A heuristic tool for exposure reduction in indoor wireless networks

A heuristic indoor network planner for exposure calculation and optimization in wireless networks is developed. The model for the electric-field strength in the vicinity of an access point is presented and the WiFi networks are optimized in order not to exceed a maximal electric-field strength at a certain separation from the access points. The influence of the maximally allowed field strength and the assumed minimal separation between the access point and the human is assessed for a typical office building

Distributed optimization in wireless networks using broadcast advantage

In this paper, we consider cross layer optimization in wireless networks with wireless broadcast advantage, focusing on the problem of distributed scheduling of broadcast links. The wireless broadcast advantage is most useful in multicast scenarios. For a multicast scenario, we give a subgradient algorithm for distributed joint congestion control, network coding and session scheduling, which however requires centralized link scheduling. Under the primary interference model, link scheduling problem is equivalent to a maximum weighted hypergraph matching problem that is NP-complete. To solve the scheduling problem distributedly, locally greedy and randomized approximation algorithms are proposed and shown to have bounded worst-case performance. With random network coding, we obtain a fully distributed cross-layer design. Numerical results show promising throughput gain using the proposed algorithms, and surprisingly, in some cases even with less complexity than cross-layer design without broadcast advantage

Pareto Analysis and Multi-Objective Optimization in Wireless Networks

C

Cross-layer schemes for performance optimization in wireless networks

Wireless networks are undergoing rapid progress and inspiring numerous applications. As the application of wireless networks becomes broader, they are expected to not only provide ubiquitous connectivity, but also support end users with certain service guarantees. End-to-end delay is an important Quality of Service (QoS) metric in multihop wireless networks. This dissertation addresses how to minimize end-to-end delay through joint optimization of network layer routing and link layer scheduling. Two cross-layer schemes, a loosely coupled cross-layer scheme and a tightly coupled cross-layer scheme, are proposed. The two cross-layer schemes involve interference modeling in multihop wireless networks with omnidirectional antenna. In addition, based on the interference model, multicast schedules are optimized to minimize the total end-to-end delay. Throughput is another important QoS metric in wireless networks. This dissertation addresses how to leverage the spatial multiplexing function of MIMO links to improve wireless network throughput. Wireless interference modeling of a half-duplex MIMO node is presented. Based on the interference model, routing, spatial multiplexing, and scheduling are jointly considered in one optimization model. The throughput optimization problem is first addressed in constant bit rate networks and then in variable bit rate networks. In a variable data rate network, transmitters can use adaptive coding and modulation schemes to change their data rates so that the data rates are supported by the Signal to Noise and Interference Ratio (SINR). The problem of achieving maximum throughput in a millimeter-wave wireless personal area network is studied --Abstract, page iv

Cross-layer design for network performance optimization in wireless networks

In this dissertation, I use mathematical optimization approach to solve the complex network problems. Paper l and paper 2 first show that ignoring the bandwidth constraint can lead to infeasible routing solutions. A sufficient condition on link bandwidth is proposed that makes a routing solution feasible, and then a mathematical optimization model based on this sufficient condition is provided. Simulation results show that joint optimization models can provide more feasible routing solutions and provide significant improvement on throughput and lifetime. In paper 3 and paper 4, an interference model is proposed and a transmission scheduling scheme is presented to minimize the end-to-end delay. This scheduling scheme is designed based on integer linear programming and involves interference modeling. Using this schedule, there are no conflicting transmissions at any time. Through simulation, it shows that the proposed link scheduling scheme can significantly reduce end-to-end latency. Since to compute the maximum throughput is an NP-hard problem, efficient heuristics are presented in Paper 5 that use sufficient conditions instead of the computationally-expensive-to-get optimal condition to capture the mutual conflict relation in a collision domain. Both one-way transmission and two-way transmission are considered. Simulation results show that the proposed algorithms improve network throughput and reduce energy consumption, with significant improvement over previous work on both aspects. Paper 6 studies the complicated tradeoff relation among multiple factors that affect the sensor network lifetime and proposes an adaptive multi-hop clustering algorithm. It realizes the best tradeoff among multiple factors and outperforms others that do not. It is adaptive in the sense the clustering topology changes over time in order to have the maximum lifetime --Abstract, page iv

On distributed scheduling in wireless networks exploiting broadcast and network coding

In this paper, we consider cross-layer optimization in wireless networks with wireless broadcast advantage, focusing on the problem of distributed scheduling of broadcast links. The wireless broadcast advantage is most useful in multicast scenarios. As such, we include network coding in our design to exploit the throughput gain brought in by network coding for multicasting. We derive a subgradient algorithm for joint rate control, network coding and scheduling, which however requires centralized link scheduling. Under the primary interference model, link scheduling problem is equivalent to a maximum weighted hypergraph matching problem that is NP-complete. To solve the scheduling problem distributedly, locally greedy and randomized approximation algorithms are proposed and shown to have bounded worst-case performance. With random network coding, we obtain a fully distributed cross-layer design. Numerical results show promising throughput gain using the proposed algorithms, and surprisingly, in some cases even with less complexity than cross-layer design without broadcast advantage

A Genetic Algorithm-based Framework for Soft Handoff Optimization in Wireless Networks

In this paper, a genetic algorithm (GA)-based approach is used to evaluate the probability of successful handoff in heterogeneous wireless networks (HWNs) so as to increase capacity and network performance. The traditional handoff schemes are prone to ping pong and corner effects and developing an optimized handoff scheme for seamless, faster, and less power consuming handoff decision is challenging. The GA scheme can effectively optimize soft handoff decision by selecting the best fit network for the mobile terminal (MT) considering quality of service (QoS) requirements, network parameters and user’s preference in terms of cost of different attachment points for the MT. The robustness and ability to determine global optima for any function using crossover and mutation operations makes GA a promising solution. The developed optimization framework was simulated in Matrix Laboratory (MATLAB) software using MATLAB’s optima tool and results show that an optimal MT attachment point is the one with the highest handoff success probability value which determines direction for successful handoff in HWN environment. The system maintained a 90%  with 4 channels and more while a 75% was obtained even at high traffic intensity

A Tutorial on Cross-layer Optimization Wireless Network System Using TOPSIS Method

Each other, leading to issues such as interference, limited bandwidth, and varying channel conditions. These challenges require specialized optimization techniques tailored to the wireless environment. In wireless communication networks is to maximize the overall system throughput while ensuring fairness among users and maintaining quality of service requirements. This objective can be achieved through resource allocation optimization, where the available network resources such as bandwidth, power, and time slots are allocated to users in an optimal manner. Optimization-based approaches in wireless resource allocation typically involve formulating the resource allocation problem as an optimization problem with certain constraints.. These techniques provide practical solutions with reduced computational complexity, although they may not guarantee optimality. In summary, optimization-based approaches have been instrumental in studying resource allocation problems in communication networks, including the wireless domain. While techniques from the Internet setting have influenced the understanding of congestion control and protocol design, specific challenges in wireless networks necessitate tailored optimization techniques that account for interference, limited bandwidth, and varying channel conditions. power allocation problem in wireless ad hoc networks Cross-layer optimization refers to the process of jointly optimizing the allocation of resources across different layers of wireless networks, the interactions between different layers become more complex due to the shared medium and time-varying channel conditions.  Nash equilibrium, where no user can unilaterally improve its own performance by changing its strategy. Game theory can capture the distributed nature of wireless networks and provide insights into the behavior of users in resource allocation scenarios Additionally, heuristics and approximation algorithms are often employed in wireless resource allocation due to the complexity of the optimization problems involved. In traditional cellular systems, each user is allocated a fixed time slot for transmission, regardless of their channel conditions. However, in opportunistic scheduling. Alternative parameters for “Data rate Ž kbps, Geographic coverage ,  Service requirements , cost ” Evaluation parameter for “Circuit-switched cell, CDPD, WLAN, Paging, Satellite.” “the first ranking training is obtained with the lowest quality of compensation.