Performance evaluation

4.5.2.1 SINR evaluation

We have calculated the SINR for various position of the MS in the cell. Figure.4.3 shows the SINR of all of the positions of the MS in the sectoring relay model. The SINR is very high when the MS is near the RSs or the BS and decreases with exponent factor 3.5 (COST231 Hata path loss model) when the distance between the MS and the BS/RS increases. This result is almost the same when we evaluate the SINR in non cooperative an cooperative relay model. In the coverage zone of the RS or the BS, the numerical result shows that the received power from other stations is always much smaller than that from the main station. In the worst case (edge of coverage zone), SINR decreases to most 2dB when we take into account the interferences from other

4.5 Simulation scenario and result discussions

Figure 4.3: SINR of mobile station at all the positions in the cell

stations. We can conclude that the impact of interferences in our model is the same as in the other relay models.

4.5.2.2 Spectrum efficiency evaluation

In this section we discuss about the spectrum efficiency at the base station for all of the possible positions of MSs in the cell. We remind that BS is not used in the second phase in the cooperative relay station and the BS only helps the RS to transmit data to the MS in the second phase. The resource at the BS is not used efficiently in these two cases. If the link between the BS and the RS is reliable (using the best coding scheme 64-QAM), the BS spends at least twice time to transmit the same amount of data to the MS than it spends on the direct connection. This correlates with the result obtained in the simulation (c.f Figure.4.4). Even if the MS is near to RS, the spectrum efficiency of BS is always smaller than 2.5 bits/Hz/s. In the sectoring relay model, the RS uses a different frequency band to transmit data in the second phase so that the BS is free to transmit data to the other MSs without being interfered by the RS in the same sector.

To transmit an amount of data to the MS via the RS, the BS spends only a fraction of its communication resources (time and frequency channel) to transmit this data to

(a) Non cooperative relay (b) Cooperative relay

(c) Sectoring relay

Figure 4.4: Spectrum efficiency of base station at all the point in the cell (three difference cases)

the RS. That is why even if the coding scheme from the RS to the MS is weak, the spectrum efficiency at the BS is still the best because the link between BS and RS is always reliable. Figure.4.4(b) shows that the BS achieves the best spectrum efficiency at the coverage range of the RS. This result proves the superiority of our proposed sectoring relay model in term of spectrum efficiency vs other models.

The average spectrum efficiency is also evaluated in different models and in different deployments of the MS in the cell. The “Static sectoring” model was proposed in our previous work [71] where the entire frequency band is equally divided among the different sectors of the cell. In the worst case, all the MSs are allocated in only one

4.5 Simulation scenario and result discussions

Figure 4.5: Spectrum efficiency Bit/Hz/s in different relay model

sector, and therefore the resource at BS is wasted in the two other sectors. To solve this problem, we propose a scheme called “Dynamic sectoring” where the frequency band in each sector is adjusted based on the data demand in each sector. The result of the simulation running over 10 000 experiences is illustrated in Figure.4.5. The average spectrum efficiency with 2% variation is presented. The result shows that the average capacity of the BS decreases significantly in “Static sectoring” model when all fo the MSs are located in only one sector. In this case, the “Dynamic sectoring” model becomes the “non cooperative relay”. Hence, the average spectrum efficiency in “Non cooperative relay” model is the same as the one in “Dynamic sectoring” model. It is slightly smaller than the average spectrum in “Cooperative relay” model. When the MSs are deployed in two sector, the “Dynamic sectoring” model performs much better than “Cooperative relay” and “Non cooperative relay” model while average capacity of the BS in the “Static sectoring” model is slightly smaller than the one in the other models. When the MSs are distributed uniformly in all the three sectors of the cell, the

“Static sectoring” model becomes the “Dynamic sectoring” model, the simulation shows that the average spectrum efficiency is equivalent in the two models. Comparing to the system non cooperative relay and cooperative relay in terms of spectrum efficiency Bit/Hz/s, the sectoring relay model increases by 50%. We conclude that the proposed sectoring technique significantly improve spectrum efficiency.

4.6 Summary

In this chapter, we studied the impact of interference in the sectoring relay 802.16j model. We reviewed the non cooperative relay model, the cooperative relay model and also the proposed sectoring relay model. We used the COST231 Hata path loss model to evaluate the impact of interference in all of these three relay models. We also proposed a new dynamic frequency band allocation among the sectors. The results show that the average spectrum efficiency in our model is almost the same as the average spectrum efficiency in the other models in the worst case where the MSs are located in one sector.

In the other deployment of the MSs, our solution introduces a significant increase in terms of spectrum efficiency at the base station when the interference is taken into account.

Chapter 5

Radio Resource Management : Algorithm and Optimization

5.1 Introduction

In the previous chapter, we described a new architecture of Wimax with Relays standard and its frame structure in order to enhance the spectrum efficiency. We also studied the impact of interference in this model. We showed an improvement of the system throughput due to the capability of the architecture to mitigate interferences.

In this chapter we will study the radio resource management in our system. In section II, III, the radio resource management(RRM) studies are presented in both Wimax and Wimax with Relays. We then formulate the RRM optimization problem in section IV.

We also propose a heuristic algorithms with low complexity to solve the optimization problem are given in this section. The simulation results are discussed in section V.

Finally, the conclusion of our study in this chapter is given in section VI.