Contrasting Open-Loop and Closed-Loop Power Control Performance in UTRAN LTE Uplink by UE Trace Analysis
ABSTRACT Uplink power control in UTRAN Long Term Evolution consists of an open-loop scheme handled by the User Equipment and closed-loop power corrections determined and signaled by the network. In this study the difference in performance between pure open-loop and combined open and closed-loop power control has been analyzed and the different behavior of fractional vs. full path-loss compensation has been evaluated. A comprehensive system level simulation model has been used with a facility to trace a particular test user during its motion from eNodeB towards the cell border and back to its initial position. This study demonstrates the effect of distance path-loss of a test user on several physical layer performance metrics including throughput, resource allocation as well as modulation and coding scheme utilization. Simulation results in a fully loaded network show high throughput for open-loop fractional power control for the user located in the vicinity of the serving eNodeB, however, steep performance degradation has been observed when the user is moving towards the cell edge. The user throughput at the cell border can be increased by the closed-loop component. The benefit of closed-loop power control is the higher homogeneity in terms of throughput across the entire network area and the ability to automatically stabilize the network performance under different conditions like cell load and traffic distribution.
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ABSTRACT: In this paper, we develop a novel inter-cell interference co-ordination scheme that takes into account the interference cost on neighboring cells. We formulate a multi-cell utility maximization problem and subsequently decouple it into single-cell optimization problems by including an interference penalty. By solving this decoupled problem, we derive policies for user selection, resource allocation, and power-control. Since the coupling between cells is indirectly taken into account by means of the user's channel gain to the neighboring cells, our simulation results show that this distributed solution has no degradation in performance while little or no inter-cell co-ordination is required. We present simulation results that show that the Interference Penalty Algorithm (IPA) provides significant improvement in sector and cell-edge throughputs.Wireless Communications and Networking Conference (WCNC), 2013 IEEE; 01/2013
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ABSTRACT: Uplink power control plays a key role on the performance of uplink cellular network. In this work, the power control factor ($\in[0,1]$) is evaluated based on three parameters namely: average transmit power, coverage probability and average rate. In other words, we evaluate power control factor such that average transmit power should be low, coverage probability of cell-edge users should be high and also average rate over all the uplink users should be high. We show through numerical studies that the power control factor should be close to $0.5$ in order to achieve an acceptable trade-off between these three parameters.01/2014;
Conference Paper: Coverage probability of uplink cellular networks[Show abstract] [Hide abstract]
ABSTRACT: The cellular uplink has typically been studied using simple Wyner-type analytical models where interference is modeled as a constant or a single random variable, or via complex system-level simulations for a given set of parameters, which are often insufficient to evaluate performance in all operational regimes. In this paper, we take a fresh look at this classic problem using tools from point process theory and stochastic geometry, and develop a new tractable model for the cellular uplink which provides easy-to-evaluate expressions for important performance metrics such as coverage probability. The main idea is to model the locations of mobiles as a realization of a Poisson Point Process where each base station (BS) is located uniformly in the Voronoi cell of the mobile it serves, thereby capturing the dependence in two spatial processes. In addition to modeling interference accurately, it provides a natural way to model per-mobile power control, which is an important aspect of the uplink and one of the reasons why uplink analysis is more involved than its downlink counterpart. We also show that the same framework can be used to study regular as well as irregular BS deployments by choosing an appropriate distribution for the distance of a mobile to its serving BS. We verify the accuracy of this framework with an actual urban/suburban cellular network.Global Communications Conference (GLOBECOM), 2012 IEEE; 01/2012