. Relative theoretical analysis and simulation experiments have also been conducted to demonstrate its benefits which also represent the reason for the choice of this allocation scheme. It also solves the issues related to network partition and merger efficiently.

Physical damage and/or node power exhaustion may lead to coverage holes in WSNs. Coverage holes can be directly detected by certain proximate nodes known as boundary nodes (B-nodes). Due to the sensor nodes' redundant deployment and autonomous fault detection, holes are surrounded by a margin of B-nodes (MB-nodes). If all B-nodes in the margin take part in the hole recovery processes, either by increasing their transmission power or by relocating towards region of interest (ROI), the probability of collision, interference, disconnection, and isolation may increase affecting the rest of the network's performance and QoS. Thus, distributed boundary node selection algorithms (BNS-Algorithms) are proposed to address these issues. BNS-algorithms allow B-nodes to self-select based on available 1-hop information extracted from nodes' simple geometrical and statistical features. Our results show that the performance of the proposed distributed BNS-algorithms approaches that of their centralized counterparts.

Opportunistic cooperation promises to enhance the user experience when streaming media over wireless devices by improving wireless network reliability at the link level. This paper presents DAFMAC, an efficient cooperative diversity partner selection algorithm for IEEE 802.11 devices. Simulation results show DAFMAC provides a significantly higher transmission reliability in poor channel conditions than traditional ARQ techniques without modifying the device hardware. Further analysis shows the low overhead of DAFMAC makes it highly competitive with other proposed cooperative retransmission mechanisms in an ad-hoc network.

In this paper we analyze the outage probability of a cooperative multihop parallel relay network in Nakagami-m fading channels. The general closed form expression of the outage probability is derived both for integer and arbitrary Nakagami parameter m. We present numerical results on the performance of the network. It shows a careful configuration of the network size and power sharing between nodes can ensure optimal outage performance in the network.

In this paper we focus on the subcarrier allocation for the uplink OFDMA based cooperative relay networks. Multiple cells were considered, each composed of a single base station (destination), multiple amplify and forward (AF) relay stations and multiple subscriber stations (sources). The effects of inter-cell interference (ICI) have been considered to optimize the subcarrier allocation with low complexity. The optimization problem aims to maximize the sum rate of all sources and at the same time maintain the fairness among them. Full channel state information (CSI) is assumed to be available at the base station. In the proposed algorithm the subcarrier allocation is performed in three steps; firstly the subcarriers are allocated to the Relay Stations (RSs) by which the received ICI on each RS is minimized. Then, the pre-allocated subcarriers are allocated to subscribers to achieve their individual rate requirements. Finally the remaining subcarriers are allocated to subscribers with the best channel condition to maximize the total sum of their data rates. The results show that the proposed algorithm significantly reduces the complexity with almost the same achievable rate of the optimal allocation in a single cell case. In case of multi-cell, the proposed algorithm outperforms the conventional algorithm in terms of total network achievable data rate and overall network complexity.

This paper evaluates the performance of the IEEE 802.11 broadcast traffic under both saturation and non- saturation conditions. The evaluation highlights some important characteristics of IEEE 802.11 broadcast traffic as compared to corresponding unicast traffic. Moreover, it underlines the inaccuracy of the broadcast saturation model proposed by Ma and Chen due to the absence of backoff counter freeze process when channel is busy. Computer simulations are used to validate the accuracy of the new model and demonstrate the importance of capturing the freezing of backoff counter in the analytical study of IEEE 802.11 broadcast.

Over the years, a considerable research effort has been applied to the design of ad hoc network routing protocols. However, there is still a lack of understanding of the subtle interactions between routing protocols and lower layers in the protocol stack. In this paper, the instability which may arise when reactive routing protocols interact with the IEEE 802.11 MAC protocol is investigated. In particular, several erratic behaviours of the Ad hod On-demand Distance Vector (AODV) routing protocol in a congested IEEE 802.11 ad hoc network are demonstrated. A cross-layer solution is proposed based on an Adaptive Bulk Trigger policy and a Dynamic Window Selection scheme. Simulation studies are presented which show that the proposed solution is effective in alleviating erratic behaviour of AODV and improving the end-to-end path stability.

This paper present a new routing protocol for Ad hoc networks, called On-demand Tree-based Routing Protocol (OTRP). This protocol combines the idea of hop-by-hop routing such as AODV with an efficient route discovery algorithm called Tree-based Optimized Flooding (TOF) to improve scalability of Ad hoc networks when there is no previous knowledge about the destination. To achieve this in OTRP, route discovery overheads are minimized by selectively flooding the network through a limited set of nodes, referred to as branching-nodes. The theoretical analysis and simulation results showed that OTRP outperforms AODV, DYMO, and OLSR and it reduces overheads as number of nodes and traffic increase.

The capacity and multi-hopping performance of ad hoc mesh networks in dynamic environment still remains an open research issue. Previous theoretical studies suggest that they do not scale in densely distributed networks. However, a study has shown that scalability and hence the multi- hopping capacity of mesh network is not only bound by the number of nodes in the network but also the number of hops [3]. In this paper we investigate the performance of multi- hop ad hoc mesh networks, using both simulation studies and an experimental test-bed, and monitor the performance of the network as the number of hops in the network increases. Our results show that the drop in performance in multi-hopping is much more significant when the traffic levels are high. Furthermore our test-bed study shows that ad hoc mesh networks can maintain high levels of packet delivery and throughput when traffic levels are low, however, the delay experienced continues to increase after each hop.

This paper presents a number of different route discovery strategies for on-demand routing protocols, which provide more control to each intermediate node make during the route discovery phase to make intelligent forwarding decisions. This is achieved through the idea of self-selection. In self-selecting route discovery each node independently makes route request (RREQ) forwarding decisions based upon a selection criterion or by satisfying certain conditions. The nodes which do not satisfy the selection criterion do not rebroadcast the routing packets. We implemented our self-selecting route discovery strategies over AODV using the GloMoSim network simulation package, and compared the performance with existing route discovery strategies used in AODV. Our simulation results show that a significant drop in the number of control packets can be achieved by giving each intermediate node more authority for self-selection during route discovery. Furthermore, a significant increase in throughput is achieved as the number nodes in the network is increased

This paper presents a new routing strategy for mobile ad hoc networks, called dynamic zone-based topology routing protocol (DZTR). We introduce new strategies to maintain up-to-date intrazone and interzone topology information at each node. We also propose a GPS-based location tracking mechanism, which reduces route discovery area and the number of nodes queried to find the required destination. Our routing strategy has been designed to work with a dynamic zone, which contains a set of member nodes. Every node outside a zone is called a single-state node. We perform theoretical performance analysis, which shows that our network topology creation process has significantly fewer overheads than flooding approaches.