4,463 research outputs found
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
Multicell Edge Coverage Enhancement Using Mobile UAV-Relay
Unmanned aerial vehicle (UAV)-assisted communication is a promising technology in future wireless communication networks. UAVs can not only help offload data traffic from ground base stations (GBSs) but also improve the Quality of Service (QoS) of cell-edge users (CEUs). In this article, we consider the enhancement of cell-edge communications through a mobile relay, i.e., UAV, in multicell networks. During each transmission period, GBSs first send data to the UAV, and then the UAV forwards its received data to CEUs according to a certain association strategy. In order to maximize the sum rate of all CEUs, we jointly optimize the UAV mobility management, including trajectory, velocity, and acceleration, and association strategy of CEUs to the UAV, subject to minimum rate requirements of CEUs, mobility constraints of the UAV, and causal buffer constraints in practice. To address the mixed-integer nonconvex problem, we transform it into two convex subproblems by applying tight bounds and relaxations. An iterative algorithm is proposed to solve the two subproblems in an alternating manner. Numerical results show that the proposed algorithm achieves higher rates of CEUs as compared with the existing benchmark schemes
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