## 5 Our Proposed Novel Resource Allocation Scheme
### Proposed Algorithm
During each timeslot, there are eight users transmitting simultaneously via eight subcarriers in each cell and their positions are randomly generated. Wireless channel taken in our simulation is multipath Rayleigh fading with pass loss exponent \(\alpha=2.6\) and 8 paths with power [1 0 0 2.0053 0 0 0 1.2646] in dB. We have evaluated the sum rate of users in both cells achieved by our algorithm under different backhaul resource. As the benchmarks, the performance of Random Pairing with Equal Backhaul resource Allocation (RPEB) and Random Pairing with Random Backhaul resource Allocation (RPRB) schemes are also presented. Specifically, both RPEB and RPRB let \(\alpha\) be the same as in our proposed algorithm, \(\beta\) is a random mapping; RPRB lets \(r\) be uniformly distributed among all subcarriers; RPRB generates \(r\) randomly. For a given backhaul resource, the achievable sum rate under each scheme is averaged by 100 channel generations. The following Figure 3 compares the average sum-rate achieved by different schemes. We can make the following observations:

Our proposed algorithm outperforms two benchmarks by a significant margin. As the backhaul resource grows, this margin also grows. This is because the proposed algorithm has more and more freedom to allocate backhaul resources. Until the backhaul resource is sufficient, this margin stays stable. It verifies that optimal backhaul resource allocation is necessary to obtain better system performance [30]. These three curves have a common tendency. As the backhaul resource grows, the sum rate at first increases approximately linearly, and then it rises slowly, and finally, it enters into a stable stage. This is because in this low backhaul resource region, system capacity is limited by backhaul resources rather than additional information BS B can offer. In other words, the upper cut set bound is dominant. However, at the high backhaul resource region (larger than 60 bpcu as depicted in the figure), the additional information offered by BS B becomes the limiting factor. That is the upper multiple access channel bound is dominant. In this region, the sum rate is saturated. In addition, when the backhaul resource equals 0, all three curves converge to the same point. This is because the three schemes have the same initialization at this point. In other words \(\alpha\) is the same. Figure 2: Scenario of the theoretical analysis. Two base stations are connected through the cooperative link and our proposed method is given. ### System Level Simulation Results

In this part, the system level simulation results have been given. Different from the theoretical analysis, the system level simulation result is close to the real scenario, which is widely used in evaluation of the algorithm. In this section, we propose the scenario with seven base stations, where every base station is divided into three 120 degree sectors. The intersite distance is 500 m for regular transmission. In Table 1, we list all parameters and assumptions for the proposed simulation. The main scenario is based on the 3 GPP LTE-Advanced Winner Channel Model used in [33]; the Urban Micro channel scenario is considered, which reflects the fact of a typical load in wireless personal communications. For the LTE-Advanced system without carrier aggregation, 20 MHz bandwidth and 2 GHz carrier frequency are considered, 2 by 2 MIMO mode is also selected, but the transmission mode is simple, and the antennas at the base station side are working separately. As is shown in the following figure, each transmission antenna will send signals to its fixed received antenna only, that means the channel matrix is diagonal. The transmission power of the system is set to 6.3 W for micro or pico base stations. The number of users located in the system is 210 in total. For every base station, there are 30 users on average with the speed of 1 m/s.