1,297 research outputs found
A Framework for Uplink Intercell Interference Modeling with Channel-Based Scheduling
This paper presents a novel framework for modeling the uplink intercell
interference (ICI) in a multiuser cellular network. The proposed framework
assists in quantifying the impact of various fading channel models and
state-of-the-art scheduling schemes on the uplink ICI. Firstly, we derive a
semianalytical expression for the distribution of the location of the scheduled
user in a given cell considering a wide range of scheduling schemes. Based on
this, we derive the distribution and moment generating function (MGF) of the
uplink ICI considering a single interfering cell. Consequently, we determine
the MGF of the cumulative ICI observed from all interfering cells and derive
explicit MGF expressions for three typical fading models. Finally, we utilize
the obtained expressions to evaluate important network performance metrics such
as the outage probability, ergodic capacity, and average fairness numerically.
Monte-Carlo simulation results are provided to demonstrate the efficacy of the
derived analytical expressions.Comment: IEEE Transactions on Wireless Communications, 2013. arXiv admin note:
substantial text overlap with arXiv:1206.229
Optimality of Treating Interference as Noise: A Combinatorial Perspective
For single-antenna Gaussian interference channels, we re-formulate the
problem of determining the Generalized Degrees of Freedom (GDoF) region
achievable by treating interference as Gaussian noise (TIN) derived in [3] from
a combinatorial perspective. We show that the TIN power control problem can be
cast into an assignment problem, such that the globally optimal power
allocation variables can be obtained by well-known polynomial time algorithms.
Furthermore, the expression of the TIN-Achievable GDoF region (TINA region) can
be substantially simplified with the aid of maximum weighted matchings. We also
provide conditions under which the TINA region is a convex polytope that relax
those in [3]. For these new conditions, together with a channel connectivity
(i.e., interference topology) condition, we show TIN optimality for a new class
of interference networks that is not included, nor includes, the class found in
[3].
Building on the above insights, we consider the problem of joint link
scheduling and power control in wireless networks, which has been widely
studied as a basic physical layer mechanism for device-to-device (D2D)
communications. Inspired by the relaxed TIN channel strength condition as well
as the assignment-based power allocation, we propose a low-complexity
GDoF-based distributed link scheduling and power control mechanism (ITLinQ+)
that improves upon the ITLinQ scheme proposed in [4] and further improves over
the heuristic approach known as FlashLinQ. It is demonstrated by simulation
that ITLinQ+ provides significant average network throughput gains over both
ITLinQ and FlashLinQ, and yet still maintains the same level of implementation
complexity. More notably, the energy efficiency of the newly proposed ITLinQ+
is substantially larger than that of ITLinQ and FlashLinQ, which is desirable
for D2D networks formed by battery-powered devices.Comment: A short version has been presented at IEEE International Symposium on
Information Theory (ISIT 2015), Hong Kon
Optimizing Sectorized Wireless Networks: Model, Analysis, and Algorithm
Future wireless networks need to support the increasing demands for high data
rates and improved coverage. One promising solution is sectorization, where an
infrastructure node (e.g., a base station) is equipped with multiple sectors
employing directional communication. Although the concept of sectorization is
not new, it is critical to fully understand the potential of sectorized
networks, such as the rate gain achieved when multiple sectors can be
simultaneously activated. In this paper, we focus on sectorized wireless
networks, where sectorized infrastructure nodes with beam-steering capabilities
form a multi-hop mesh network for data forwarding and routing. We present a
sectorized node model and characterize the capacity region of these sectorized
networks. We define the flow extension ratio and the corresponding
sectorization gain, which quantitatively measure the performance gain
introduced by node sectorization as a function of the network flow. Our
objective is to find the optimal sectorization of each node that achieves the
maximum flow extension ratio, and thus the sectorization gain. Towards this
goal, we formulate the corresponding optimization problem and develop an
efficient distributed algorithm that obtains the node sectorization under a
given network flow with an approximation ratio of 2/3. Through extensive
simulations, we evaluate the sectorization gain and the performance of the
proposed algorithm in various network scenarios with varying network flows. The
simulation results show that the approximate sectorization gain increases
sublinearly as a function of the number of sectors per node
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