Power adjustment and scheduling in OFDMA femtocell networks

Densely-deployed femtocell networks are used to enhance wireless coverage in public spaces like office buildings, subways, and academic buildings. These networks can increase throughput for users, but edge users can suffer from co-channel interference, leading to service outages. This paper introduces a distributed algorithm for network configuration, called Radius Reduction and Scheduling (RRS), to improve the performance and fairness of the network. RRS determines cell sizes using a Voronoi-Laguerre framework, then schedules users using a scheduling algorithm that includes vacancy requests to increase fairness in dense femtocell networks. We prove that our algorithm always terminate in a finite time, producing a configuration that guarantees user or area coverage. Simulation results show a decrease in outage probability of up to 50%, as well as an increase in Jain's fairness index of almost 200%

Sensor Activation and Radius Adaptation (SARA) in Heterogeneous Sensor Networks

In order to prolong the lifetime of a wireless sensor network (WSN) devoted to monitoring an area of interest, a useful means is to exploit network redundancy, activating only the sensors that are strictly necessary for coverage and making them work with the minimum necessary sensing radius. In this article, we introduce the first algorithm that reduces sensor coverage redundancy through joint Sensor Activation and sensing Radius Adaptation (SARA) in general application scenarios comprising two classes of devices: sensors with variable sensing radius and sensors with fixed sensing radius. This device heterogeneity is explicitly addressed by modeling the coverage problem through Voronoi-Laguerre diagrams that, differently from Voronoi diagrams, allow for correctly identifying each sensor coverage region depending on the sensor current radius and the radii of its neighboring nodes. SARA executes quickly with guaranteed termination and, given the currently available nodes, it always guarantees maximum coverage. By means of extensive simulations, we show that SARA obtains remarkable improvements with respect to previous solutions, ensuring, in networks with heterogeneous nodes, longer network lifetime and wider coverage

Deployment Strategies for Target Monitoring and Coverage Improvement in Mobile Sensor Networks

Efficient sensor deployment strategies are developed in this work for target monitoring and coverage improvement in collaborative wireless mobile sensor networks. The objective of the target monitoring problem is to compute the desired sensing and communication radii of sensors as well as their location at every time instant such that a set of prescribed specifications such as connectivity preservation and low energy consumption are satisfied. An energy-efficient strategy is also proposed for tracking a moving target in a sensing field, using a grid of sufficiently small rectangular cells. The grid is converted to a graph with properly weighted edges. A shortest-path algorithm is subsequently used to route information from target to destination by a subset of sensors. In the problem of coverage improvement in mobile sensor networks, on the other hand, the objective is to place each sensor in the field using available local information about its neighbors in such a way that the area covered by sensors is as large as possible, while some important criteria are taken into consideration. Both cases of identical and nonidentical sensors (in terms of sensing radii) are considered, and different iterative algorithms are developed which are shown to be convergent. The relocation algorithms are based on the relative position of each sensor w.r.t. the boundaries of its cell or the corresponding corner point. The algorithms are extended to the case of limited communication range of sensors (leading to inaccurate Voronoi cells), an environment with prioritized sensing (mathematically characterized by a weighting function for different points), and an environment with obstacles (leading to some invisible areas). Simulation results are provided to validate the effectiveness of the proposed algorithms