Energy efficiency-spectral efficiency tradeoff in interference-limited wireless networks
Résumé
One of the used strategies to increase the spectral efficiency (SE) of cellular network is to reuse the frequency bandwidth over relatively small areas. The major issue in this case is higher interference, decreasing the energy efficiency (EE). In addition to the higher bandwidth, densification of the networks (e.g. small cells or multi-user multiple input single output, MU-MISO) potentially increases the area spectral efficiency (ASE). The total energy consumption of the wireless networks increases due to the large amount of circuit power consumed by the dense network structures, leading to the decrease of EE. In this thesis, the EE-SE achievable region is characterized in a hexagonal cellular network considering several frequency reuse factors (FRF), as well as shadowing. The EE-ASE region is also studied using Poisson point processes (PPP) to model the MU-MISO network with signal-to-leakage-and-noise ratio (SLNR) precoder. Different base station (BS) densities and different number of BS antennas with static power consumption are considered.The EE-SE region in a hexagonal cellular network for different FRF, both with and without shadowing is first characterized. When shadowing is considered in addition to the path loss, the ε-SE-EE tradeoff is proposed as an outage measure for performance evaluation. The EE-SE curves have a large linear part, due to the static power consumption, followed by a sharp decreasing EE, since the network is homogeneous and interference-limited. The results show that FRF of 1 for regions close to BS and higher FRF for regions closer to the cell edge improve the EE-SE optimal point. Moreover, better EE-SE tradeoff can be achieved with higher outage values. Besides, FRF of 1 is the best choice for very high outage value due to the significant signal-to-interference-plus-noise ratio (SINR) decrease.In downlink, precoders are used in space division multiple access (SDMA) MU-MISO cellular networks to improve the SINR. Stochastic geometry has been intensively used to analyse such a complex system. A closed-form expression for ASE in asymptotic regime, i.e. number of antennas and number of users grow to infinity, has been derived using random matrix theory and stochastic geometry. BSs and users are modeled by two independent PPP and SLNR precoder is used at BS. EE is then derived from a linear power consumption model. Monte Carlo simulations show that the analytical expressions are tight even for moderate number of antennas and users. Moreover, the EE-ASE curves have a large linear part before a sharply decreasing EE, as observed for hexagonal network. The results also show that SLNR outperforms the zero-foring (ZF) precoder, which is typically used in literature. Numerical results for SLNR show that deploying more BS or a large number of BS antennas increase ASE, but the gain depends on the BS-user density ratio and on the number of antennas when user density is fixed. EE increases only when the increase in ASE dominates the increase of the power consumption per unit area. On the other hand, when the user density increases, ASE in interference-limited region can be improved by deploying more BS without sacrificing EE and the ergodic rate of the users.
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