QOS IMPROVEMENT IN CELLULAR NETWORKS USING CCSM TECHNIQUE
ABSTRACT
The objective of our project is to improve the Quality of service (QoS) in cellular network using CCSM technique. CCSM is a technique which measures the statistics of a cell periodically. The statistics includes call blocking ratio (CBR), signal to interference plus noise ratio (SINR) and intercell interference (ICI).
These parameters are measured in NME (Network management entity) of the cell cluster and then stored as database. NME is proposed in master base station of a cluster. Usually the center cell of a cluster is taken as master cell. The master base station analyses the statistics of all cells in a cluster periodically. The cells are then ranked based on rule based ranking using AHP (Analytic Hierarchy Process).
The ranking is then communicated to all the cells in a cluster for QoS parameter improvement. Thus by analyzing the cell statistics, QoS parameter such as SINR,CBR,ICI are improved when compared with existing method.
Key words: Qos – CCSM – NME- Master base station- Analytic hierarchy process.
Introduction
Cellular communication is based on a cellular network. Each transmitter in cellular systems for mobile communications, typically called a base station, covers a certain area called a cell. Aservice coverage area of cellular network is divided intomany small areas which are known as hexagonal cells. Eachcell has one base station which is located in its center. Thebase station (BS) is fixed. Several base stations (BSs) areconnected with a mobile switching center (MSC).
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The MSC is connected to a public switched telephone network (PSTN) and is the control center for the cellular system, coordinating the actions of the base station. A mobile host can communicate only with the base station in its cell directly. When a mobile host wants to set up a call, it sends a request to its base station in its cell on the control channel. The call can be set up only if a channel is assigned to support the communication between the mobile host and the base station. The assignment of channels to cells and to mobile stations is the fundamental operation of a mobile communication system and efficient channel allocation strategies are required to increase call carrying capacity and load balancing. In cellular networks, while the motivation behind all basic channel assignment strategies such as FCA, DCA and HCA is the better utilization of the available frequency spectrum with the consequent reduction of the call blocking probability in each cell and to improve the Quality of service in the network.The maintenance of Quality of Service (QoS) in a wireless environment is a difficult problem.In cellular network, there are no of parameters which are affecting on quality of service of the network. There are various techniques which are used to improve it. One of the parameter is rejection of a call due to unavailability of the free channel. Call can be new call or handoff call.
In order to balance the load among different cells, it isneeded to transfer the over-loaded traffic from hot cells to neighboring cooler ones.That is a cell with traffic load substantially larger than the design load called as hot-spot cell. Different techniques can be used to increase the capacity.Among such techniques, reservation based channel assignment technique is proposed.[1].In cellular networks, blocking occurs when a base station has no free channel to allocate to a mobile user. One distinguishes between two kinds of blocking, the first is called new call blocking which refers to blocking of new calls, and the second is called handoff blocking which refers to blocking of ongoing calls due to the mobility of the users.
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Fig.1. New call and handoff call
By using reservation based channel assignment technique we can assign channel groups to user groups according to call duration so that short duration calls will not be blocked due to long duration calls.
Another approach is hierarchical based scheme dual-band cellular mobile communication network is considered where each cell i.e. the macro and microcells are served by different base stations that are center excited. If the speed of the user is determined to be fast then the call is sent to the macro cell, else if the user were slow then the call would be sent to microcell to be served. When a call is sent to the microcell but the required bandwidth of the call is large than the available bandwidth, then the call would be forwarded to the macro cell[2].
Rana introduces the concept of hybrid channel allocation (HCA) which is the combination of fixed channel allocation (FCA) and dynamic channel allocation (DCA).
When a mobile host needs a channel for its call, and all the channels in its fixed set are busy, only then a request from the dynamic set is made.[3]
Also call blocking can be reduced using auxiliary stations. Failure probability may be minimized if the handoff request is served by an Auxiliary Station (AS) closest to the mobile station (MS), if the channels of base station (BS) are not free. The mobile station, being in the auxiliary station, will send requests to the base station within fixed time intervals and when it will find free channels are available in base station it will automatically connect with it, rejecting the connection of the auxiliary station (AS).
This process effectively reduces the handoff failure probability.[4]
PROPOSED SYSTEM ARCHITECTURE
The proposed system uses a CCSM technique which has network management entity. NME plays an important role in load balancing as it collects the status of all the cells in a cluster.
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This system improves the Quality of Service (QoS) in the cell and avoids unnecessary handoff.
ALGORITHM DESIGN AND DESCRIPTION
Consider a cellular network, in which the cells are alternatively loaded as lightly loaded, medium loaded and heavily loaded.
1) NME, at the centre cell of a cluster sends control signal to all the surrounding BS to know about the status of each cell.
2) Each cell report its measurement to the NME
3) The CCSM in NME detects an overload, if it satisfies the following condition.
* CBR≥CBRth
* SINR≤SINRth
* ICI≥ICIth
Fig 2.Structure of cellular network.
4) Now, CCSM in NME analyses how much the cell is loaded by using the following rules
Rule1: If (load is lightly loaded)
a. Then (status_loadbalance_node is receiver)
Rule2: If (load is heavily loaded)
b. Then (status_loadbalance_node is sender)
Rule3: If (load is medium load)
c. Then (status_loadbalance_node is receiver)
5) After analyzing, it checks the status of the adjacent cells to make a decision using an AHP, and share its load.
6) This process is repeated for an average time of 60sec periodically.
7) When taking decisionusing AHP, we need to do same comparisons.
8) For that, first we need to create a matrix table for the pair wise comparison of alternatives based on each criterion.
9) The matrix table is created by the use of common intensity table.
10) Then the matrixes value must be squared and normalize the value to compute priority vector.
11) Next, criteria comparison also made similar to alternative comparison and compute its priority vector.
12) Now, to develop an overall priority ranking multiply the normalized value of each alternative with its respective criteria value.
13) Then add all the values of criteria for each cell to obtain the output.
14) Depending upon the result of AHP ranking, the load is shared to the desired cell and the process ends.
PARAMETER DISCUSSION
AHP CALCULATION
Analytic hierarchy process is a decision making tool used to solve complex decision problems. A master base station wishes to select a light loaded adjacent cell in a cluster and has 3 aspects in mind which will govern its selection choice: SINR, CBR, ICI. Competing cells for that heavily loaded cell have offered three options. That is they are the adjacent cells of a heavily loaded cells. The NME have looked at these options and decides according to it.
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HIERARCHY TREE
SELECT THE LIGHT LOAD CELL (GOAL)
ICI
CBR
SINR
INTERMEDIATE NEIGHBOURING CELL
INTERMEDIATE NEIGHBOURING CELL
INTERMEDIATE NEIGHBOURING CELL
q
The mathematics of the AHP and the calculation techniques are explained here. “The AHP calculations” but its essence is to construct a matrix expressing the relative values of a set of attributes.For example, what is the relative importance to select a light loaded cells? We have to choose whether which cell is much more important, somewhat important, absolutely more important and so on down to very much less important. Each of these judgments is assigned a number on a scale. One common
scale (adapted from Saaty) [5] is the one shown in Table 1.
INTENSITY OF IMPORTANCE | DEFINITION | EXPLANATION |
1 | Equal importance | Two factors contribute equally to the objective |
3 | Somewhat important | Experience and judgment slightly favor one over the other |
5 | Much more important | Experience and judgment strongly favor one over the other |
9 | Absolutely more important | The evidence favoring one over the other is of the highest possible validity |
TABLE 1
A basic, but very reasonable, assumption is that if attribute A is absolutely more important than attribute B and is rated at 9, then B must be absolutely less important than A and is valued at 1/9. These pair wise comparisons are carried out for all factors to be considered and the matrix is completed.
PAIRWISE COMPARISON
EVALUATE ALL ALTERNATIVES WITH RESPECT TO EACH CRITERION
SINR | CELL 1 | CELL 2 | CELL 6 |
CELL 1 | 1 | 1/9 | 1/5 |
CELL 2 | 9 | 1 | 9 |
CELL 6 | 5 | 1/9 | 1 |
NORMALIZED VALUE: 0.044
0.816
0.139
0.999
The same comparison matrix is repeated for CBR&ICI.
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CRITERIA COMPARISON
CRITERIA | SINR | CBR | ICI |
SINR | 1 | 1/9 | 5 |
CBR | 9 | 1 | 3 |
ICI | 1/5 | 1/3 | 1 |
NORMALIZED VALUE: 0.1592
0.7699
0.070
0.9994
To develop an overall priority ranking multiply the normalized value of each alternative with its respective criteria value.Then add all the values of criteria for each cell to obtain the output.
AHP RANKING
CRITERIA/ ALTERNATIVE | SINR | CBR | ICI | OVERALL PRIORITY |
CELL 1 | 0.00702 | 0.0338 | 0.0030 | 3
0.04382 |
CELL 2 | 0.13034 | 0.6282 | 0.0573 | 1
0.81584 |
CELL 6 | 0.0223 | 0.10755 | 0.0098 | 2
0.13965 |
RESULTS AND DISCUSSIONS
COMPARISON RESULTS
| LOAD BALANCING | SINR | CBR | ICI | CELL RANKING |
Existing method | Load can be shared to the nearest cell even it is heavily loaded | SINR is too low | CBR will be high and there is frequent drop of calls | ICI is high | No ranking position |
Proposed method CCSM Technique | Load can be balanced based on AHP | SINR is better | CBR will be low as it shares to low load cells | ICI is low | Rank is based on AHP |
CHAPTER 4
CODINGS AND RESULTS
STRUCTURE OF CELLULAR NETWORK
PROPOSED MODEL CONSIDERATION OF CELLULAR NETWORK
SNR VS ICI
PERFORMANCE OF SINR VARIATION
THE CELL SELECTED WITH AHP ALGORITHM
Conclusion
The Proposed method is simple to implement and flexible. Using proposed algorithm we can reduce handoff failure when all the channels are busy and can reduce unnecessary hand off. By using this algorithm, call will never get rejected, so call blocking probability is reduced and improves the traffic distribution between cells. It provides satisfactory services to all the users without a call dropping problem and also ensures a reliable Quality of Service to the subscribers.
References
1) Abhijit Sharma, Deepak Kumar “Call Blocking Performance of New Reservation based Channel Assignment Scheme in Cellular” IJCA Special Issue on “2nd National Conference- Computing, Communication and Sensor Network” CCSN, 2011
2) SaravananKandasamy, Prihandoko, BorhanuddinMohd.Ali “New Call Blocking Probability (NCBP) in Improved Adaptive Quality of Service (AdQoS) for Wireless Multimedia Communications using Hierarchical Cellular Approach” 2003.
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3) RanaEjaz Ahmed , “A Channel Allocation Algorithm for Hot-Spot Cells in Wireless Networks” journal of advances in information technology, vol. 1, no. 3, august 2010
4) “Minimization of Call Blocking Probability using Auxiliary Stations” International Journal of Computer Applications (0975 – 8887)Volume 25– No.7, July 2011
5) Using the Analytic hierarchy process for decision making in engineering applications ,EvangelosTriantaphyllou, International journal of industrial engineering, vol- 2
6) An illustrated guide to the Analytic hierarchy process by Dr.Rainer Haas, Dr.OliverMeixner