Resource Allocation Strategies Study In Broadband Wireless Communication System

OFDM (Orthogonal Frequency Division Multiplexing) has become one key physical-layer technology in the future BWCS (broadband wireless communication system), and has been applied in various B3G systems, such as LTE, WiMAX. Lots of research is carried out on utilizing OFDM as a physical-layer multi-carrier modulation technology, but more deep discussion on OFDM resource allocation is still required because it employs OFDM as a multiple-access manner.Compared to the single-user OFDM system, the multi-user one is able to exploit multi-dimensional diversity gain, including frequency diversity, time diversity, multi-user diversity, space diversity (deploying multi-antenna) and so on. However, the amount of actual gain is decided by the selection for resource allocation strategies. Therefore, only flexible and practical resource allocation strategies can guarantee high frequency efficiency for system and excellent QoS (Quality of Service) performance for users in the future BWCS.This dissertation focuses on multi-user OFDM resource allocation. It is well known that a lot of key technologies in mobile communication system are proposed to combat threefold dynamics: channel dynamics, user dynamics and traffic dynamics. The research of this dissertation is also related to them. Chapter 2 discusses resource allocation schemes in case of small-scale multi-path channel dynamics; Chapter 3 investigates how channel quantization affects small-scale muti-path channel dynamics, and hence degrades system capacity. Then, this chapter chooses an appropriate channel quantization scheme to maximize the total system capacity; Chapter 4 extends channel dynamics to the joint effect of large-scale propagation loss, shadow fading as well as small-scale multi-path fading, and analyzes how to effectively allocate OFDM resource in a single cell. Chapter 5 introduces distributed multi-antenna into the cell, which decreases channel dynamics, improves channel condition, and thus enhances the resource allocation performance in OFDM system. Chapter 6 also designs resource allocation schemes in OFDM DAS (distributed antenna system) while taking both user and traffic dynamics into consideration.The contents of this dissertation range from resource allocation in OFDM system to that in OFDM DAS. With the deployment of distributed multi-antenna, system model becomes more complicated. The major work and conclusions of this dissertation can be detailedly described as follows:Chapter 2 studies uplink/downlink resource allocation in the special OFDM system, where different users have equal path loss. For downlink, a power transfer algorithm is proposed, and the convergence is proved. The proposed algorithm can achieve almost the same capacity as optimal power allocation, but holds a lower computational complexity. A low-complexity downlink resource allocation scheme can be formed by combining grouped subcarrier assignment and the proposed algorithm. This chapter also simulates the effect of different channel parameters, such as the number of multi-path, maximum delay spread, subcarrier bandwidth, on the scheme performance. This is capable of guiding parameter selection when realizing the scheme in the actual system. For uplink, this chapter finds the user capacity-saturation problem, and avoids that saturated users always take up resource by dynamically changing the set of users who are waiting for resource allocation. It helps to raise the total system capacity.Chapter 3 discusses OFDM resource allocation problem in condition of partial CSI (channel state information). Ideally, CSI design and resource allocation should be optimized jointly to reach the optimum of the system performance. Nevertheless, the majority of existing papers consider resource allocation optimization problem with partial CSI. This chapter attempts to investigate the problem from another point of view, and tries to address channel quantization design problem while selecting maximum SNR (signal-to-noise ratio) as resource allocation scheme. A multi-user channel probability quantization scheme is proposed by equal power assumption and theoretical derivation. The proposed scheme can obtain much higher capacity than equal amplitude quantization if provided the same uplink feedback bandwidth. Thus, this scheme succeeds in reducing feedback bandwidth, and boosts the application of OFDM system.Chapter 4 investigates resource allocation problem in a cell of OFDM system. Even though the existing papers all assume equal power allocation for each subcarrier on the overall bandwidth, it is difficult to ensure that different users hold the same short/middle-term average of channel gain since wireless environment and location vary from users to users. Different initial power settings for different users are needed to eliminate channel condition difference and improve inter-user fairness. This chapter introduces an initial-power optimization model, solves the model by numerical method, and then implements subcarrier assignment and swapping based on obtained initial-power allocation. These steps construct the proposed subcarrier algorithm, which significantly betters fairness among users. Simulation results show that the proposed algorithm combined with optimal power allocation greatly enlarges system capacity, increases frequency efficiency, and is a cost-efficient resource allocation scheme in a cell of OFDM system.Chapter 5 studies resource allocation in OFDM DAS. By deploying distributed antennas in the cell, OFDM DAS remarkably lowers channel dynamics, and upgrades users' channel condition. This chapter achieves optimal resource allocation algorithm, and derives the capacity of the single-user OFDM DAS and OFDM CAS. Simulated results maintain consistent with theoretical derivation. The following conclusions can be drawn from simulation results: 1) OFDM DAS considerably increases system rate-sum capacity; 2) Compared to water-filling, equal power allocation results in negligible capacity loss for OFDM DAS; 3) the capacity of OFDM DAS has close relations with the number of antennas and the site of antennas. How antennas are deployed in actual system should adapt to user density distribution in order to attain a cost-effective scheme. Chapter 6 further investigates resource allocation in OFDM DAS with introducing both user and traffic dynamics to system and channel model. This chapter proposes a resource allocation scheme which is suitable for min-rate guaranteed best-effort services. The scheme consists of two parts: the former aims to satisfy users' min-rate requirements, whereas the objective of the latter is to increase system capacity. The scheme proposed by this chapter needs implementing once every frame, and can achieve time, frequency, space, user diversity gain. It effectively fulfills users' service demands, and surpasses timeslot-based resource allocation in terms of supporting users' traffic dynamics. Simulation results also show that OFDM DAS outperforms OFDM CAS when adapting to traffic characteristics. It could conclude that distributed antenna is a powerful technology to enhance the performace in the future communication system.Capacity bottleneck for the future BWCS lies in wireless AN (access network), and OFDM technology is ready for breaking capacity restriction for AN. However, actual capacity rise in OFDM system is mainly determined by resource allocation strategies. That is the reason why resource allocation strategies selection for OFDM system is of great importance for providing high-rate services in the future BWCS. Work of this dissertation starts in the aforementioned context. Related research productions have published in IEEE conferences or international/domestic journals, and some of them have applied for patents.