Mobility Capacity Conversion
Bounding the Mobility/Capacity Conversion Efficiency in multi Service Wireless Communication Networks.
Abstract
- In this paper the mobility/capacity conversion (MCC) efficiency of reused based resource management strategies in multi-service wireless communication networks is mathematically analyzed.
- A useful and efficient resource management strategy is proposed and evaluated.
- The proposed strategy exploits the synergy between the maximum packing multiple fractional channel reservation and anticipated channel release mechanism to maximize the MCC efficiency.
- A multi cell model is considered for tele traffic analysis.
- Numerical results show that the use of dynamic channel allocation and handoff protection policies, in addition to anticipated channel release mechanism in the resource management strategy is crucial for minimizing the impact of mobility on the MCC process.
- This is true when network supports multiple classes of subscribers having different bandwidth and QOS requirements.
Introduction
- Third generation and beyond third generation of mobile cellular networks will serve multiple classes of subscribers with each class having significantly different QOS and bandwidth requirements.
- Goal of the network operators is to maximize system capacity subject to constraints on the QOS metrics.
- In this paper a general formulation on analyzing the mobility/capacity conversion efficiency of reuse based resource management strategies in multi service wireless communication network is presented.
- The main conclusion is that a wireless network has to sacrifice its capacity in order support the mobility increase.
- Challenge for any resource management is to maximize MCC efficiency.
Primary difference between present work and previous approaches
- Instead of advocating a resource management strategy a systematic way of maximizing the efficiency of MCC process is provided.
- In particular a useful and efficient resource management strategy is proposed and evaluated.
- Proposed strategy exploits the synergy between maximum packing (MP) , multiple channel reservation(MCR), fractional channel reservation(FCR), and anticipated channel release(ACR) concepts to provide a point of reference on maximum MCC efficiency.
- These concepts are used ion this work simultaneously.
- The MP is idealized algorithm that provides the best performance of dynamic channel allocation (DCA) strategies.
- DCA has recently received again increasing attention due to its capability of easily adapting itself to both temporal and spatial traffic variations.
- In multi service scenario MCR provides multiple prioritization levels to efficiency satisfy the QOS of different traffic classes.
- FCR finely controls the communication service quality by varying the average number of reserved channels.
- In short MCR, ACR, DCA and FCR allow system to reach its maximum capacity while meeting the QOS constraints.
- ACR mechanism takes advantage of break-before-make hard handoff characteristics.
- To improve system capability it is (ACR) when a handoff attempts occurs the occupied channel is released in the source cell just before the handoff is carried out.
Goal of Presented Work
- The goal is obtain new and very important insights into the behavior of their mobility/capacity conversion process in network supporting multiple classes of subscribers with each class having different QOS and bandwidth requirements.
Teletraffic Analysis
- To study the MCC process a multi cell model is considered for the teletraffic analysis. Additional the effect of the relative user's mobility and bandwidth requirements on system capacity is evaluated.
System and Teletraffic Models
- Traffic arriving at each cell is partitioned into k separate classes based on bandwidth requirements. Each class k of subscriber requires ck channel or bandwidth basic unit (BBU). Where ck is an integral number of channel.
- Sub carrier for OFDM based system, time slots for TDMA based system, and frequency channel for FDMA.
Classes of Traffic
- Each class of traffic is separated into two types of calls, namely
- New call and handoff calls.
- K different services result in total of 2k different call types, namely,
- New calls of service 1(N1), handoff calls of service 1
- New calls of service 2(N2), handoff calls of service 2
- New calls of service k (NK) , handoff calls of service k.
Each with different bandwidth and individual QOS requirements.
System Capacity
- System capacity is defined as maximum offered traffic load for which all the QOS constraints are still satisfied.
Teletraffic Analysis
- In this section authors mathematically analyzed the maximum packing with multiple channels reservation and anticipated channel reservation release strategy (MPFA)
- The MPFA strategy reserves different real numbers of BBU in order to provide certain protection level to each of the diverse call types. It assumes that the prioritization level assigned to a call type is directly proportional to the amount of resources it has access to. Thus the higher priority a call type has the more resources it can use.
Method of Analysis
- To facilitate the analysis authors first convert the k-D dimensional Markov process to a1 dimensional one by renumbering the states.
- Numerical evaluation is performed by mapping.
- Authors also draw and elaborate the equilibrium state equations of their presented model.
- Authors used the Gauss seidel method to calculate the corresponding steady state probabilities.
- Finally authors used hill climbing method to determine the optimum number of reserved channels.
Numerical Results
- In this section numerical results of proposed strategy have shown.
- Authors evaluate the performance of following many strategies
- MP
- MPA
- FCAF
- MPF
- MPFA
- Their results shows that resource management strategies based on dynamic channel allocation present a more efficient mobility/capacity conversion process compared with strategies based on fixed channel allocation.
- It is also evident that the synergy between MP and FCR is considerably improved by ACR mechanism.
Conclusion
My Suggestions after detailed review of Paper
We provide a professional essay writing service that thousands of our customers use as an effective way of improving their grades, improving their research and saving them lots of time.
