Transmit power allocation for self-organising future cellular mobile radio networks

Abstract

Future mobile radio networks are expected to witness an increase in capacity demand. Since the spectrum suited for mobile radio application is scarce, the spectrum efficiency of future mobile radio networks has to be increased in order to be able to meet the capacity demand. In networks applying adaptive modulation and coding, both, transmit power and bandwidth can be considered as resources. In order to achieve high spectrum efficiency, the adaptation of the allocation of transmit power and bandwidth to the time-varying capacity demand is an important topic. In this paper, an approach that adjusts the allocation of transmit power to the cells in order to adapt the network to changing capacity demands is proposed. A mathematical model that relates transmit power and the probability of outage in the cells is presented and used in an approach for the minimsation of the outage probability in the cells using convex optimisation techniques. The performance of the presented approach is evaluated and its suitability for the adaptation of the network to capacity hotspots is shown. Due to the use of a mathematical model and convex optimisation techniques, the presented approach is suited for self-organising optimisation.

Distributed and Autonomous Resource and Power Allocation for Wireless Networks

“…Furthermore, it is clear that the average throughput of fuzzy logic is improved over the greedy heuristic (by 4%), even though after 15 time slots the performance is similar. This highlights that fuzzy logic ICIC is optimal on a cell-individual basis, however is able to (due to other inputs such as rate requirement and desired signal strength) converge to this optimum much quicker 6 .…”

“…efficiency is achieved quite rapidly. The added energy efficiency due to LA is a direct result of the augmented throughputs (see (6)). It is shown that ABS transmission is slightly more energy efficient than maximum power transmission, which is logical since on average 10% less power is used, but the loss in throughput is <10%, thus enhancing the energy efficiency.…”

“…2) are combined at each of M RBs available at the FBS, inducing a complexity of KM. Following this, the RBs are sorted according to their fuzzy score, in order 6 The substantial decline in performance by the greedy heuristic in the first time slots results from the lack of interference information. The unused RBs with "zero" interference are allocated in all cells simultaneously, thus causing large outages in these slots.…”

“…In cellular networks, such organisation can be performed via optimisation techniques [6], however these tasks become increasingly difficult given the additional APs and network parameters to be considered, motivating a distributed configuration approach [7].…”

Power Consumption Optimization Strategy for Wireless Networks

“…A convex optimization technique has been proposed in [9] to adjust the allocation of transmit power to the cells in order to adapt the network to changing capacity demands. The bandwidth allocated to the cells is fixed, but the transmit power allocated to the cells is adjusted in order to adapt the capacities of the cells according to the demand.…”