Downlink transmit power setting in LTE HetNets with carrier aggregation

Abstract

Carrier aggregation, which allows users to aggregate several component carriers to obtain up to 100 MHz of bandwidth, is one of the central features envisioned for next generation cellular networks. While this feature will enable support for higher data rates and improve quality of service, it may also be employed as an effective interference mitigation technique, especially in multi-tier heterogeneous networks. Having in mind that the aggregated component carriers may belong to different frequency bands and, hence, have varying propagation profiles, we argue that it is not necessary, indeed even harmful, to transmit at maximum power at all carriers, at all times. Rather, by using game theory, we design a distributed algorithm that lets eNodeBs and micro base stations dynamically adjust the downlink transmit power for the different component carriers. We compare our scheme to different power strategies combined with popular interference mitigation techniques, in a typical large-scale scenario, and show that our solution significantly outperforms the other strategies in terms of global network utility, power consumption and user throughput.

Distributed Downlink Power Control for Dense Networks With Carrier Aggregation

“…Let us first focus on a single carrier and consider two possible borderline strategies that a team may adopt: the max-power strategy in which all locations transmit at the highest power level, and the min-power strategy in which all locations transmit at the lowest available power level greater than 0. As shown in our previous study [21], it transpires that the min-power always outperforms the max-power in a multi-tier dense scenario. We therefore devise a procedure that should be executed by each team leader (macro PoA), in order to update the locations' downlink power setting, either periodically or upon changes in the user traffic or propagation conditions.…”

“…This combination was shown to perform best in our previous work [21] and is widely used in the literature and in practice. eICIC is applied with CRE for microcells set at 8 dB and macro PoAs downlink transmissions muted in 25% of subframes (ABS).…”

“…The team leader will then notify it to the neighboring team leaders that can be affected by this choice. BPS will be run by the teams till convergence is reached, which, as shown in [21], occurs very swiftly. Also, we remark that the strategies identified over the different iterations are not actually implemented by the PoAs.…”

LaSR: A Supple Multi-Connectivity Scheduler for Multi-RAT OFDMA Systems

“…[12], [13], including throughput, delay, energy and fairness considerations. Only recently, a few works consider carrier aggregation [14]- [18]. In [14], [15], the authors focus on allocating rates to maximize the network utility as a proportionally fair allocation of utilities of different traffic classes; the latter supporting user discrimination.…”

“…In terms of complexity, all these works require solving a sequence of convex programs at every slot (mild complexity). Finally, in [18], the authors address the rate allocation problem using a game-theoretic approach, suitable for a distributed setting, which requires a number of operations that scale exponentially with the number of users and RATs. Although all these works offer a very valuable theoretical analysis of the performance boundaries of carrier aggregation technology, they are not applicable in practice because, in contrast to ours, they either (i) operate only in the capacity boundary (very high load), (ii) do not let RATs be deactivated to reduce costs in low-, mid-load regimes, and/or (iii) do not consider practical issues of real systems like e.g.…”