Multi-User Diversity Gain based Analysis

This scenario investigates the multi-user diversity gain that can be obtained by ap- plying LTE air interface virtualization and spectrum sharing. Since OFDMA is used the user channels are normally frequency selective, which means that each user will be experiencing different channel conditions on different PRBs. There-

fore the multi-user diversity can be exploited where the channel-aware scheduler assigns the PRBS to the users experiencing better channel conditions. Virtualiza- tion enables the VOs to share their individual spectrum, which also means that the scheduler of each virtual operator has a bigger set of PRBs to exploit the multi-user diversity, which can bring additional multi-user diversity gain to the system.

This scenario shows that even in the case where no multiplexing is allowed between the different virtual operators, and each operator still has a fixed amount of spectrum, a gain can still be achieved if the spectrum is dynamically chosen based on the user channel conditions [ZZGTG11]. In this scenario two different setups are compared against each other as follows:

• Legacy setup: which is similar to today’s mobile network setup where each operator owns a fixed amount of spectrum that is pre-allocated throughout the whole simulation.

• Virtualized setup: which aims at showing how the multi-user diversity gain can be achieved by sharing the spectrum among the operators, with the total amount of spectrum each operator gets is fixed and not changing (no multi- plexing).

The rest of the simulation configurations is given in Table 5.2.

Parameter Assumption

Number of virtual operators 3 virtual operators with circular cells of 375 meters radius

Total Number of PRBs - 75 PRBs or 15 MHz (5MHz for each operator)

- 150 PRBs or 30 MHz (10MHz for each operator) - 300 PRBs or 60 MHz (20MHz for each operator)

Mobility model Random Way Point (RWP) with vehicular speed (120 km/h)

Number of users VO1: 1, 2, 3, 4, 5, 10, 15 FTP users

VO2: 1, 2, 3, 4, 5, 10, 15 FTP users VO3: 1, 2, 3, 4, 5, 10, 15 FTP users

Channel model described in section 4.3.5

MAC layer scheduler Max-C/I2

DL traffic model FTP traffic with full buffer occupancy

File size = 5 MByte, next file is loaded immediately when previous file finishes

Hypervisor resolution 1 second (for the virtualized setup)

Simulation run time 1000 seconds

Figure 5.13 shows the average cell throughput of virtual operator 1. The cell throughput is shown against various number of users (from 1 user all the way up to 15 users), as well as different system bandwidth (i.e., 5, 10 and 20 MHz). There are several findings from these results. First of all, the virtual setup achieves higher average cell throughput compared to the legacy setup, as a result of higher multi- user diversity by applying virtualization. This additional multi-user diversity gain is obtained due to the fact that the virtual operator can choose which PRBs to use in order to schedule the users from a larger spectrum selection (3 times larger).

1 2 3 4 5 10 15 0 10 20 30 40 50 60 70 80 90 100 Number of users Throughput (Mbps)

VO1 Cell Throughput against Different Bandwidth and Users Constellations Legacy 5MHz Virtual 5MHz Legacy 10MHz Virtual 10MHz Legacy 20MHz Virtual 20MHz

Figure 5.13: Virtual Operator 1 cell throughput with and without virtualization

It can also be noticed that the gap between the virtual scenario and the legacy one decreases when the number of users is increased. The reason for that is the fact that when the number of users increases, the achieved multi-user diversity gain in the legacy scenario is nearly fully exploited (converging towards the maximum gain) since the probability of finding a user with good channel condition on each PRB increases. The absolute gain in cell throughput can be more clearly seen in figure 5.14. This is the difference in cell throughput between the virtual and the legacy scenario. It can be observed that the gain in cell throughput decreases when the number of users increases. Furthermore, it is found that when the overall

2_{The max-C/I algorithm schedules the user with the highest instantaneous SINR value so as to max-}

imize the system throughput. It is often a very unfair scheduler since users with bad channel conditions might starve.

spectrum is increased the gain in cell throughput increases as well. This is because that with more spectrum resources the probability of finding a PRB where the user is experiencing good channel conditions is much higher due to the larger spectrum selection. It needs to be noted that in case of one user there is no multi- user diversity gain at all, and thus the absolute gain increases from one user to two users, and then gradually goes down with more users. The results of the other two virtual operators are not shown due to their similarity to operator 1.

1 2 3 4 5 10 15 0 1 2 3 4 5 6 7 Number of users Throughput Gain (Mbps)

VO1 Cell Throughput Gain due to Virtualization

5MHz 10MHz 20MHz

Figure 5.14: Virtual Operator 1 cell throughput gain due to virtualization

The presented results demonstrate that with the air interface virtualization and spectrum sharing, even though each operator uses a fixed amount of spectrum (no multiplexing), but being able to choose the suitable PRB from a larger spectrum selection for the users can lead to a higher cell throughput. That means applying LTE air interface virtualization and spectrum sharing improves the multi-user di- versity gain, since the chance of finding the best PRBs for each user according to his channel condition increases compared to the legacy scenario.