Deployment Of Wireless Networks Research Articles

Bound-based power optimization for multi-hop heterogeneous wireless industrial networks under statistical delay constraints

The noticeably increased deployment of wireless networks for battery-limited industrial applications in recent years highlights the need for tractable performance analysis methodologies as well as efficient QoS-aware transmit power management schemes. In this work, we seek to combine several important aspects of such networks, i.e., multi-hop connectivity, channel heterogeneity and the queuing effect, in order to address these needs. We design delay-bound-based algorithms for transmit power minimization and network lifetime maximization of multi-hop heterogeneous wireless networks using our previously developed stochastic network calculus approach for performance analysis of a cascade of buffered wireless fading channels. Our analysis shows an overall transmit power saving of up to 95% compared to a fixed power allocation scheme in case when the service is modeled via a Shannon capacity. For a more realistic set-up, we evaluate the performance of the suggested algorithm in a WirelessHART network, which is a widely used communication standard for industrial process automation applications. We find that link heterogeneity can significantly reduce network lifetime when no efficient power management is applied. Using extensive simulation study we further show that the proposed bound-based power allocation performs reasonably well compared to the real optimum, especially in the case of WirelessHART networks.

Mobile Learning Technologies

<p>Technological development have altered the way we communicate, learn, think, share, and spread information. Mobile technologies are those that make use of wireless technologies to gain some sort of data. As mobile connectedness continues to spread across the world, the value of employing mobile technologies in the arena of learning and teaching seems to be both self-evident and unavoidable The fast deployment of mobile devices and wireless networks in university campuses makes higher education a good environment to integrate learners-centered m-learning . this paper discusses mobile learning technologies that are being used for educational purposes and the effect they have on teaching and learning methods.</p>

Generalized carrier to interference ratio analysis for shotgun cellular systems in multiple dimensions over composite Rayleigh–Lognormal (Suzuki) fading

This paper analyzes the carrier-to-interference ratio (CIR) of the so-called shotgun cellular systems (SCSs) in $$\tau $$ dimensions ( $$\tau =1, 2,$$ and 3). SCSs are wireless communication systems with randomly placed base stations (BSs) over the entire plane according to a Poisson point process in $$\tau $$ dimensions. Such a system can model a dense cellular or wireless data network deployment, where locations of BSs end up being close to random due to constraints other than optimal coverage. In this paper we apply SCSs in $$\tau $$ dimensions and also, in addition to path-loss and shadow fading, consider Rayleigh fading as a most commonly used distribution to model multi-path fading, and analyze the CIR over the composite fading channel [i.e., Rayleigh–Lognormal (or Suzuki) fading channel], and determine a generalized expression for the distribution of CIR and obtain the tail probability of CIR.

Optimal Base Station Deployment with Downlink Rate Coverage Probability Constraint

The uncertainty in user locations and channel conditions makes the deployment and performance analysis of wireless networks challenging. Stochastic geometry has emerged as a powerful tool for analyzing the performance of wireless networks, assuming certain stochastic models for the distribution of both users and base stations (BSs). In this letter, seeking further precision, we derive the downlink rate coverage probability of a wireless network with deterministically known BS locations . Then, we use this result to optimize the placement of BSs while keeping the downlink rate coverage probability above a certain threshold.

A game theoretical approach to model the channel selection dynamics in non-coordinated IEEE 802.11 networks

The massive deployment of Wireless Local Area Networks has made interference mitigation between neighboring networks a challenging issue. These uncoordinated access networks aim at improving their operation by choosing the best wireless channel available, characterizing a competition over the restricted set of possible channels. This work analyses this competition using Game Theory and Markov Chains models, showing that such competitive behavior can lead to Nash Equilibria and that outcomes mostly will not be maximal. Additionally, partially and fully cooperative models are proposed and evaluated, allowing (a) individual players to increase global results using arbitrarily computed and non-rational moves, and (b) achieving maximal outcomes when considering the cooperation of up to all players.

Carrier to interference ratio analysis in shotgun cellular systems over a generalized shadowing distribution

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.

Asynchronous Stochastic Approximation Based Learning Algorithms for As-You-Go Deployment of Wireless Relay Networks Along a Line

We are motivated by the need, in emergency situations, for impromptu (or “as-you-go”) deployment of multihop wireless networks, by human agents or robots (e.g., unmanned aerial vehicles (UAVs)); the agent moves along a line, makes wireless link quality measurements at regular intervals, and makes on-line placement decisions using these measurements. As a first step, we have formulated such deployment along a line as a sequential decision problem. In our earlier work, reported in [1] , we proposed two possible deployment approaches: (i) the pure as-you-go approach where the deployment agent can only move forward, and (ii) the explore-forward approach where the deployment agent explores a few successive steps and then selects the best relay placement location among them. The latter was shown to provide better performance (in terms of network cost, network performance, and power expenditure), but at the expense of more measurements and deployment time, which makes explore-forward impractical for quick deployment by an energy constrained agent such as a UAV. Further, since in emergency situations the terrain would be unknown, the deployment algorithm should not require a-priori knowledge of the parameters of the wireless propagation model. In [1] , we, therefore, developed learning algorithms for the explore-forward approach. The current paper fills in an important gap by providing deploy-and-learn algorithms for the pure as-you-go approach. We formulate the sequential relay deployment problem as an average cost Markov decision process (MDP), which trades off among power consumption, link outage probabilities, and the number of relay nodes in the deployed network. While the pure as-you-go deployment problem was previously formulated as a discounted cost MDP (see [1] ), the discounted cost MDP formulation was not amenable for learning algorithms that are proposed in this paper. In this paper, first we show structural results for the optimal policy corresponding to the average cost MDP, and provide new insights into the optimal policy. Next, by exploiting the special structure of the average cost optimality equation and by using the theory of asynchronous stochastic approximation (in single and two timescale), we develop two learning algorithms that asymptotically converge to the set of optimal policies as deployment progresses. Numerical results show reasonably fast speed of convergence, and hence the model-free algorithms can be useful for practical, fast deployment of emergency wireless networks.

Modeling dense urban wireless networks with 3D stochastic geometry

Over the past decade, many works on the modeling of wireless networks using stochastic geometry have been proposed. Results about probability of coverage, capacity or mean interference, have been provided for a wide variety of networks (cellular, ad hoc, cognitive, sensors, etc.). These results notably allow to tune network protocol parameters. Nevertheless, in their vast majority, these works assume that the wireless network deployment is flat: nodes are placed on the Euclidean plane. However, this assumption is disproved in dense urban environments where many nodes are deployed in high buildings. In this paper, we derive the exact form of the probability of coverage for the cases where the interferers form a 3D Poisson Point Process (PPP) and an approximation for the 3D Modified Matern Process (MMP). We compare the 3D model with the 2D model and with simulation results. We comment the adequacy of each model depending on the parameters of the nodes (emission power, reception threshold, MAC protocol, etc.) and the height of the buildings in the simulations.

Multiple Access for Visible Light Communications: Research Challenges and Future Trends

The ever-increasing demand of mobile Internet and multimedia services poses unique and significant challenges for current and future generation wireless networks. These challenges are mainly related to the support of massive ubiquitous connectivity, low latency, and highly efficient utilization of spectrum resources. Therefore, it is of a paramount importance to address them in the design and deployment of future wireless networks. To this end, this paper provides a comprehensive overview of multiple access schemes in the context of visible light communications (VLC). Specifically, we initially provide a thorough overview of frequency-domain multiple access techniques for single- and multi-carrier systems, which is then followed by an in-depth discussion on the technical considerations of optical code-division multiple access techniques and their adoption in indoor VLC applications. Furthermore, we address space-division multiple access and, finally, we revisit and analyze a new promising technology, namely, non-orthogonal multiple access (NOMA). It is shown that NOMA exhibits significant benefits in VLC systems that can outperform conventional multiple access schemes, rendering it a particularly effective solution. Furthermore, it is demonstrated that it can coexist with the above optical multiple access schemes, which can maximize the performance and efficiency of future VLC systems. However, it is also shown that the potential of NOMA in VLC systems requires efficient addressing of a series of related challenges and constraints, such as fast and effective successive interference cancellation techniques, compensation and mitigation of LED non-linearity, and imperfect and/or outdated channel state information.

Exploring the Effect of Various Cluster Structures on Energy Consumption and End-to-End Delay in Cognitive Radio Wireless Sensor Networks

The growing demand and wide deployment of cost effective wireless communication networks, and the challenges related to its technical design and operations have necessitated the work on the more efficient use of the very limited radio frequency spectrum, limited energy resources and reduction of the end-to-end delay as an integral part of the next generation smart wireless networks. In this paper, we explore three different cognitive radio wireless sensor networks cluster structures; modified single-hop structure, multi-hop cluster structure, and hybrid cluster structure. We study the effect of the three structures in multiple setups in regards to varying the selected area. The evaluation results of the suggested three structures are compared with the single-hop cluster. Extensive simulation results carried out using MATLAB package showed that the end-to-end delay is minimum for the hybrid algorithm on the expense of a slight increase in energy consumption compared with the single-hop and the multi-hop cluster structures. On the other hand, the multi-hop cluster structure is more energy consuming than the single-hop, but it achieves a wider coverage area.

Collab-SAR: A Collaborative Avalanche Search-and-Rescue Missions Exploiting Hostile Alpine Networks

Every year, Alpine experiences a considerable number of avalanches causing danger to visitor and saviors, where most of the existing techniques to mitigate the number of fatalities in such hostile environments are based on a non-collaborative approach and is time- and effort-inefficient. A recently completed European project on Smart collaboration between Humans and ground-aErial Robots for imProving rescuing activities in Alpine environments (SHERPA) has proposed a novel collaborative approach to improve the rescuing activities. To be an integral part of the SHERPA framework, this paper considers deployment of an air-ground collaborative wireless network (AGCWN) to support search and rescue (SAR) missions in hostile alpine environments. We propose a network infrastructure for such challenging environments by considering the available network components, hostility of the environments, scenarios, and requirements. The proposed infrastructure also considers two degrees of quality of service, in terms of high throughput and long coverage range, to enable timely delivery of videos and images of the long patrolled area, which is the key in any searching and rescuing mission. We also incorporate a probabilistic search technique, which is suitable for collaborative search assuming AGCWN infrastructure for sharing information. The effectiveness of the proposed infrastructure and collaborative search technique, referred to as Collab-SAR , is demonstrated via a series of computer simulations. The results confirm the effectiveness of the proposal.

Micro Operator Design Pattern in 5G SDN/NFV Network

The trend of 5G mobile networks is increasing with the number of users and the transmission rate. Many operators are turning to small cell and indoor coverage of telecom network service. With the emerging Software Defined Networking and Network Function Virtualization technologies, Internet Service Provider is able to deploy their networks more flexibly and dynamically. In addition to the change of the wireless mobile network deployment model, it also drives the development trend of the Micro Operator (μO). Telecom operators can provide regional network services through public buildings, shopping malls, or industrial sites. In addition, localized network services are provided and bandwidth consumption is reduced. The distributed architecture of μO tackles computing requirements for applications, data, and services from cloud data center to edge network devices or to the micro data center of μO. The service model of μO is capable of reducing network latency in response to the low‐latency applications for future 5G edge computing environment. This paper addresses the design pattern of 5G micro operator and proposes a Decision Tree Based Flow Redirection (DTBFR) mechanism to redirect the traffic flows to neighbor service nodes. The DTBFR mechanism allows different μOs to share network resources and speed up the development of edge computing in the future.

Laplace Functional Ordering of Point Processes in Large‐Scale Wireless Networks

Stochastic orders on point processes are partial orders which capture notions like being larger or more variable. Laplace functional ordering of point processes is a useful stochastic order for comparing spatial deployments of wireless networks. It is shown that the ordering of point processes is preserved under independent operations such as marking, thinning, clustering, superposition, and random translation. Laplace functional ordering can be used to establish comparisons of several performance metrics such as coverage probability, achievable rate, and resource allocation even when closed form expressions of such metrics are unavailable. Applications in several network scenarios are also provided where tradeoffs between coverage and interference as well as fairness and peakyness are studied. Monte‐Carlo simulations are used to supplement our analytical results.

Updating Neighbour Cell List via Crowdsourced User Reports: A Framework for Measuring Time Performance

In modern wireless networks deployments, each serving node needs to keep its Neighbour Cell List (NCL) constantly up to date to keep track of network changes. The time needed by each serving node to update its NCL is an important parameter of the network’s reliability and performance. An adequate estimate of such parameter enables a significant improvement of self‐configuration functionalities. This paper focuses on the update time of NCLs when an approach of crowdsourced user reports is adopted. In this setting, each user periodically reports to the serving node information about the set of nodes sensed by the user itself. We show that, by mapping the local topological structure of the network onto states of increasing knowledge, a crisp mathematical framework can be obtained, which allows in turn for the use of a variety of user mobility models. Further, using a simplified mobility model we show how to obtain useful upper bounds on the expected time for a serving node to gain Full Knowledge of its local neighbourhood.

5G Wireless Networks Deployment with Emerging Technologies and Research Challenges

Over the last couple of decades the world has witnessed gradual, yet steady evolution of mobile wireless communications towards second, third and fourth generation wireless networks. Introduction of digital modulations, effective frequency reuse, penetration of packetbased Internet and rapid advancement in physical layer technologies. Currently all IP based 4G Long Term Evolution (LTE/4G) networks have become a part of everyday life. As a result, a set of new, user-oriented mobile multimedia applications, like mobile video conferencing, streaming video, e-healthcare and online gaming are coming up. These new applications are not only satisfying users’ requirements, but also opening up new business horizons for wireless operators to increase their revenue. Fifth generation mobile communications (5G) are expected to accommodate rapidly increasing mobile traffic aiming at the realization of a “Hyper Connected World” in which all people and surrounding things are connected and information is exchanged between them, and to play the role of a basis of the Internet of everything. The 5G wireless network is expected to become a “Heterogeneous Network” where new wireless access technologies incompatible with 4G and the wireless access technologies for unlicensed band are incorporated with the enhanced technology of 4G (e.g. IMT-advanced). This paper introduces the vision and emerging technology trends of 5G, shows key directions of the research challenges and development of 5G in the future.

Layered Group Sparse Beamforming for Cache-Enabled Green Wireless Networks

The exponential growth of mobile data traffic is driving the deployment of dense wireless networks, which will not only impose heavy backhaul burdens, but also generate considerable power consumption. Introducing caches to the wireless network edge is a potential and cost-effective solution to address these challenges. In this paper, we will investigate the problem of minimizing the network power consumption of cache-enabled wireless networks, consisting of the base station (BS) and backhaul power consumption. The objective is to develop efficient algorithms that unify adaptive BS selection, backhaul content assignment and multicast beamforming, while taking account of user QoS requirements and backhaul capacity limitations. To address the NP-hardness of the network power minimization problem, we first propose a generalized layered group sparse beamforming (LGSBF) modeling framework, which helps to reveal the layered sparsity structure in the beamformers. By adopting the reweighted $\left.\ell_{1}\right/\ell_{2}$-norm technique, we further develop a convex approximation procedure for the LGSBF problem, followed by a three-stage iterative LGSBF framework to induce the desired sparsity structure in the beamformers. Simulation results validate the effectiveness of the proposed algorithm in reducing the network power consumption, and demonstrate that caching plays a more significant role in networks with higher user densities and less power-efficient backhaul links.

Software Defined Network Service Chaining for OTT Service Providers in 5G Networks

The fifth generation wireless networks are expected to offer high capacity and accommodate numerous over-the-top applications, relying on users' Internet connectivity, thus involving different stakeholders, that is, network service providers and over-the-top service providers. For the efficient management of over-the-top application flows, the implementation of service functions and their interconnection in service chains, namely network service chaining, should consider the over-the-top service providers' performance goals and user management strategies. However, in current wireless network deployments, the network service providers have full control of network service chaining. Considering that user satisfaction from the offered services is a common interest for both types of stakeholders, the over-the-top service providers need to participate in network service chaining, and apply QoS and user prioritization policies to network service chain resource management, which involves users connected at different network points, in a distributed manner. In this article, we describe 5G network management architectures and propose virtualization components that enable over-the-top service-provider- oriented network service. We also outline the arising issues for over-the-top service providers in network service chaining and introduce a distributed prioritization network service chain management scheme for over-the-top application flows, based on matching theory. The evaluation results indicate the performance gains in overthe- top service providers' service levels that stem from the proposed scheme, demonstrating the benefits of introducing prioritization in network service chain deployment.

A Dynamical Relay node placement solution for MANETs

Network deployment in wireless networks implies the distribution of the communication nodes to improve some key operational aspects, such as energy saving, coverage, connectivity, or simply reducing the network cost. Most node placement approaches are focused on static scenarios like WSNs, where the topology of the network does not vary over time. Nevertheless, there exist certain situations in which the network node locations can continuously change. In this case, the use of special nodes, so-called Relay Nodes (RNs), contributes to supporting, maintaining or recovering communication in the network. The present work introduces a multi-stage dynamical RN placement solution to lead the RNs to their time-varying optimized positions. The approach, named Dynamical Relay Node placement Solution (DRNS), is based on the use of Particle Swarm Optimization (PSO) algorithms and is inspired by Model Predictive Control (MPC) techniques following a bi-objective optimization procedure, where both network connectivity and throughput are jointly maximized. DRNS is validated in both simulated and real environments composed of mobile robotic nodes, the results showing its goodness and operational suitability for real MANET environments.

Mobile Learning Technologies

<p>Technological development have altered the way we communicate, learn, think, share, and spread information. Mobile technologies are those that make use of wireless technologies to gain some sort of data. As mobile connectedness continues to spread across the world, the value of employing mobile technologies in the arena of learning and teaching seems to be both self-evident and unavoidable The fast deployment of mobile devices and wireless networks in university campuses makes higher education a good environment to integrate learners-centered m-learning . this paper discusses mobile learning technologies that are being used for educational purposes and the effect they have on teaching and learning methods.</p>

Evolutionary game-based cooperative strategy for effective capacity of multiple-input-multiple-output communications

Cooperative-relaying networks have great potential for deployment in next-generation wireless communication networks. However, a cooperative-relaying network using two-dimensional multiple-input-mu...