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An Adaptive Soft Handover Scheme Using Fuzzy Load Balancing for WCDMA Systems
In cellular systems, user distribution variations can cause load imbalance between cells. Embedding a load balancing strategy within the handover scheme means that ensuing traffic congestion can be alleviated by dynamically reallocating load between neighbouring cells. An adaptive soft handover scheme for multimedia cellular communication systems is proposed in this paper, that considers both the cell load factors as well as the pilot channel signal-to-interference-and-noise-ratio (SINR) for soft handovers. By using fuzzy principles, the soft handover thresholds and time hysteresis are adapted dependent upon the loads of the neighbouring cells. Simulation results show that the new algorithm provides improved system performance in terms of a more evenly distributed load, lower blocking probabilities and higher throughput
Soft handover issues in radio resource management for 3G WCDMA networks
PhDMobile terminals allow users to access services while on the move. This unique
feature has driven the rapid growth in the mobile network industry, changing it from a
new technology into a massive industry within less than two decades.
Handover is the essential functionality for dealing with the mobility of the mobile
users. Compared with the conventional hard handover employed in the GSM mobile
networks, the soft handover used in IS-95 and being proposed for 3G has better
performance on both link and system level.
Previous work on soft handover has led to several algorithms being proposed and
extensive research has been conducted on the performance analysis and parameters
optimisation of these algorithms. Most of the previous analysis focused on the uplink
direction. However, in future mobile networks, the downlink is more likely to be the
bottleneck of the system capacity because of the asymmetric nature of new services,
such as Internet traffic.
In this thesis, an in-depth study of the soft handover effects on the downlink
direction of WCDMA networks is carried out, leading to a new method of optimising
soft handover for maximising the downlink capacity and a new power control
approach
Final report on the evaluation of RRM/CRRM algorithms
Deliverable public del projecte EVERESTThis deliverable provides a definition and a complete evaluation of the RRM/CRRM algorithms selected in D11 and D15, and evolved and refined on an iterative process. The evaluation will be carried out by means of simulations using the simulators provided at D07, and D14.Preprin
A combinatorial approximation algorithm for CDMA downlink rate allocation
This paper presents a combinatorial algorithm for downlink rate allocation in Code Division Multiple Access (CDMA) mobile networks. By discretizing the coverage area into small segments, the transmit power requirements are characterized via a matrix representation that separates user and system characteristics. We obtain a closed-form analytical expression for the so-called Perron-Frobenius eigenvalue of that matrix, which provides a quick assessment of the feasibility of the power assignment for a given downlink rate allocation. Based on the Perron-Frobenius eigenvalue, we reduce the downlink rate allocation problem to a set of multiple-choice knapsack problems. The solution of these problems provides an approximation of the optimal downlink rate allocation and cell borders for which the system throughput, expressed in terms of utility functions of the users, is maximized
Resource management in QoS-aware wireless cellular networks
2011 Summer.Includes bibliographical references.Emerging broadband wireless networks that support high speed packet data with heterogeneous quality of service (QoS) requirements demand more flexible and efficient use of the scarce spectral resource. Opportunistic scheduling exploits the time-varying, location-dependent channel conditions to achieve multiuser diversity. In this work, we study two types of resource allocation problems in QoS-aware wireless cellular networks. First, we develop a rigorous framework to study opportunistic scheduling in multiuser OFDM systems. We derive optimal opportunistic scheduling policies under three common QoS/fairness constraints for multiuser OFDM systems--temporal fairness, utilitarian fairness, and minimum-performance guarantees. To implement these optimal policies efficiently, we provide a modified Hungarian algorithm and a simple suboptimal algorithm. We then propose a generalized opportunistic scheduling framework that incorporates multiple mixed QoS/fairness constraints, including providing both lower and upper bound constraints. Next, taking input queues and channel memory into consideration, we reformulate the transmission scheduling problem as a new class of Markov decision processes (MDPs) with fairness constraints. We investigate the throughput maximization and the delay minimization problems in this context. We study two categories of fairness constraints, namely temporal fairness and utilitarian fairness. We consider two criteria: infinite horizon expected total discounted reward and expected average reward. We derive and prove explicit dynamic programming equations for the above constrained MDPs, and characterize optimal scheduling policies based on those equations. An attractive feature of our proposed schemes is that they can easily be extended to fit different objective functions and other fairness measures. Although we only focus on uplink scheduling, the scheme is equally applicable to the downlink case. Furthermore, we develop an efficient approximation method--temporal fair rollout--to reduce the computational cost
GAME THEORETIC APPROACH TO RADIO RESOURCE MANAGEMENT ON THE REVERSE LINK FOR MULTI-RATE CDMA WIRELESS DATA NETWORKS
This work deals with efficient power and rate assignment to mobile stations (MSs) involved in bursty data transmission in cellular CDMA networks. Power control in the current CDMA standards is based on a fixed target signal quality called signal to interference ratio (SIR). The target SIR represents a predefined frame error rate (FER). This approach is inefficient for data-MSs because a fixed target SIR can limit the MS's throughput. Power control should thus provide dynamic target SIRs instead of a fixed target SIR. In the research literature, the power control problem has been modeled using game theory. A limitation of the current literature is that in order to implement the algorithms, each MS needs to know information such as path gains and transmission rates of all other MSs. Fast rate control schemes in the evolving cellular data systems such as cdma2000-1x-EV assign transmission rates to MSs using a probabilistic approach. The limitation here is that the radio resources can be either under or over-utilized. Further, all MSs are not assigned the same rates. In the schemes proposed in the literature, only few MSs, which have the best channel conditions, obtain all radio resources. In this dissertation, we address the power control issue by moving the computation of the Nash equilibrium from each MS to the base station (BS). We also propose equal radio resource allocation for all MSs under the constraint that only the maximum allowable radio resources are used in a cell. This dissertation addresses the problem of how to efficiently assign power and rate to MSs based on dynamic target SIRs for bursty transmissions. The proposed schemes in this work maximize the throughput of each data-MS while still providing equal allocation of radio resources to all MSs and achieving full radio resource utilization in each cell. The proposed schemes result in power and rate control algorithms that however require some assistance from the BS. The performance evaluation and comparisons with cdma2000-1x-Evolution Data Only (1x-EV-DO) show that the proposed schemes can provide better effective rates (rates after error) than the existing schemes
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