Distributed Throughput Maximization in Wireless Networks via Random Power Allocation

ABSTRACT:
We develop a distributed throughput-optimal power allocation algorithm in wireless networks. The study of this problem has been limited due to the non-convexity of the underlying optimization problems that prohibits an efficient solution even in a centralized setting. By generalizing the randomization framework originally proposed for input queued switches to SINR rate-based interference model, we characterize the throughput-optimality conditions that enable efficient and distributed implementation. Using gossiping algorithm, we develop a distributed power allocation algorithm that satisfies the optimality conditions, thereby achieving (nearly) 100 percent throughput. We illustrate the performance of our power allocation solution through numerical simulation.

EXISTING SYSTEM:
The most of the existing works in the literature consider a simple setting where all nodes in the network use fixed transmission power levels and the resource allocation problem degenerates into simply a link scheduling problem. Furthermore, the link scheduling problem has been mostly studied assuming a simplistic graph-based interference model.



DISADVANTAGES OF EXISTING SYSTEM:
RESOURCE allocation in multi-hop wireless networks involves solving a joint link scheduling and power allocation problem which is very difficult in general.

PROPOSED SYSTEM:
In every time slot, the randomization framework does the following:

1. RAND-SCH: generate a new random schedule,

2. DECIDE: decide on the current schedule by comparing and selecting the better of the new and old schedules (i.e., the one with higher weight)

We present a power allocation policy RAND-POW that satisfies C1, i.e., finds with positive probability a power vector within a small factor of the optimal value.

ADVANTAGES OF PROPOSED SYSTEM:
We considered the problem of achieving maximum throughput under SINR rate-based model in multi-hop wireless networks.

By applying randomization approach, we characterized new throughput-optimality conditions that enable distributed implementation. We developed a randomized power allocation that satisfies the new optimality conditions, and a distributed gossip-based comparison mechanism that achieves 100 percent throughput, together with the randomized power allocation.

MODULES:
ü Network Construction Module

ü SINR rate based interference model

ü Randomized Power Control Framework

ü Wireless Network Simulation Module


MODULE DESCRIPTION:

Network Construction Module

In fact, the resource allocation problem has been considered mainly in two different network settings. The first setting is a static one which does not take randomness in the traffic arrival processes into consideration. In particular, it is usually assumed that users either have unlimited amount of traffic to transmit or have predetermined traffic demands. Here, resource allocation aims at achieving fair share of resource among competing traffic flows or developing resource allocation algorithms which have nice performance properties (e.g., constructing minimum length schedule to support a traffic demands). The second setting assumes random arrival traffic and one of the main objectives of the resource allocation problem is to maximize the average arrival rates which can be supported while maintaining network stability.


SINR rate based interference model

In this module, we assume a SINR rate-based interference model where the transmission rate of a link is given as a continuous function of its SINR. To the best of our knowledge, there is no known work that assumes the SINR rate-based interference model and solves the throughput optimal power control problem in the stability framework. SINR rate-based interference model will be as follows: first, in each time slot t, the nodes generate a new random power allocation vector, denoted by ~pðtÞ, in a distributed manner. Second, the current power vector pðtÞ is selected by comparing the new power vector

Randomized Power Control Framework

In this module, we implement the following algorithm:

Algorithm 1:
Randomized Power Control Framework (for each time slot t)
1. RAND-POW: Generate a new random power allocation vector ~pðtÞ in a distributed manner.

2. DECIDE: Determine the current power allocation pðtÞ by comparing the previous power allocation pðt _ 1Þ and the new power allocation ~pðtÞ, and selecting the one with higher weight



Wireless Network Simulation Module
In this module we develop a simulator for Wireless Networks which shows the simulation features and power values. We generated a network topology by randomly placing N nodes in a plane. For each link ða; bÞ, packets arrive according to a Poisson arrival process of rate 0.5, with the mean packet size of 2_. The offered load is thus, and this parameter will be changed to examine the algorithm performance.

HARDWARE REQUIREMENTS

•                     SYSTEM             : Pentium IV 2.4 GHz
•                     HARD DISK        : 40 GB
•                     FLOPPY DRIVE  : 1.44 MB
•                     MONITOR           : 15 VGA colour
•                     MOUSE               : Logitech.
•                     RAM                    : 256 MB
•                     KEYBOARD       : 110 keys enhanced.

SOFTWARE REQUIREMENTS

•                     Operating system           :-  Windows XP Professional
•                     Front End             :-  Microsoft Visual Studio .Net 2008
•                     Coding Language : - C# .NET.


REFERENCE:
Hyang-Won Lee, Member, IEEE, Eytan Modiano, Fellow, IEEE, and Long Bao Le, Member, IEEE, “Distributed Throughput Maximization in Wireless Networks via Random Power Allocation”, IEEE TRANSACTIONS ON MOBILE COMPUTING, VOL. 11, NO. 4, APRIL 2012.