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

Accurate angle-of-arrival measurement using particle swarm optimization

As one of the major methods for location positioning, angle-of-arrival (AOA) estimation is a significant technology in radar, sonar, radio astronomy, and mobile communications. AOA measurements can be exploited to locate mobile units, enhance communication efficiency and network capacity, and support location-aided routing, dynamic network management, and many location-based services. In this paper, we propose an algorithm for AOA estimation in colored noise fields and harsh application scenarios. By modeling the unknown noise covariance as a linear combination of known weighting matrices, a maximum likelihood (ML) criterion is established, and a particle swarm optimization (PSO) paradigm is designed to optimize the cost function. Simulation results demonstrate that the paired estimator PSO-ML significantly outperforms other popular techniques and produces superior AOA estimates

A Comprehensive Survey of Potential Game Approaches to Wireless Networks

Potential games form a class of non-cooperative games where unilateral improvement dynamics are guaranteed to converge in many practical cases. The potential game approach has been applied to a wide range of wireless network problems, particularly to a variety of channel assignment problems. In this paper, the properties of potential games are introduced, and games in wireless networks that have been proven to be potential games are comprehensively discussed.Comment: 44 pages, 6 figures, to appear in IEICE Transactions on Communications, vol. E98-B, no. 9, Sept. 201

Multiuser MIMO-OFDM for Next-Generation Wireless Systems

This overview portrays the 40-year evolution of orthogonal frequency division multiplexing (OFDM) research. The amelioration of powerful multicarrier OFDM arrangements with multiple-input multiple-output (MIMO) systems has numerous benefits, which are detailed in this treatise. We continue by highlighting the limitations of conventional detection and channel estimation techniques designed for multiuser MIMO OFDM systems in the so-called rank-deficient scenarios, where the number of users supported or the number of transmit antennas employed exceeds the number of receiver antennas. This is often encountered in practice, unless we limit the number of users granted access in the base station’s or radio port’s coverage area. Following a historical perspective on the associated design problems and their state-of-the-art solutions, the second half of this treatise details a range of classic multiuser detectors (MUDs) designed for MIMO-OFDM systems and characterizes their achievable performance. A further section aims for identifying novel cutting-edge genetic algorithm (GA)-aided detector solutions, which have found numerous applications in wireless communications in recent years. In an effort to stimulate the cross pollination of ideas across the machine learning, optimization, signal processing, and wireless communications research communities, we will review the broadly applicable principles of various GA-assisted optimization techniques, which were recently proposed also for employment inmultiuser MIMO OFDM. In order to stimulate new research, we demonstrate that the family of GA-aided MUDs is capable of achieving a near-optimum performance at the cost of a significantly lower computational complexity than that imposed by their optimum maximum-likelihood (ML) MUD aided counterparts. The paper is concluded by outlining a range of future research options that may find their way into next-generation wireless systems

Applications of Soft Computing in Mobile and Wireless Communications

Soft computing is a synergistic combination of artificial intelligence methodologies to model and solve real world problems that are either impossible or too difficult to model mathematically. Furthermore, the use of conventional modeling techniques demands rigor, precision and certainty, which carry computational cost. On the other hand, soft computing utilizes computation, reasoning and inference to reduce computational cost by exploiting tolerance for imprecision, uncertainty, partial truth and approximation. In addition to computational cost savings, soft computing is an excellent platform for autonomic computing, owing to its roots in artificial intelligence. Wireless communication networks are associated with much uncertainty and imprecision due to a number of stochastic processes such as escalating number of access points, constantly changing propagation channels, sudden variations in network load and random mobility of users. This reality has fuelled numerous applications of soft computing techniques in mobile and wireless communications. This paper reviews various applications of the core soft computing methodologies in mobile and wireless communications

QoS constrained cellular ad hoc augmented networks

In this dissertation, based on different design criteria, three novel quality of service (QoS) constrained cellular ad hoc augmented network (CAHAN) architectures are proposed for next generation wireless networks. The CAHAN architectures have a hybrid architecture, in which each MT of CDMA cellular networks has ad hoc communication capability. The CAHAN architectures are an evolutionary approach to conventional cellular networks. The proposed architectures have good system scalability and high system reliability. The first proposed architecture is the QoS constrained minimum-power cellular ad hoc augmented network architecture (QCMP CAHAN). The QCMP CAHAN can find the optimal minimum-power routes under the QoS constraints (bandwidth, packet-delay, or packet-error-rate constraint). The total energy consumed by the MTs is lower in the case of QCMP CAHAN than in the case of pure cellular networks. As the ad hoc communication range of each MT increases, the total transmitted power in QCMP CAHAN decreases. However, due to the increased number of hops involved in information delivery between the source and the destination, the end-to-end delay increases. The maximum end-to-end delay will be limited to a specified tolerable value for different services. An MT in QCMP CAHAN will not relay any messages when its ad hoc communication range is zero, and if this is the case for all MTs, then QCMP CAHAN reduces to the traditional cellular network. A QoS constrained network lifetime extension cellular ad hoc augmented network architecture (QCLE CAHAN) is proposed to achieve the maximum network lifetime under the QoS constraints. The network lifetime is higher in the case of QCLE CAHAN than in the case of pure cellular networks or QCMP CAHAN. In QCLE CAHAN, a novel QoS-constrained network lifetime extension routing algorithm will dynamically select suitable ad-hoc-switch-to-cellular points (ASCPs) according to the MT remaining battery energy such that the selection will balance all the MT battery energy and maximizes the network lifetime. As the number of ASCPs in an ad hoc subnet decreases, the network lifetime will be extended. Maximum network lifetime can be increased until the end-to-end QoS in QCLE CAHAN reaches its maximum tolerable value. Geocasting is the mechanism to multicast messages to the MTs whose locations lie within a given geographic area (target area). Geolocation-aware CAHAN (GA CAHAN) architecture is proposed to improve total transmitted power expended for geocast services in cellular networks. By using GA CAHAN for geocasting, saving in total transmitted energy can be achieved as compared to the case of pure cellular networks. When the size of geocast target area is large, GA CAHAN can save larger transmitted energy

Integrated channel assignment and power control in cellular networks using hill-climbing approach.

Recent year\u27s incredible success and exponential growth of wireless cellular network services have necessitated careful management of radio resources to improve system capacity. Mainly due to the insufficiency of radio spectrum, reuse or sharing of radio frequency must be considered. In practical, the sharing of radio frequency introduces interferences among users, which in turn limit the system capacity. On the other hand, control of transmitter power can suppress co-channel interference, adjacent channel interference and limits the consumption of power. Thus channel assignment and power control are two effective means in wireless cellular networks and they are highly correlated to each other. Most of the existing papers have focused on optimizing the assignment of channels assuming that the allocation of transmitter power is known and fixed or vice-versa. In this thesis, we study the integration of channel assignment and power control simultaneously to increase the network capacity and throughput. We have proposed a new channel assignment approach, called HCA-PC (Hybrid Channel Assignment + Power Control) using dynamic reuse distance concept to optimize the channel assignment. We develop a Hill-climbing approach with random restart strategy, using an efficient problem representation and a fitness function that optimizes channel assignment and power control in the cellular network. (Abstract shortened by UMI.) Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2003 .V52. Source: Masters Abstracts International, Volume: 44-03, page: 1392. Thesis (M.Sc.)--University of Windsor (Canada), 2005

SIMULATION OF A CODE DIVISION MULTIPLE ACCESS (CDMA) 2000 DOWNLINK SYSTEM

The topic chosen for this project is the simulation of a CDMA 2000 downlink system. CDMA 2000 is a 3G mobile telecommunications standard that uses CDMA to send voice, data and signaling data (such as a dialed telephone number) between mobile telephones and cell sites. The purpose of the simulation is to show that the design of the system can be implemented in actual application. The original codes and libraries aretaken directly from the Matlab software for the purpose of the simulation. The simulation is set up by considering the data rate, the channel model and also the performance of the system in terms of bit error rate results and the frame quality indicator. I