DSP IEEE 2018 Projects @ Chennai

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Thursday

CALL ADMISSION CONTROL OPTIMIZATION IN WIMAX NETWORKS

INTRODUCTION

Worldwide interoperability for microwave access (WiMAX) is a promising technology for last-mile Internet access, particularly in the areas where wired infrastructures are not available. In a WiMAX network, call admission control (CAC) is deployed to effectively control different traffic loads and prevent the network from being overloaded. In this paper, we propose a framework of a 2-D CAC to accommodate various features of WiMAX networks. Specifically, we decompose the 2-D uplink and downlink WiMAX CAC problem into two independent 1-D CAC problems and formulate the 1-D CAC optimization, in which the demands of service providers and subscribers are jointly taken into account. To solve the optimization problem, we develop a utility- and fairness-constrained optimal revenue policy, as well as its corresponding approximation algorithm.

THERE exist many regions in the world where wired infrastructures (i.e., T1, DSL, cables, etc.) are difficult to deploy for geographical or economic reasons. To provide broadband wireless access to these regions, many researchers advocate worldwide interoperability for microwave access (WiMAX), which is an IEEE 802.16 standardized wireless technology based on an orthogonal frequency-division multiplexing (OFDM) physical-layer architecture. To support a variety of applications, IEEE 802.16 has defined four types of service:
1) unsolicited grant service (UGS);
2) real-time polling service (rtPS);
3) non-real-time polling service (nrtPS); and
4) best effort (BE) service.

In a WiMAX network with heterogeneous traffic loads, it is essential to find a call admission control (CAC) solution that can effectively allocate bandwidth resources to different applications. In this Project, a proposed WiMAX CAC framework, which effectively meets all operational requirements of WiMAX networks. In this CAC framework, we decompose the 2-D uplink (UL) and downlink (DL) WiMAX CAC problem into two independent 1-D CAC problems. We further formulate the 1-D CAC as an optimization problem under a certain objective function, which should be chosen to maximize either the revenue of service providers or the satisfaction of subscribers.

With respect to 1-D CAC optimization problems, most previous studies were focused only on two approaches:
1) the optimal revenue strategy (also known as the stochastic knapsack problem) and
2) the minimum weighted sum of blocking strategy .

In this project, we will show that these two strategies are, in fact, equivalent. Therefore, we can mainly concentrate on the investigation of the optimal revenue strategy and view the minimum weighted sum of blocking strategy as the basis for fast calculation algorithms. Clearly, the optimal revenue policy only considers the profit of service providers. As an effort to conduct a multi objective study, in this paper, we will also take into account the requirements from WiMAX subscribers and develop a policy with a satisfactory tradeoff between service providers and subscribers.

The Project includes the following:
1) The development of a framework of CAC for WiMAX networks;
2) The investigation on various CAC optimization strategies; and
3) The proposal of a series of constrained greedy revenue algorithms for fast calculation. Through detailed performance evaluation, the study carried out in this paper will show that the proposed CAC solution can meet the expectations of both service providers and subscribers.

Modules:
  • CAC model for WiMAX networks
  • Calculate the UL and DL capacity
  • 1-D CAC optimization strategies and develop their corresponding approximation algorithms
The following parameters calculate using Greedy algorithm:
  • Utility Requirement
  • Fairness Requirement
  • Constrained Optimal Revenue Strategy

Simulation graphs:
  • Traffic arrival vs Revenue
  • Traffic arrival vs Utility
  • Blocking probability vs Traffic arrival

VIDEO DEMO

1 comment:

prasanth said...

how could i see the entire project work