Resource Allocation in OFDM Based Wireless Relay Networks ...

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1.4 Resource Allocation Problem 1.4 Resource Allocation Problem The motivation behind this research project is to develop efficient resource utilization algorithms for OFDM based relay network. Although optimal resource allocation techniques have been developed for traditional point to point OFDM networks, these techniques can not be directly applied to the relay networks due to the strong coupling between different hops. Optimization tries to find the best strategy to use the resources (optimization variables) such that a performance metric (objective functions) is improved under certain system limitations (constraints function). Resource allocation in OFDM systems, for example the power allocation and the sub-carrier assignment, are formulated into an optimization problem with an objective to optimize system performance such as the system throughput subject to various constraints, e.g., the power limitation of the batteries of transmitting nodes. The optimization techniques, such as the dual decomposition, the primal decomposition, and the sub-gradient methods are used to optimally solve these resource allocation problems. In this section, we give a general overview of resource allocation in OFDM based relay networks. Detailed review of the existing works will be presented in the next chapters. The optimal power allocation is known to enhance the system performance in traditional point to point OFDM systems and is achieved by applying the water-filling algorithm such that large amount of power is loaded on the sub-carriers which have high SNR values. The power allocation problems are formulated in two different ways. First, the objective is to maximize the system throughput given the constrained transmission power. The second aims to minimize the transmission power while providing a minimum QoS. In relay aided communication, the fading of different channels are mutually independent such that the sub-carriers which experience deep fading over one hop may not face deep fading over the next hop. With this fact, the reception and transmission over the same sub-carrier is clearly sub-optimal and could result in severe performance loss. Therefore, pairing the sub-carriers from different hops 9
1.4 Resource Allocation Problem is important to enhance the transmission rate. The first work on the sub-carrier pairing problem was reported in [15] where the OFDM modulated single user dual-hop relay network is discussed. It was proved that the system throughput can be increased if the sub-carriers on the two hops are coupled in the order of their channel magnitudes. This work was further exploited in [16], where a suboptimal carrier coupling algorithm was presented for multi-relay scenario. However, both [15] and [16] did not consider the power allocation which may change the effective channel magnitude. In [17], the authors proposed a joint power allocation and sub-carrier pairing algorithm for single user single relay network under different power constraints. On the other hand in multiple user scenario, the existence of the users at different locations introduces multi-user diversity where a particular sub-carrier undergoes different fading attenuation for different users. To exploit the multiuser diversity and to avoid the inter-user interference, Orthogonal Frequency Division Multiplexing (OFDMA) has been widely adopted in the wireless communication networks. In OFDMA transmission, each user is assigned a disjoint set of sub-carriers such that each sub-carrier is assigned to a unique user based on a given criteria, e.g., to a user which results in least attenuation. The sub-carrier allocation has almost always been considered with the other resource allocation in OFDMA networks. Generally speaking, the resource allocation problem can be divided into two categories: the overall system throughput maximization problem and the fair resource allocation problem. In throughput maximization problem, the sub-carriers are allocated in such a way that the sum rate of all users is maximized. However, this scheme lacks the fairness among user because more sub-carriers could be allocated to the users which have good channels. Under the fair resource allocation problem, each users is granted a fair share of resources. However, on the other hand, this schemes can have severe negative effects on the overall performance because more resource will be gone to the users which are in bad channel conditions. In this thesis, we focus on the overall system performance enhancement problem to avoid the wastage 10
Page 1 and 2: Resource Allocation in OFDM Based W
Page 3 and 4: Dedications: To my family
Page 5 and 6: Acknowledgment I am greatly thankfu
Page 7 and 8: Contents 2.3.3 Proposed Low-Complex
Page 9 and 10: Abstract The combination of relay t
Page 11 and 12: List of Tables 3.1 Complexity compa
Page 13 and 14: List of Figures 4.1 System model fo
Page 15 and 16: List of Acronyms IEEE MU RS AWGN OW
Page 17 and 18: 1.1 Overview of Relay Networks wire
Page 19 and 20: 1.2 Overview of OFDM Figure 1.2: Th
Page 21 and 22: 1.3 Basics of the Optimization Theo
Page 23: 1.3 Basics of the Optimization Theo
Page 27 and 28: 1.5 Contribution and Organization o
Page 29 and 30: 1.5 Contribution and Organization o
Page 31 and 32: 2.1 Introduction allocated to a nod
Page 33 and 34: 2.1 Introduction The main contribut
Page 35 and 36: 2.2 System Model where h m,k denote
Page 37 and 38: 2.3 Resource Allocation Schemes opt
Page 39 and 40: 2.3 Resource Allocation Schemes ( )
Page 41 and 42: 2.3 Resource Allocation Schemes and
Page 43 and 44: 2.3 Resource Allocation Schemes tha
Page 45 and 46: 2.3 Resource Allocation Schemes 2.3
Page 47 and 48: 2.4 Generalization to Multiple Rela
Page 49 and 50: 2.4 Generalization to Multiple Rela
Page 51 and 52: 2.5 Simulation Results • OptSol/J
Page 53 and 54: 2.5 Simulation Results 0.9 0.85 0.8
Page 55 and 56: 2.6 Summary 2.6 2.4 2.2 2 Rate (bit
Page 57 and 58: 2.6 Summary 2.4 2.2 2 1.8 N=4 N=3 N
Page 59 and 60: 3.1 Introduction A new technology c
Page 61 and 62: 3.1 Introduction • Broadcast Phas
Page 63 and 64: 3.2 System Model MU MU 3 8 A 1 2 7
Page 65 and 66: 3.4 Joint Resource Allocation Schem
Page 67 and 68: 3.4 Joint Resource Allocation Schem
Page 69 and 70: 3.5 Step-Wise Low-Complexity Resour
Page 71 and 72: 3.6 Simulation Results and SNR B m,
Page 73 and 74: 3.6 Simulation Results 3 2.5 2 Uppe
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3.7 Summary 1.8 1.6 1.4 JntOpt SubO
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4.1 Introduction • Non-orthogonal
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4.3 Cooperative Non-Orthogonal Tran
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4.4 Optimization under Orthogonal T
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4.4 Optimization under Orthogonal T
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4.5 Simulations Then, the over all
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4.5 Simulations 40 30 20 Sum−ρ S
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4.6 Summary 0.9 0.8 0.7 JPSC Pow EP
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Chapter 5 Lifetime Maximization in
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5.1 Introduction Figure 5.2: Linear
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5.2 System Model antenna that canno
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5.4 Lifetime Maximization Scheme 5.
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5.4 Lifetime Maximization Scheme wh
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5.5 Simulation Results 150 OPT−SO
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5.6 Summary Lifetime (S) 150 100 50
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Chapter 6 Resource Allocation in Co
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7. Conclusions were considered for
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Bibliography [12] A. Peled, and A.
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Bibliography [36] Z. Luo and S. Zha
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Bibliography [61] D. H. N. Nguyen,
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Bibliography [84] A. Goldsmith, S.
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Bibliography [105] Y. Li, W. Wang,
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Appendix A Derivations of Closed-Fo
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B. Derivations of the Optimal Power
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