Kuo-ng Chu

Survivability and performance optimization of mobile wireless communication networks in the event of base station failure

In this paper, we investigate the survivability of mobile wireless communication networks in the event of base station (BS) failure. A survivable network is modeled as a mathematical optimization problem in which the objective is to minimize the total amount of blocked traffic. We apply Lagrangean relaxation as a solution approach and analyze the experiment results in terms of the blocking rate, service rate, and CPU time. The results show that the total call blocking rate (CBR) is much less sensitive to the call blocking probability (CBP) threshold of each BS when the load is light, rather than heavy; therefore, the more traffic loaded, the less the service rate will vary. BS recovery is much more important when the network load is light. However, the BS recovery ratio (BSRR), which is a key factor in reducing the blocking rate for a small number of BSs, is more important when a system is heavily loaded. The proposed model provides network survivability subject to available resources. The model also fits capacity expansion requirements by locating mobile/portable BSs in the places they are most needed.

Adaptive channel reservation for call admission control to support prioritized soft handoff calls in a cellular CDMA system

This paper proposes a prioritized call admission control (CAC) model to support soft handoff calls with quality of service (QoS) assurances for both the uplink and downlink connections in a CDMA system. CAC is formulated as a combinatorial optimization problem in which the problem objective is to minimize the handoff forced termination rate. The model, which is based on the adaptive channel reservation (ACR) scheme for prioritized calls, adapts to changes in handoff traffic where the associated parameters (reserved channels, and new and handoff call arrival rates) can be varied. To solve the optimization model, iteration-based Lagrangean relaxation is applied by allocating a time budget. We express our achievements in terms of the problem formulation and performance improvement. Computational experiments demonstrate that the proposed ACR scheme outperforms other approaches when there are fewer rather than more channels, and it reduces the handoff call blocking rate more efficiently when the handoff traffic is heavily loaded. Moreover, the model can be adapted to any kind of reservation service.

Integrated planning and capacity management of survivable DS-CDMA networks

In this paper, we jointly investigate both planning and survivability problems for DS-CDMA networks, which is modeled as a mathematical optimization formulation in terms of deploying cost minimization. We apply Lagrangean relaxation as a solution approach. Based on computational experiments, the proposed algorithm is calculated with much more improvements than other primal heuristic. This paper concludes that survivability is a time-consuming and expensive factor. For more efficiency, it is suggested that in the stage of network planning, the planning of normal condition (without considering failure states) is appropriate. A new model considering survivability and performance management can be developed when it is needed.

An Admission Control-based Benefit Optimization Model for Mobile Communications: the Effect of a Decision Time Budget

In mobile communication systems, a soft handoff (SHO) technique is used to optimize the quality and capacity of communications. However, because the handoff process incurs a high overhead there must be a tradeoff between the system capacity and the handoff overhead. In this paper, we propose a benefit optimization model for mobile communications. The model tries to maximize the overall system capacity by considering SHO process overhead and quality of service requirements jointly. We first construct a framework of admission policies and devise an appropriate admission control policy, which is then used to analyze the system benefit. The service rate is defined by three measures: the call blocking ratio, system load, and admit-to-existence ratio; while the solution quality is defined by the gap between the upper bound and lower bound of the objective function value. By applying iteration-based Lagrangian relaxation as a solution approach, a time budget is allocated to each iteration so that admission control can be implemented. To fulfill the continuous admission process requirements in the long-term, users’ demands are randomly distributed via a simulation process. The goal of this paper is to investigate the effect of the admission control policy on the system benefit, service rate and solution quality. Experiment results are presented to demonstrate the efficacy of both the proposed model and the solution approach.

Minimum-Cost QoS-Constrained Deployment and Routing Policies for Wireless Relay Networks

With the continued evolution of wireless communication technology, relaying is one of the features proposed for the 4G LTE Advanced (LTE-A) system. The aim of relaying is to enhance both coverage and capacity. The idea of relays is not new, but relaying is being considered to ensure that the optimum performance is achieved to enable the expectations or good quality of service (QoS) of the users to be met while still keeping capital expenditure (CAPEX) within the budgeted bounds of operators. In this paper, we try to stand for an operator to propose a solution that determines where and how many relays should be deployed in the planning stages to minimize the development cost. In the planning stages, we not only derive a multicast tree routing algorithm to both determine and fulfill the QoS requirements to enhance throughput, but we also utilize the Lagrangian relaxation (LR) method in conjunction with optimization-based heuristics and conduct computational experiments to evaluate the performance. Our contribution is utilizing the LR method to propose an optimal solution to minimize the CAPEX of operators to build up a relay network with more efficiency and effectiveness and the QoS can be guaranteed by service level agreement.

The effect of call admission policies on the system benefit of CDMA communication networks

Previous studies of call admission control (CAC) in mobile communication networks focused on call blocking and call dropping mechanisms. However, achieving global optimization of the system benefit is a complicated process. In this paper, we propose a benefit optimization model that accommodates as many users as possible, while simultaneously maintaining system-wide quality of service (QoS) in terms of admission control. To clarify the CAC concept, we construct a framework of CAC policies, derive associated interference models based on the framework, and then investigate the effects of the policies on the system benefit. In addition, to solve the complicated integer programming problem, we adopt the Lagrangean relaxation approach, and employ Lagrangean multipliers to perform sensitivity analysis of several parameters. The contribution of this study is twofold: the novel problem formulation and the improvement in the system benefit. The computational results demonstrate that the system accrues more benefit as new traffic is loaded and the number of users increases. Meanwhile, the sensitivity analysis shows that proper assignment of the strength of power-controlled signals is a key factor in the global optimization of the system benefit.

Modeling of Adaptive Load Balancing with Hybrid F/CDMA and Sectorization Schemes in Mobile Communication Networks

In this paper, we investigate the load balancing problem in mobile communications by considering sectorization and a hybrid F/CDMA scheme (HFCS) jointly in the scenario of uneven traffic distributions. The problem is formulated as a combinatorial optimization model, subject to quality of service (QoS) requirements, and solved by the Lagrangean relaxation approach. In addition, Lagrangean multipliers are used to conduct sensitivity analysis. The model’s objective is to minimize the weighted call blocking rate in terms of the distribution diversity. The model’s performance is evaluated by the proposed HFCS, which is an adaptive scheme (AS). We compare the performance of AS with that of a non-adaptive (NA) scheme, which is a common power control method. Experiment results show that combining sectorization with the bandwidth segmentation scheme provides effective adaptive load balancing (ALB). The performance improvement achieved by the proposed adaptive scheme over the common power control scheme is as high as 68%. Moreover, under the scheme, the performance improves as the traffic load increases. Load balancing improves even further when AS is combined with the sectorization.

Network planning and capacity management considering adaptive sectorization in survivable FDMA/CDMA systems

In this paper, we investigate the integrated problem of survivable CDMA network planning and management. The problem is formulated as a combinatorial optimization formulation in terms of deploying cost minimization. Solution approach to the development algorithm is Lagrangean relaxation. In experiment results, the proposed algorithm is shown to be more effective and achieves up to 25% reduction on the total deployment cost over a simple algorithm. It also takes around 30% expenses to guarantee survivability

An admission control algorithm for CDMA networks

This paper proposes an admission control algorithm for CDMA networks, from which a revenue optimization problem is formulated as a mixed integer problem. The objective of the optimization problem is to maximizing total system revenue subject to capacity as well as QoS constraints. The approach for solving revenue optimization problem is Lagrangean relaxation in conjunction with a heuristic. The experiments consider total system revenue with respective to voice activity factor WAF) and signal-tointerference (SIR) on 500 test cases which are within 9 base stations, 50 existing mobile stations, as well as 50 new mobile stations. Computational results illustrate that the solution quality of error gap less than 5.0% is with percentile 0.99. Proposed algorithm is calculated with near-optimal solution. Index Termsadmission control algorithm, CDMA networks, Lagrangean relaxation, mathematical formulation, optimization model

PERFORMANCE ANALYSIS OF ADMISSION CONTROL ALGORITHMS FOR CDMA NETWORKS

This paper proposes a modified mathematical formulation of revenue optimization problem in terms of CDMA admission control. The problem solution is based upon proposed algorithm as well as Lagrangean relaxation approach. Performance analysis on three algorithms with respect to voice activity factor (VAF) is considered, where 9 base stations, 50 existing mobile stations, and new mobile stations in Poisson arrival process (λ=100) on 500 test cases are given. Computational results illustrate that no matter which value of VAF is given; proposed algorithm always is with an outstanding performance on solution optimality, blocking rate, as well as revenue contribution.