### Handoff Analysis in CDMA Based Wireless Cellular Network using Hard Handoff Model

**Bhavtosh Awasthi**

Department of Mathematics,
JECRC University, Jaipur-303905, Rajasthan, INDIA.

email: bhavtosh123@gmail.com.

(Received on: November 26, 2017)

**ABSTRACT**

In Code division Multiple Access (CDMA) based cellular network, all cells share the same frequency bands and user can transmit simultaneously. In hard handoff, the old radio link is established and a handset always communicates with on base station (BS) at any given time. In the handoff procedure, the network needs to set up the new voice path for the handoff call. This setup time is referred as the network response time. If the old radio link is disconnected before the network completes the setup, the call is forcedly terminated. In this paper we introduce the concept of overlap region between adjacent cells and develop an analytical model for hard handoff in CDMA system. Balking and reneging behaviors of calls have also considered in this model. Different performance measures using variation in different parameters are calculated and results have been analyzed graphs.

**Keywords:**CDMA, Handoff, Base station, overlap region.

**1.INTRODUCTION**

With the rapid demand of wireless communication services, mobiles users are expecting the same level of availability and performance from wireless communication systems as traditional wireline networks. In general, wireless systems are characterized by their scarce radio resources which limit not only the service offering but also the quality of service (QoS). Mobility causes dynamic variations in link quality and interference levels in cellular systems, sometimes a particular user change its serving base station because of his/her mobility. This change is known as a handoff. In hard handoff, the old radio link is broken before the new radio link is established, and a handset always communicates with one BS at any given time. In the handoff procedure, the network needs to set up the new voice path for the handoff call. This setup time is referred to as the network response time if the old radio link is disconnected before the network completes the setup, the call is forced terminated.

Thus, even if idle channels are available in the new cell, a handoff call may fail if the network response time for link transfer is too long. A handoff failure may not necessarily cause a call drop. It is normally some time-out mechanism for the voice or signaling path which leads to a dropped call. Cellular communication system requires handoff to provide seamless service for users, moving across cells. Code division multiple access has received a great deal of attention as a multiple access method for future mobile networks. It main advantages are higher radios capacity and the capability of flexible data transmission.

Lee^{1,2} gave his overview on the system and explains different term and future of the mobile communication system and general description of code division multiple access (CDMA) system. They also analyzed power control scheme in (CDMA) system. Gilhousen et al.^{3,4} proposed spread spectrum or code division techniques for multiple access and developed personal handy phone system. Jabbari et al.^{5} developed a system for personal mobile communication system using hard handoff. Yeung and Nanda6 proposed a scheme for channel management in microcell/macrocell cellular radio systems. Sandouk et al.^{7} analyzed performance of CDMA voice signals. Ramakrishna and Holtzman8 discussed a scheme for throughput maximization in a dual-class CDMA system. Khan et. al.^{9} investigated linear and exponential back off techniques for the uplink common channel packet transmission in wide band CDMA for Poisson arrival process. Greenberg et al.^{10} described how to assign distinct number of code channels to each traffic class. Kim and Sung^{11} proposed many analytical schemes for handoff analysis based on hard handoff in mobile communication system. They developed an analytical model for soft handoff in CDMA systems by introducing an overlapping region between adjacent cells and the handoff call attempt rate and the channel holding times are derived. Applying these results to a non-prioritized CDMA system, the effects of soft handoff and the mean cell residual time are investigated. Lee et al.^{12,13}analyzed performance of channel borrowing handoff schema based on user mobility in CDMA cellular system and also studied the soft-handoff mechanism and compares its performance with the hard handoff. A mathematical structure for the handoff problem had developed by Rajat P. and Venugopal V. V.^{15}. They also presented an easily implementable hysteresis threshold approximation and shown that it retains the adaptive nature of the LO algorithm. Kishor S. Trivedi et al.^{16} have presented our research work on handoff performance in wireless cellular radio system. They developed tractable analytic models for the wireless system with hard handoff, and hard handoff including channel failures. They also obtained closed form solutions to new call blocking probabilities and handoff call dropping probabilities. Kishor S. Trivedi et al.^{17} have presented the CTMC, MRM and SRN models for performability studyof a variety of wireless systems. By solving the two-level models, we can compute performability measures, such as call blocking probability and handoff call dropping probability, for wireless systems and wireless cellular systems with handoff, base repeaters, and control channels. Hamdaoui & Ramanathan^{18} implemented a soft handoff scheme called soft handoff. Through analytic and simulation studies, they showed show that SHIP achieves significant performance improvements. Bhuvaneswari and George^{19} provided an overview of handoff types, performance metrics, handoff schemes and handoff algorithms has been provided. This survey gives an idea to us about the existing schemes and algorithms to handle handoffs. Nisha & Sunil^{20} summarized different handover schemes like soft handover, hard handover, vertical handover and horizontal handover. Liton (2013) presented an overview about the issues related to handoff initiation and decision and discuss about different types of handoff techniques in wireless communication. Imeh et al. (2014) have analyzed the performance of soft handoff in a realistic cellular network and revealed the problems associated with soft handoffs in telecommunication systems. They have also proposed a SH model, implementing same using realistic data for the purpose of improving the performance of the system, taking into consideration different coverage areas and diverse propagation exponents.

In this chapter, we have developed the mathematical model for hard handoffs in CDMA system to analyze the problem of handoff in cellular radio system. In this model, the balking and reneging behaviors of queued handoff calls also considered. The system capacity is to be considered finite. We have calculated different performance measures like blocking probability of new calls; call incompletion probability, blocking probability of handoff calls etc.

**2. THE TRAFFIC MODEL**

The queueing model dealing with soft handoff scheme for a cellular radio system with finite capacity is developed. There is C channels available in each cell of the system. In this system two types of calls are arrive 1) new calls and 2) handoff calls. The balking and reneging behaviors of calls are also considered. We assume that a handset can connect up to two radio links in a CDMA system.

**2.1 DERIVATION**

ti = time that a handset can receive the signal from cell i i. e. the time that the handset resides in cell i

τi = the overlapping time i. e. the time that the handset resides in the overlapping area of the cell i

yi = the time that the handset stays in the non-overlapping area of cell i

In Hard handoff, a communication mobile unit is switched from cell i to cell (i+1) at some point within τ i. The handoff occur at time zi , i=0, 1, 2, . . .

According to hard handoff scheme, the residence time of the handset at cell i is

Since the radio link between the base station and the mobile unit is broken before it is connected in hard handoff, the link transfer may fail due to long response time even if radio channels are available in the new base station. The following assumptions are considered in this model:

- The call arrival to/from a handset is following a Poisson process. The new call arrival rate to a cell is λn and the handoff call arrival rate isλh .
- The mobile residence time qi in a cell i has an exponential distribution with the density function given by

*f*(3)_{m}(q_{i}) = θ_{e}−θ_{qi} - pn =New call blocking probability
- pr =Probability that a handoff call is blocked because no free channel in the is available probability
- The balking of calls according to exponential distribution with balking probability β
- The reneging of calls according to exponential distribution with parameterv. The call holding time tc is exponentially distributed with the mean 1/μ p f = forced termination probability or the probability that a handoff call is blocked because no channel is available
- pnc = call incompletion probability
- α h = The probability that a hard handoff call is blocked because the network response time is too long.
- Pi = the steady state probability that there is i customer in the system at any arbitrary point of time.
- 1/η =Mean time that the handset stays in non-overlay area.
- 1γ =Mean time that the handset stays in overlay area.
- 1/θ =Mean residence time of the handset at cell.
- 1/β1 =Mean network response time.

**3. MATHEMATICAL ANALYSES**

We are considering only one case to model soft handoff CDMA system. The steady state probabilities for this case are obtained as follows.

**3.1 M\M\C\K Model**

Using birth-death process as shown in the figure (2), the steady state probabilities for
this model are given by

Let i P be the steady state probability for S(i). Then

**4. RESULT AND DISCUSSION**

In this section, we have calculated the numerical results and draw graphs to show the effect of different parameters on the blocking probabilities. Simulation technique has been applied to analyze the numerical results. Some graphs have been presented here to show the effect of different parameters on different blocking probabilities.

**5. DISCUSSIONS**

We derived mathematical model with simulation to analyze the problem of handoffs in CDMA (Code Division Multiple Access) network. Balking and reneging behaviors of queued handoff calls are considered in this chapter. We have considered only voice traffic of new and handoff calls. Different types of blocking probabilities have been derived. Simulation results are calculated to show the effect of different parameters on blocking probabilities. In this chapter effect of Balking and reneging behaviors of calls on performance indices are summarized. From results it is conclude that:

- As number of channels in a cell or service rate increase, then the corresponding blocking probabilities decrease.
- The blocking probabilities decrease with increase in arrival rate of both type of calls (New and Handoff).

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