Call Admission Control And Handover Management Scheme In LEO Satellite Networks

Due to the inherent advantages of seemless global coverage, large system capacity, and low propagation delay, Low Earth Orbit (LEO) satellite networks have shown to be a prospective technical resolution to the next generation broadband satellite communication system. Call Admission Control (CAC) and handover management schemes are substantial Radio Resource Management (RRM) techniques to avoid disruption of ongoing calls and to improve the overall system efficiency. In LEO satellite networks, CAC and handover management schemes should be more sophisticated designed taking account of the unique features of the network, such as limited bandwidth, topological dynamics, wide range of services, and wireless channel impairments owing to different types of fading and adjacent signal interference. Focusing on the call-level system performance, the thesis aims at designing effective and practical CAC and handover management schemes under different application scenarios. The main contributions of our work are organized as follows:1. An effective approach for minimizing forced termination probability in LEO satellite networks is to reserve channels before handover occurrence. In this case although no delay is imposed, inevitable increasing of blocking probability is undedisirable. To characterize the user mobility and the handover generation process, firstly we study the footprint of LEO satellite constellation and build up a homogeneous and memoryless mobility model. It is possible to predict statistically the channel holding time and the handover traffic load, thereby helping to overcome the problem of inefficient resource utilization in conservative reservation schemes. A novel Threshold-Based Handover Prioritization (TBHP) sheme in homogeneous traffic conditions is proposed by introducing a time threshold parameter, according to which the reservation requests are deferred to increase the chance of new call access and improve the system resource utilization. Analytical and simulation results show that when the time threshold value is properly set, TBHP sheme is effective to balance the tradeoffs between new call blocking probability and forced termination probability, so as to achieve a higher performance. Another advantage is that different values of time threshold parameter can be utilized to different satellites/spotbeams, according to the offered traffic load.2. With the arrival of broadband mobile satellite services, the main problem of CAC and handover management scheme in heterogeneous traffic LEO satellite networks is to guarantee individual QoS with limited bandwidth resources. The main contributions of this part are the proposal of a new Multi-Threshold Channel Reservation (MTCR) policy and the analytical framework of the call-level performance of CAC and handover management scheme for heterogeneous traffic. The proposed MTCR policy exploits the homogeneous and memoryless property of LEO satellite networks mobility model, and extending the classic channel reservation method to heterogeneous traffic environment with diverse QoS requirements. Traffic differentiation can be performed by setting different admission bandwidth thresholds for new and handover calls of each service type such that the higher priority call/service will be given preferentially treatment. Moreover, the stationary distribution of the system state under MTCR policy has a product form, and the system performance can be evaluated through efficient convolution algorithms. Thus, the commonly confronted state spce explosion problem in modeling a system with high capacity and more service types is circumvented. Extensive simulation results validate the analytical model, and show that MTCR policy can meet individual QoS requirements and achieve higher overall performace by setting a proper threshold parameter vector.3. The optimal CAC and handover management scheme in LEO satellite networks is researched, generally falling into two parts– the objective function and the optimization algorithm. It is desirable to implement a CAC and handover management scheme that optimizes certain performance metrics, which are always defined in the long term or at the steady state. Firstly the revenue function concept in economics is referenced to formulate the optimization problem as a system revenue rate function. The deriving of optimal MTCR (OMTCR) policy that maximizes the revenue rate function is expressed as solving unconstrained and QoS-constrained nonlinear programming problem. After that, intelligent computing technique is used to find optimal or suboptimal policy, taking into account that optimal policy is not necessarily attainable, particularly in realistic scenarios with a large problem size and complicated system parameter interdependence. A new modified Genetic Algorithm (GA) adapting for the particular feasible points and QoS-constraints in OMTCR problem is addressed to derive the optimum threshold vector offline. The statistical average and sampling results show that the modified GA achieves high accuracy in reasonable runtime, thus ensuring the practicality of OMTCR policy in LEO satellite networks. However, since the number of threshold vectors grows exponentially with the service classes and the cell capacity, the contradiction between initial population size and optimal solution accuracy will arise with large problem size of future system. Finally to cope with this problem, we further develop a small initial population iterative GA optimizing scheme, which also has some engineering application value.4. Although greatly enhancing transmission reliability and system throughput, adaptive modulation brings new challenges for CAC and handover management scheme in future LEO satellite networks. Since the spectral efficiency varies as the transmission mode, the QoS requirements are not surely guaranteed in deep fading conditions even if larger bandwidth is allocated to the traffic. In this case a statistical CAC and handover management scheme at the call-level should be designed jointly with the adaptive modulation in fading channels. First the LEO satellite channel fading characteristics are summarized, and then the channel fading state probability distribution in discrete rate Multi-level Quadrature Amplitude Modulation (M-QAM) transmission is studied for the pratical reason. Based on this performance analysis, a novel OVerload-probability-based Channel Reservation (OVCR) scheme is proposed to extend the MTCR scheme to the statistical channel conditions. The cross-layer design, which meets the target Bit Error Rate (BER) at the physical layer, restricts the system overload probability below the predetermined threshold and maximizes the system revenue rate. Numerical results illustrate the improvement of system performance under the joint design of OVCR and M-QAM. We also demonstrated applications of the proposed cross-layer analytical framework to obtain the optimal or suboptimal OVCR policy threshold vector.