Capacity Analysis of LTE-Advanced HetNets with Reduced Power Subframes and Range Expansion

The time domain inter-cell interference coordination techniques specified in LTE Rel. 10 standard improves the throughput of picocell-edge users by protecting them from macrocell interference. On the other hand, it also degrades the aggregate capacity in macrocell because the macro base station (MBS) does not transmit data during certain subframes known as almost blank subframes. The MBS data transmission using reduced power subframes was standardized in LTE Rel. 11, which can improve the capacity in macrocell while not causing high interference to the nearby picocells. In order to get maximum benefit from the reduced power subframes, setting the key system parameters, such as the amount of power reduction, carries critical importance. Using stochastic geometry, this paper lays down a theoretical foundation for the performance evaluation of heterogeneous networks with reduced power subframes and range expansion bias. The analytic expressions for average capacity and 5th percentile throughput are derived as a function of transmit powers, node densities, and interference coordination parameters in a heterogeneous network scenario, and are validated through Monte Carlo simulations. Joint optimization of range expansion bias, power reduction factor, scheduling thresholds, and duty cycle of reduced power subframes are performed to study the trade-offs between aggregate capacity of a cell and fairness among the users. To validate our analysis, we also compare the stochastic geometry based theoretical results with the real MBS deployment (in the city of London) and the hexagonal-grid model. Our analysis shows that with optimum parameter settings, the LTE Rel. 11 with reduced power subframes can provide substantially better performance than the LTE Rel. 10 with almost blank subframes, in terms of both aggregate capacity and fairness.Comment: Submitted to EURASIP Journal on Wireless Communications and Networking (JWCN

WHO-IS: Wireless Hetnet Optimization using Impact Selection

We propose a method to first identify users who have the most negative impact on the overall network performance, and then offload them to an orthogonal channel. The feasibility of such an approach is verified using real-world traces, network simulations, and a lab experiment that employs multi-homed wireless stations. In our experiment, as offload target, we employ LiFi IR transceivers, and as the primary network we consider a typical Enterprise Wi-Fi setup. We found that a limited number of users can impact the overall experience of the Wi-Fi network negatively, hence motivating targeted offloading. In our simulations and experiments we saw that the proposed solution can improve the collision probability with 82% and achieve a 61 percentage point air utilization improvement compared to random offloading, respectively

Fair and QoS-oriented resource management in heterogeneous networks

In this paper, a heterogeneous network composed of femtocells deployed within a macrocell network is considered, and a quality-of-service (QoS)-oriented fairness metric which captures important characteristics of tiered network architectures is proposed. Using homogeneous Poisson processes, the sum capacities in such networks are expressed in closed form for co-channel, dedicated channel, and hybrid resource allocation methods. Then a resource splitting strategy that simultaneously considers capacity maximization, fairness constraints, and QoS constraints is proposed. Detailed computer simulations utilizing 3GPP simulation assumptions show that a hybrid allocation strategy with a well-designed resource split ratio enjoys the best cell-edge user performance, with minimal degradation in the sum throughput of macrocell users when compared with that of co-channel operation