Integrated channel assignment and power control in wireless mobile networks using evolutionary strategy.

In wireless mobile communication system, radio spectrum is a limited resource. However, efficient use of available channels has been shown to improve the system capacity. The role of a channel assignment scheme is to allocate channels to cells or mobiles in such a way as to minimize call blocking or call dropping probabilities, and also to maximize the quality of service. Channel assignment is known to be an NP-hard optimization problem. In this thesis, we have developed an Evolutionary Strategy (ES) which optimizes the channel assignment. The proposed ES approach uses an efficient problem representation as well as an appropriate fitness function. Our thesis deals with a novel hybrid channel assignment based scheme called D-ring. Our D-ring method yields a faster running time and simpler objective function. We also propose a novel way of generating initial candidate solutions that are near optimal. We have obtained at least better results (as well as faster running time) than a similar approach in literature. The efficient use of available channels and transmitter power have been shown to improve the system capacity. The role of power control is to assign power level to each transmitter so that the signal quality is maintained and interference is minimized. Existing papers have focused on optimizing the assignment of channels assuming that the allocation of transmitter power is known and fixed (vice-versa). In this thesis, we integrate the problem of channel assignment with power control using the dynamic reuse distance concept. Using an efficient problem representation as well as an appropriate fitness function, we develop an evolutionary strategy which concurrently optimizes channel assignment and power control. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2003 .V52. Source: Masters Abstracts International, Volume: 42-03, page: 0976. Adviser: Alioune Ngom. Thesis (M.Sc.)--University of Windsor (Canada), 2003

Energy-Efficient Heterogeneous Cellular Networks with Spectrum Underlay and Overlay Access

In this paper, we provide joint subcarrier assignment and power allocation schemes for quality-of-service (QoS)-constrained energy-efficiency (EE) optimization in the downlink of an orthogonal frequency division multiple access (OFDMA)-based two-tier heterogeneous cellular network (HCN). Considering underlay transmission, where spectrum-efficiency (SE) is fully exploited, the EE solution involves tackling a complex mixed-combinatorial and non-convex optimization problem. With appropriate decomposition of the original problem and leveraging on the quasi-concavity of the EE function, we propose a dual-layer resource allocation approach and provide a complete solution using difference-of-two-concave-functions approximation, successive convex approximation, and gradient-search methods. On the other hand, the inherent inter-tier interference from spectrum underlay access may degrade EE particularly under dense small-cell deployment and large bandwidth utilization. We therefore develop a novel resource allocation approach based on the concepts of spectrum overlay access and resource efficiency (RE) (normalized EE-SE trade-off). Specifically, the optimization procedure is separated in this case such that the macro-cell optimal RE and corresponding bandwidth is first determined, then the EE of small-cells utilizing the remaining spectrum is maximized. Simulation results confirm the theoretical findings and demonstrate that the proposed resource allocation schemes can approach the optimal EE with each strategy being superior under certain system settings

Ant colony optimisation-based algorithms for optical burst switching networks

This research developed two novel distributed algorithms inspired by Ant Colony Optimisation (ACO) for a solution to the problem of dynamic Routing and Wavelength Assignment (RWA) with wavelength continuity constraint in Optical Burst Switching (OBS) networks utilising both the traditional International Telecommunication Union (ITU) Fixed Grid Wavelength Division Multiplexing (WDM) and Flexible Spectrum scenarios. The growing demand for more bandwidth in optical networks require more efficient utilisation of available optical resources. OBS is a promising optical switching technique for the improved utilisation of optical network resources over the current optical circuit switching technique. The development of newer technologies has introduced higher rate transmissions and various modulation formats, however, introducing these technologies into the traditional ITU Fixed Grid does not efficiently utilise the available bandwidth. Flexible Spectrum is a promising approach offering a solution to the problem of improving bandwidth utilisation, which comes with a potential cost. Transmissions have the potential for impairment with respect to the increased traffic and lack of large channel spacing. Proposed routing algorithms should be aware of the linear and non-linear Physical Layer Impairments (PLIs) in order to operate closer to optimum performance. The OBS resource reservation protocol does not cater for the loss of transmissions, Burst Control Packets (BCPs) included, due to physical layer impairments. The protocol was adapted for use in Flexible Spectrum. Investigation of the use of a route and wavelength combination, from source to destination node pair, for the RWA process was proposed for ACO-based approaches to enforce the establishment and use of complete paths for greedy exploitation in Flexible Spectrum was conducted. The routing tuple for the RWA process is the tight coupling of a route and wavelength in combination intended to promote the greedy exploitation of successful paths for transmission requests. The application of the routing tuples differs from traditional ACO-based approaches and prompted the investigation of new pheromone calculation equations. The two novel proposed approaches were tested and experiments conducted comparing with and against existing algorithms (a simple greedy and an ACO-based algorithm) in a traditional ITU Fixed Grid and Flexible Spectrum scenario on three different network topologies. The proposed Flexible Spectrum Ant Colony (FSAC) approach had a markably improved performance over the existing algorithms in the ITU Fixed Grid WDM and Flexible Spectrum scenarios, while Upper Confidence Bound Routing and Wavelength Assignment (UCBRWA) algorithm was able to perform well in the traditional ITU Fixed Grid WDM scenario, but underperformed in the Flexible Spectrum scenario. The results show that the distributed ACO-based FSAC algorithm significantly improved the burst transmission success probability, providing a good solution in the Flexible Spectrum network environment undergoing transmission impairments

Jointly Optimizing Placement and Inference for Beacon-based Localization

The ability of robots to estimate their location is crucial for a wide variety of autonomous operations. In settings where GPS is unavailable, measurements of transmissions from fixed beacons provide an effective means of estimating a robot's location as it navigates. The accuracy of such a beacon-based localization system depends both on how beacons are distributed in the environment, and how the robot's location is inferred based on noisy and potentially ambiguous measurements. We propose an approach for making these design decisions automatically and without expert supervision, by explicitly searching for the placement and inference strategies that, together, are optimal for a given environment. Since this search is computationally expensive, our approach encodes beacon placement as a differential neural layer that interfaces with a neural network for inference. This formulation allows us to employ standard techniques for training neural networks to carry out the joint optimization. We evaluate this approach on a variety of environments and settings, and find that it is able to discover designs that enable high localization accuracy.Comment: Appeared at 2017 International Conference on Intelligent Robots and Systems (IROS

Control Aware Radio Resource Allocation in Low Latency Wireless Control Systems

We consider the problem of allocating radio resources over wireless communication links to control a series of independent wireless control systems. Low-latency transmissions are necessary in enabling time-sensitive control systems to operate over wireless links with high reliability. Achieving fast data rates over wireless links thus comes at the cost of reliability in the form of high packet error rates compared to wired links due to channel noise and interference. However, the effect of the communication link errors on the control system performance depends dynamically on the control system state. We propose a novel control-communication co-design approach to the low-latency resource allocation problem. We incorporate control and channel state information to make scheduling decisions over time on frequency, bandwidth and data rates across the next-generation Wi-Fi based wireless communication links that close the control loops. Control systems that are closer to instability or further from a desired range in a given control cycle are given higher packet delivery rate targets to meet. Rather than a simple priority ranking, we derive precise packet error rate targets for each system needed to satisfy stability targets and make scheduling decisions to meet such targets while reducing total transmission time. The resulting Control-Aware Low Latency Scheduling (CALLS) method is tested in numerous simulation experiments that demonstrate its effectiveness in meeting control-based goals under tight latency constraints relative to control-agnostic scheduling

Optimal channel allocation with dynamic power control in cellular networks

Techniques for channel allocation in cellular networks have been an area of intense research interest for many years. An efficient channel allocation scheme can significantly reduce call-blocking and calldropping probabilities. Another important issue is to effectively manage the power requirements for communication. An efficient power control strategy leads to reduced power consumption and improved signal quality. In this paper, we present a novel integer linear program (ILP) formulation that jointly optimizes channel allocation and power control for incoming calls, based on the carrier-to-interference ratio (CIR). In our approach we use a hybrid channel assignment scheme, where an incoming call is admitted only if a suitable channel is found such that the CIR of all ongoing calls on that channel, as well as that of the new call, will be above a specified value. Our formulation also guarantees that the overall power requirement for the selected channel will be minimized as much as possible and that no ongoing calls will be dropped as a result of admitting the new call. We have run simulations on a benchmark 49 cell environment with 70 channels to investigate the effect of different parameters such as the desired CIR. The results indicate that our approach leads to significant improvements over existing techniques.Comment: 11 page

Optimization Framework and Graph-Based Approach for Relay-Assisted Bidirectional OFDMA Cellular Networks

This paper considers a relay-assisted bidirectional cellular network where the base station (BS) communicates with each mobile station (MS) using OFDMA for both uplink and downlink. The goal is to improve the overall system performance by exploring the full potential of the network in various dimensions including user, subcarrier, relay, and bidirectional traffic. In this work, we first introduce a novel three-time-slot time-division duplexing (TDD) transmission protocol. This protocol unifies direct transmission, one-way relaying and network-coded two-way relaying between the BS and each MS. Using the proposed three-time-slot TDD protocol, we then propose an optimization framework for resource allocation to achieve the following gains: cooperative diversity (via relay selection), network coding gain (via bidirectional transmission mode selection), and multiuser diversity (via subcarrier assignment). We formulate the problem as a combinatorial optimization problem, which is NP-complete. To make it more tractable, we adopt a graph-based approach. We first establish the equivalence between the original problem and a maximum weighted clique problem in graph theory. A metaheuristic algorithm based on any colony optimization (ACO) is then employed to find the solution in polynomial time. Simulation results demonstrate that the proposed protocol together with the ACO algorithm significantly enhances the system total throughput.Comment: 27 pages, 8 figures, 2 table