International audience In this paper, we address the problem of optimally placing relay nodes in a cellular network with the aim of maximizing cell capacity. In order to accurately model interference, we use a dynamic framework, in which users arrive at random time instants and locations, download a file and leave the system. A fixed point equation is solved to account for the interactions between stations. We also propose an extension of a fluid model to relay based cellular networks. This allows us to obtain quick approximations of the Signal to Interference plus Noise Ratio (SINR) that are very close to 3GPP LTE-A guideline results in terms of SINR distribution.We then use these formulas to develop a dedicated Simulated Annealing (SA) algorithm, which adapts dynamically the temperature to energy variations and uses a combination of coarse and fine grids to accelerate the search for an optimized solution. Simulations results are provided for both in-band and out-of-band relays. They show how relays should be placed in a cell in order to increase the capacity in case of uniform and non-uniform traffic. The crucial impact of the backhaul link is analyzed for in-band relays. Insights are given on the influence of shadowing.
This paper studies the performance of two traditional schedulers, Proportional Fair (PF) and Round Robin (RR), in the context of relay-enhanced LTE-A networks. These two schedulers are indeed natural candidates for implementation in relays nodes (RN) and, following the results obtained in singlehop networks, mobile operators could be tempted to adopt PF because of the good trade-off it offers between cell capacity and fairness. Based on a statistical throughput evaluation model, we show that this is not necessarily the right option. The number of RNs, their locations in the cell, and the backhaul link quality have indeed a decisive influence on the scheduler choice. In some scenarios, it is even not desirable to deploy relays as they degrade the network performance compared to the no relay case. For the purpose of performance evaluation, we develop a realistic and computationally tractable statistical network model that takes into account fast fading, multiple interferers, cell range expansion bias, backhaul link quality, and traffic load. We also propose an optimization of the radio frame structure and a sub-optimal RN placement scheme in order to fairly compare RR and PF.
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