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\title{Performance analysis of Call Admission Control algorithm for Wireless Multimedia networks}
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             \author[1]{S.P.V  Subbarao}

             \author[2]{Dr.D.Sreenivasa  Rao}

             \affil[1]{  JNTU}

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\date{\small \em Received: 31 March 2011 Accepted: 24 April 2011 Published: 5 May 2011}

\maketitle


\begin{abstract}
        


In todays wireless networks different wireless multimedia services have diverse bandwidth and QOS requirements, which need to be guaranteed by the wireless cellular networks. The decision to admit or reject the new user call is made by the call admission control algorithm.In this paper, a novel Call Admission Control algorithm for wireless cellular networks is proposed. The call admission control algorithm is based on power control. It determines the optimum number of admission users with optimum transmission power level so as to reduce the interference level and call blocking. By our simulation we show that our proposed call admission control algorithm reduces the blocking probability.

\end{abstract}


\keywords{Call admission control, W ireless Multimedia networks, call blocking probability, }

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\textcolor{GJBlue}{\footnotesize \\ Artificial Intelligence formulated this projection for compatibility purposes from the original article published at Global Journals. However, this technology is currently in beta. \emph{Therefore, kindly ignore odd layouts, missed formulae, text, tables, or figures.}}
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\let\tabcellsep& 	 	 		 
\section[{Introduction}]{Introduction}\par
he upcoming wireless cellular infrastructures such as third generation (3G) and fourth generation (4G) are deemed to support new high-speed services with different Quality-of-Service (QOS) and their respective traffic profiles. The advent of the third and fourth generation of wireless multimedia services brought about a need to adapt to the existing mobile cellular networks to make them carry various classes of multimedia traffic like voice, video, image, web documents, data or a combination thereof. achieve this goal, radio resource management techniques are used. These schemes include: channel assignment, power control, call admission control, congestion control, and other traffic-and-mobility-management schemes.\par
Call admission control algorithm plays a central role in determining both the performance of any network, and the revenue of the network. The call admission control algorithm must decide either to accept the call or reject it, thus having an impact on both the quality of calls and the network revenues. The call admission control algorithm must deal with multiple classes of calls having different requirements, for hand off request calls ,since handoffs are important then the new calls. The power of the existing users are degraded according to priorities Here non real time services are degraded first when compared with real time services which leads to reduced loss for real time services.Session III gives the detailed description of the proposed Ad-CAC algorithm along with its design approach. Session IV gives information about the simulation model and result analysis. SessionV concludes the Paper. 
\section[{II.}]{II.}\par
Related works \hyperref[b0]{[1]} The easiest and most simple admission control protocol is the First Come First Served (FCFS). If a request arrives and there is enough bandwidth to accommodate it, the call is admitted, otherwise rejected. FCFS produces a good utilization of the medium, but is biased against calls which require high bandwidth. Besides, it does not support prioritization because of which the hand-off calls cannot be distinguished from the new calls. \hyperref[b1]{[2]} In this method, the network is divided into cells. A new call is admitted only if the number of newly arriving calls is less than or equal to maximum number of calls that can be admitted in the cell .This type of threshold based algorithm does not give efficient bandwidth utilization in Multimedia Networks.\par
In \hyperref[b2]{[3]}\hyperref[b3]{[4]}\hyperref[b4]{[5]}\hyperref[b5]{[6]} the well-known Guard Channel Scheme and its variations have been proposed to give higher priority to handoff connections over new connections by reserving a number of channels called guard channels for handoff call connections. All these schemes are static. Moreover, only one traffic class, i.e., voice traffic, is considered.\par
In \hyperref[b6]{[7]} a Resource Reservation Estimation (RRE) methodology has been proposed. The RRE module that resides in the base station dynamically estimates the amount of bandwidth to be reserved by referencing the traffic conditions in the neighboring cells periodically or upon call request arrival depending upon the design of the system. But such a system is very complicated to design and may not assure reliability.\par
In \hyperref[b7]{[8]} a Bandwidth Partitioning Scheme has In \hyperref[b8]{[9]}, an optimal Bandwidth Adaptation Algorithm has been obtained, but with the assumption of the continuous value of bandwidth. The practical bandwidth values of Adaptive Multimedia are more likely to be discrete than continuous. 
\section[{III.}]{III.} 
\section[{Power Control and Adaptive call admission control algorithm}]{Power Control and Adaptive call admission control algorithm}\par
While describing the access system we take only one mobile cell into account in which there are M active nodes(or users) that generates messages to be transmitted to another node. In this network the base station controls all the nodes within the cell. Two kinds of links are possible in this model. 
\section[{1.}]{1.}\par
2. Downlink: this describes the data transmission from BS to MS.\par
In a topological aspect, the base station is positioned for good propagation condition. The location of the portables is uncertain and varying. The wireless propagation conditions have a strong impact on a choice of a suitable multiple access protocol. 
\section[{a) Adaptive Power Control algorithm}]{a) Adaptive Power Control algorithm}\par
The transmit power can be represented as:P(t+1)=P(t)+?.sign(SIRtarget-SIRest)[dB] (1)\par
Where P(t) represent the transmit power at time t, ? is the power control step size, SIRtarget, and SIRest are the target and estimated SIR respectively. The term sign is the sign function: sign(x) = 1, when x ? 0, and sign(x) = -1, when x < 0.\par
It can be noted that sign (SIRtarget-SIRest) =-1 is equivalent to a TPC power up command which can be represented by bit 0. From Equation 1, it can be observed that the transmit power will be increased or decreased by ? on every time slot. The transmitted power will always change even when there is no change in the channel.\par
The transmit power is updated according to the following equation: P u (t+1)=P u (t)+AF u (t).PDF u (t)?.TPC u (t)\par
(2) Where AFu (t) is the Adaptive Factor of u th user at time t, and TPCu (t) is the TPC command of u th user at time t, corresponding to sign (SIRtarget-SIRest) in Equation 1, and PDF u (t) is the Power Determining Factor. If the received message is High Contention Message, then it will increase the parameter and subsequently increases the power and if the message is Low Contention then the parameter will be decreased and correspondingly the power also. 
\section[{b) Adaptive call admission control algorithm}]{b) Adaptive call admission control algorithm}\par
Let P t be the total power of the existing users in the network.\par
Let P a be the total available power. Let P r be the power of the requested new user to get admission in the network. In the above algorithm priority is given for hand off request calls ,since handoffs are important then the new calls. The power of the existing users are degraded according to priorities . Here non real time services are degraded first when compared with real time services which leads to reduced loss for real time services. The existing users are degraded to a minimum power level till they maintain acceptable quality of service in the network. 
\section[{Upgradation}]{Upgradation}\par
If M are the out going calls in the network .The out going calls are the calls that are moved from current cell to the other neighboring cells. If N are the completed calls in the network. The total power used by the out going calls and completed calls in the network is P m + P n. P m= power used by M out going calls in the network. P n.= power used by N competed calls in the network.\par
The power levels are updated in the network .The power left by the M out going calls and N competed calls can be used by the existing users in the network.\par
IV. 
\section[{Simulation Results}]{Simulation Results} 
\section[{a) Simulation Setup}]{a) Simulation Setup}\par
In this section, We simulate the proposed adaptive call admission control (ACAC) algorithm for WCDMA cellular networks. The simulation tool tool that provides discrete event simulation of user defined networks. In the simulation, mobile nodes move in a 600 meter x 600 meter region for 50 seco--nds simulation time. Initial locations and movements  
\section[{Figure1: Arrival Rate Vs Call Blocking probability}]{Figure1: Arrival Rate Vs Call Blocking probability}\par
As shown in the figure  {\ref 1} the call blocking probability of adaptive call admission control is less compared with non adaptive call admission control algorithm (CAC).H ere in ADCAC the users are degraded and the resource is given to the requesting users . CAC algorithm is not dynamic hence most of the resouce is wasted. 
\section[{Figure2: Arrival Rate Vs delay}]{Figure2: Arrival Rate Vs delay}\par
As shown in the figure  {\ref 2} the delay of adaptive call admission control is less compared with non adaptive call admission control algorithm (CAC).Here in ADCAC more users are admitted in the network hence data can be transmitted sucessfully. where as in CAC algorithm of the resouce is not used efficiently the data is not transmitted sucessfully. 
\section[{Figure3: Arrival Rate vsThroughput}]{Figure3: Arrival Rate vsThroughput}\par
As shown in the figure  {\ref 3} the Throughput off adaptive call admission control is more compared with non adaptive call admission control algorithm (CAC).here in ADCAC the users as the resource is used efficiently the requesting users are admitted in the network with out delay . where as in CAC algorithm of the resouce is not used efficiently the users have to wait for getting admission in the network.\par
V. 
\section[{Conclusion}]{Conclusion}\par
In this paper, a novel Call Admission Control algorithm for wireless cellular networks is proposed. The call admission control algorithm is based on power control. The existing users are degraded to a minimum power level till they maintain acceptable quality of service in the network and resource is utilised by the new requesting users. our proposed call admission control algorithm reduces the blocking probability increases the throughput.\begin{figure}[htbp]
\noindent\textbf{} \par 
\begin{longtable}{P{0.85\textwidth}}
1. Wait for call request arrival.\\
2. If a new call request arrives.\\
3. If it is a hand off call.\\
4. If P t+ P r < P a\\
5. Admit the request call.\\
else\\
6. If P t+ P r > P a\\
7. Degrade the existing users who are using Non\\
real time services.\\
8. After degrading NRT services If P t+ P r < P a\\
9. Admit the request call.\\
else\\
10. If still P t+ P r > P a\\
11. Degrade the existing users who are using real\\
time services.\\
12.\end{longtable} \par
 
\caption{\label{tab_1}}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{} \par 
\begin{longtable}{P{0.09066666666666667\textwidth}P{0.6346666666666667\textwidth}P{0.12466666666666666\textwidth}}
2011\tabcellsep \tabcellsep \\
May\tabcellsep Area Size\tabcellsep 600 X 600\\
\tabcellsep Number of Cells\tabcellsep 2\\
\tabcellsep Users Per Cell\tabcellsep 20\\
\tabcellsep Slot Duration\tabcellsep 2 msec\\
42\tabcellsep Radio Range Frame Length\tabcellsep 250m 2 to 8 slots\\
\tabcellsep CDMA codes\tabcellsep 2 to 5\\
Volume XI Issue VIII Version I\tabcellsep \multicolumn{2}{l}{Uplink: this demonstrates data transmission from mobile station MS to BS. Simulation Time 50 sec Routing Protocol AODV Traffic Source CBR, VBR Video Trace JurassikH263-256k Packet Size 512 bytes MSDU 2132 Transmission Rate 1Mb,2Mb,?5Mb No. of Users 2,4,6,8 and 10 SINR Threshold 5 power Tx power,Rx 0.66w,0.395w}\\
Global Journal of Computer Science and Technology\tabcellsep \multicolumn{2}{l}{Speed of mobile Table I. Simulation Parameters 25m/s b) Performance Metric The performance is mainly evaluated according to the following metrics: Throughput: It is the throughput received successfully, measured in Mb/s.}\\
\tabcellsep \tabcellsep used is NS2 which is a general-purpose simulation\\
\tabcellsep \tabcellsep ©2011 Global Journals Inc. (US)\end{longtable} \par
  {\small\itshape [Note: of Average End-to-End Delay: The end-to-end-delay is averaged over all surviving data packets from the sources to the destinations. Call Blocking Probability: It means the likelihood that a new arriving call is blocked. Actually, it depends on the CAC scheme.]} 
\caption{\label{tab_2}}\end{figure}
 			\footnote{May point (RWP) model of NS2. All nodes have the same tra -©2011 Global Journals Inc. (US)} 		 		\backmatter  			  				\begin{bibitemlist}{1}
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\end{document}
