Research On Resource Management Algorithms In Heterogeneous Integration Networks

With the rapid development of wireless communication technologies, an integration of multiple wireless networks based on different access technologies forms a heterogeneous wireless network environment. Wireless resource management is the key technology to realize the network resource optimization and guarantee the quality of service (QoS) for users. This dissertation focuses on the wireless resource management algorithms in heterogeneous integrated networks, which include a dynamic load transferring algorithm based on the priority for the Cellular/WLAN integrated network, an adaptive bandwidth allocation algorithm based on multi-threshold reservation mechanism, a dynamic bandwidth allocation algorithm based on the transmission rate adaptation, a co-channel interference mitigation algorithm based on preset thresholds cross-tier handover and a co-channel interference suppressing algorithm based on joint sub-channel and power allocation.The main contributions of this dissertation are as follows.1. For the resource reconfiguration in the cellular and wireless local area network (WLAN) integrated network, a priority-based dynamic load transferring (PDLT) algorithm is proposed. When there is no bandwidth resource available in the cellular network or WLAN, an incoming voice call or data call within the overlapping area of the cellular network and the WLAN will be directed to the spare network. Meanwhile, by dynamically computing the occupancy of the bandwidth resource, an ongoing voice call or data calls will also be transferred to the network with sufficient bandwidth resource according to the given threshold to balance the number of voice/data calls in the two networks. The numerical analysis and system simulation results show that the PDLT algorithm can effectively enhance the whole integrated network’s traffic, reduce the blocking probability of new calls and increase the throughput, and thus decrease the response time for various services.2. For the adaptive bandwidth allocation with user QoS guarantees in the heterogeneous integrated networks, an adaptive bandwidth allocation algorithm based on multi-threshold reservation mechanism is proposed. With the bandwidth reservation mechanism by setting multi-threshold in each network for every traffic, the adaptive bandwidth allocation scheme according to the transmission rate levels requirements and the network status can be formulated as an optimization with the constraints of the bandwidth allocation matrix for each traffic and all users based on the multi-homing technology. A procedure of the iterative method is presented to solve the optimization of the formulated adaptive bandwidth allocation scheme and the network throughput is maximized under bandwidth reserving thresholds and network capacity constrains. Numerical simulation results show that the proposed algorithm can support QoS requiring transmission rate grades, decrease the new call blocking probability, increase the average user access rate and improve the network throughput of the heterogeneous wireless network.3. For the dynamic bandwidth allocation in the multi-network coexistence scenario of the heterogeneous integrated networks, a dynamic bandwidth allocation algorithm based on the transmission rate adaptation is proposed. Based on the proposed transmission rate priority decision model, an optimal bandwidth reallocation matrix is obtained by dynamically adjusting users’ transmission rates to maximize the utility function of entire heterogeneous network under the transmission rate QoS requirements and capacity constraints. The adaptive bandwidth reallocation is formulated as an optimization and a dynamic optimal iterative procedure is used to adjust adaptively users’transmission rates to maximize network utility function. The results of theoretical analysis and numerical simulation show that the proposed algorithm can maximize the network utility function and reduce the new calls blocking probability as well as guaranteeing the transmission rate and QoS requirements of the users.4. For the co-channel interference mitigation in the Macro-Femto co-channel integrated network, a co-channel interference mitigation algorithm based on preset thresholds cross-tier handover is proposed. Based on the proposed cell Time-to-Stay (TTS) prediction model and co-channel interference analysis model and using a preset threshold cross-tier handover policy, both the TTS of a Macrocell User Equipment (MUE)/Femtocell User Equipment (FUE) in a Femtocell/the Macrocell, and the received Signal to Interference plus Noise Ratio (SINR) at a Femtocell Access Point (FAP)/the Macrocell Base Station (MBS) as well as the preset TTS and SINR thresholds are taken into account in making a cross-tier handover decision for an MUE/FUE to mitigate the co-channel interference and the network performance of the proposed algorithm with the minimum power transmission and the optimal power transmission is analyzed, respectively. Numerical simulation results show that the proposed algorithm can significantly improve the network performance in terms of the outage probability, user sum rate, and network capacity.5. For the interference suppression based on resource allocation in the Macro-Femto co-channel integrated network, a co-channel interference suppressing algorithm based on joint sub-channel and power allocation is proposed. Power control and handover mechanism can be used to suppress the co-channel cross-tier and intra-tier interference achieved by the power allocation for Macrocell User (MU) and joint sub-channel and power allocation for Femtocell Users (FUs), respectively. Mathematically, the cross-tier handover is formulated as optimizing the network throughput under the constraints of each tier target outage probability and the interference-aware resource allocation is formulated as optimizing the sum rate of FUs subject to the constraints of the target data rate of handover MU and interference thresholds to other MUs and FUs. Theoretical analysis and numerical simulation results show that the sum rate of FUs can be increased greatly. Meanwhile, the Femtocell network capacity and the number of deployable Femtocells can also be improved because of the co-channel interference suppression.