Chapter 4 Resource Scheduling with Directional Antennas for Multi-hop Relay
4.4 Numerical Results
The parameters of the simulated system are set according to the OFDMA mode in the IEEE 802.16 standard [14], [70], which are summarized in Table 9. The required SINRs to achieve 10-6 bit-error-rate (BER) for the various MCSs considered are given in Table 10 [70]. The scheduling method for the system with omni-directional antennas is also simulated to serve as the base-line scheme for performance comparisons. A multi-cell setup with two-tier interfering cells is considered. The locations of BS and RSs are fixed, while users are uniformly distributed within each cell. The data traffic of each user is full-buffer traffic model. A fixed transmission power is used in the downlink, and the adaptive rate control is executed every frame to select an appropriate modulation and coding scheme based on the perfect channel state information.
Figure 39 shows the simulated CDFs of SINR for different scheduling methods. To emphasize on the capacity gain obtained from the new scheduling methods, the transmission power in our simulation of the onmi-directional antenna case is increased to offset the antenna gain obtained with the directional antennas. Clearly, the scheduling scheme with omni-directional antennas has the best SINR performance, while Method-2 has the worst because it reuses the frequency spectrum more aggressive.
Table 9. OFDMA parameters for system-level simulation.
Parameter Value
Carrier frequency 3.5 GHz
Bandwidth 6 MHz
FFT size 2048
Sub-carrier frequency spacing 3.348 kHz
OFDM symbol duration (including 1/8 cyclic-prefix)
336 µs
Duplexing TDD
Frame duration 20 ms
Permutation mode of each sector FUSC (full usage of sub-channels)
Number of sub-channels 32
Number of sub-carriers per sub-channel 48
Max. transmit power of BS /RS 100 mW
Table 10. The used MCS.
Modulation Coding rate Receiver SINR (dB)
to achieve 10-6 BER
BPSK 1/2 6.4
1/2 9.4
QPSK
3/4 11.2
1/2 16.4
16-QAM
3/4 18.2
2/3 22.7
64-QAM
3/4 24.4
Figure 39. The CDF of SINR for different scheduling methods.
The capacity simulation result is shown in Figure 40. The cell capacity is increased enormously with the proposed methods. The capacity gain is approximately 6 and 12 times for Method-1 and Method-2, respectively, as compared with the system with the omni-directional antennas. The reason of the capacity gain can be simply explained as follows. First, as shown in Figure 34 and Figure 37, Method-1 and Method-2 can achieve frequency reuse factor of 1, while in Figure 29, the reuse factor of at least 2 (here the case of reuse factor 2 is simulated) is required for the system with omni-directional antennas.
Hence, at least 2 times of capacity gain is obtained as compared to the omni-directional antenna case. Second, from Figure 32, only 2/3 of the transmission phases in a frame are used for the BS’s transmission. On the other hand, 2 and 4 BS’s transmissions in each phase are possible for Method-1 and Method-2 respectively, as shown in Figure 35 and Figure 38.
That results in another 3 and 6 times of capacity gain over the case of the omni-directional antennas. Table 11 summaries where the capacity gains come from for Method-1 and Method-2 as compared with the omni-directional antenna case. However, due to the higher interference level observed in Figure 39, the simulated capacity gain of Method-1 over the system with omni-directional antennas is slightly less than 6 times, as our simplified analysis predicts. On the other hand, the simulated capacity gain of Method-2 over Method-1 is larger than 2 because the former provides more higher-data-rate connections.
Figure 40. Comparisons of cell capacity between different scheduling methods.
Table 11. The analysis of the capacity gain.
Method Reuse
factor
Effective data frame transmitted in a frame
Anal sized capacity gain Omni-directional
antennas 2 2/3 1
Method-1 1 2 6
Method-2 1 4 12
4.5 Summary
Multi-hop relay (Relay-assisted) cell architecture is a promising candidate for the next generation wireless communication systems. It has been adopted as an amendment to IEEE 802.16e standard for cell coverage extension, user throughput improvement and/or system capacity enhancement. In this chapter, we investigate the important issue of resource scheduling for Relay-assisted networks in a Manhattan-like environment. The new resource scheduling methods are proposed for the Relay-assisted networks with directional antennas equipped at both the BSs and the RSs. By taking advantage of the effect of high degree shadowing in the Manhattan-like environment, the system throughput can be increased to nearly 6 and 12 times by the proposed Method-1 and Method-2, respectively, as compared to the system with omni-directional antennas.
Chapter 5 Conclusions
In this dissertation, the design and optimization of relay-assisted cellular networks are investigated from both theoretic and practical points of view.
We comprehensively evaluate the downlink theoretical performance of relay-assisted cellular networks in the multi-cell environment with various system configurations in the first part. A genetic algorithm (GA) based method is proposed for joint multi-cell optimization of system parameters including RS’s positions, path selection, frequency-reuse pattern and resource allocation so as to maximize system SE. Numerical results show that (i) RSs provide significant improvement with respect to system SE and user throughput over the traditional cellular networks. (ii) Uniformity of user data rate comes at the expense of a large loss in system SE when FTA is employed. (iii) Somewhat surprising, the low-complexity SINR-based path selection performs nearly as good as the SE-based one for the no-reuse case while achieving slightly better performance in the frequency-reuse case.
In the second part, the uplink performance of relay-assisted cellular networks is investigated with optimized system parameters. The optimal RSs’ positions, reuse pattern, path selection and bandwidth allocation are searched to achieve two goals: one is to minimize the MS’s average transmit power to achieve a specified throughput, and the other is to maximize the uplink system SE by given a fixed MS transmit power. The advance formulation of each objective function is contributed. Genetic algorithm approach along with a multiple access interference estimation method designed for uplink performance evaluations are adopted to resolve the issues. Numerical results conclude that given a fixed allocated bandwidth to each MS, the average MS’s transmit power is significantly reduced for a targeted throughput, and the user throughput as well as the system SE are largely enhanced for a fixed uplink transmit power with the assistance of RSs as compared to the conventional cellular systems.
In the third part, we investigate the important issue of resource scheduling for Relay-assisted networks in the Manhattan-like environment. New resource scheduling methods are proposed for the Relay-assisted networks with directional antennas equipped at both the base station and relay stations. By taking advantage of the effect of high degree shadowing in the Manhattan-like environment, the system throughput can be increased to nearly 6 and 12 times by the proposed Method-1 and Method-2, respectively, as compared to the system with omni-directional antennas.
In this dissertation, the theoretical performance in both downlink and uplink with general configurations in relay-assisted cellular networks is presented. The practical issues of resource scheduling of relay-assisted cellular networks in the Manhattan-like
the benefits to improve the system capacity and the user throughput, to save transmit power of an MS in the uplink, and to provide better coverage in the Manhattan-like environment with the optimized system parameters.
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Appendix
In this appendix, we prove the following two lemmas which state the conditions for the best bandwidth allocation in a two-hop path.
Lemma 1: For the fixed-bandwidth allocation wt to each MS, the highest SE of a two-hop path is achieved with the following bandwidth allocation,
,
Proof: Recall that for the fixed-bandwidth allocation,
, ( ) , ( )
,
Lemma 2: For the fixed-throughput allocation, the highest SE of a two-hop path to achieve the target throughput tt is obtained with the following bandwidth allocation,
,
The proof follows immediately from (A.13) and (A.14).
Vita
Shiang-Jiun Lin was born in Taichung, Taiwan. She received the B.S. degree in computer science and information engineering and the M.S. and Ph.D. degrees in communication engineering from the National Chiao Tung University, Hsinchu, Taiwan, in 2000, 2002, and 2010, respectively.
In 2007, she was a summer intern in the Communication Networks (ComNets) Research Group at RWTH Aachen University in Germany. In 2008, she was a Visiting Scholar with the Department of Electrical Engineering, University of Washington, Seattle, WA, USA. Her research interests include wireless communication networks, relaying communication technology, and optimizations for wireless communication systems.