Probability In Wireless Networks Research Articles

Impact of Multi-Connectivity on Channel Capacity and Outage Probability in Wireless Networks

Multi-connectivity facilitates higher throughput, shorter delay, and lower outage probability for a user in a wireless network. Considering these promises, a rationale policy for a network operator would be to implement multi-connectivity for all of its users. In this paper, we investigate whether the promises of multi-connectivity also hold in such a setting where all users of a network are connected through multiple links. In particular, we consider a network where every user connects to its k closest base stations. Using a framework of stochastic geometry and probability theory, we obtain analytic expressions for per-user throughput and outage probability of $k$-connectivity networks under several failure models. In contrast to the conclusions of previous research, our analysis shows that per-user throughput decreases with increasing k. However, multi-connected networks are more resilient against failures than single connected networks as reflected with lower outage probability and lead to higher fairness among the users. Consequently, we conclude that rather than implementing multi-connectivity for all users, a network operator should consider it for its users who would benefit from additional links the most, e.g., cell edge users.

Reflection probability in wirelessnetworks with metasurface-coatedenvironmental objects: an approach basedon random spatial processes

Reflection probability in wirelessnetworks with metasurface-coatedenvironmental objects: an approach basedon random spatial processes

Reflection probability in wireless networks with metasurface-coated environmental objects: an approach based on random spatial processes

An emerging and promising vision of wireless networks consists of coating the environmental objects with reconfigurable metasurfaces that are capable of modifying the radio waves impinging upon them according to the generalized law of reflection. By relying on tools from point processes, stochastic geometry, and random spatial processes, we model the environmental objects with a modified random line process of fixed length and with random orientations and locations. Based on the proposed modeling approach, we develop the first analytical framework that provides one with the probability that a randomly distributed object that is coated with a reconfigurable metasurface acts as a reflector for a given pair of transmitter and receiver. In contrast to the conventional network setup where the environmental objects are not coated with reconfigurable metasurfaces, we prove that the probability that the typical random object acts as a reflector is independent of the length of the object itself. The proposed analytical approach is validated against Monte Carlo simulations, and numerical illustrations are given and discussed.

Estimating the Transmission Probability in Wireless Networks with Configuration Models

We propose a new methodology to estimate the probability of successful transmissions for random access scheduling in wireless networks, in particular those using Carrier Sense Multiple Access (CSMA). Instead of focusing on spatial configurations of users, we model the interference between users as a random graph. Using configuration models for random graphs, we show how the properties of the medium access mechanism are captured by some deterministic differential equations when the size of the graph gets large. Performance indicators such as the probability of connection of a given node can then be efficiently computed from these equations. We also perform simulations to illustrate the results on different types of random graphs. Even on spatial structures, these estimates get very accurate as soon as the variance of the interference is not negligible.

Analytical generalized results for handoff probability in wireless networks

We present analytical results for handoff probability for wireless networks under assumption that the call holding time and the cell residence time are all generally distributed. Easily computable formulas can be obtained for cases when the call holding time and cell residence time have rational Laplace transforms.

Event based resource estimation in admission control for wireless networks with heterogeneous traffic

A technique for estimating the resources needed to maintain an upper bound on handoff dropping probability in wireless networks with heterogeneous traffic is presented. The calculation is based on the number and characteristics of connections in the surrounding cells. The information is collected from the base stations in the S surrounding rings and is updated at handoff and call termination events which involves simple arithmetic operations only. Based on the resource requirement estimation, a distributed adaptive admission control algorithm is proposed. We have evaluated the performance of the admission algorithm for the single traffic type case and derived the performance bounds as functions of traffic descriptors, cell capacity and value of the tuning parameter. It is shown that by adjusting the tuning parameter, the constraints imposed on the handoff dropping probability for a given type of traffic can be met while maximizing the cell capacity utilization and minimizing the new call blocking probabilities.