3 research outputs found
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
Cellular Networks With Finite Precision CSIT: GDoF Optimality of Multi-Cell TIN and Extremal Gains of Multi-Cell Cooperation
We study the generalized degrees-of-freedom (GDoF) of cellular networks under
finite precision channel state information at the transmitters (CSIT). We
consider downlink settings modeled by the interfering broadcast channel (IBC)
under no multi-cell cooperation, and the overloaded
multiple-input-single-output broadcast channel (MISO-BC) under full multi-cell
cooperation. We focus on three regimes of interest: the mc-TIN regime, where a
scheme based on treating inter-cell interference as noise (mc-TIN) was shown to
be GDoF optimal for the IBC; the mc-CTIN regime, where the GDoF region
achievable by mc-TIN is convex without the need for time-sharing; and the
mc-SLS regime which extends a previously identified regime, where a simple
layered superposition (SLS) scheme is optimal for the 3-transmitter-3-user
MISO-BC, to overloaded cellular-type networks with more users than
transmitters. We first show that the optimality of mc-TIN for the IBC extends
to the entire mc-CTIN regime when CSIT is limited to finite precision. The
converse proof of this result relies on a new application of aligned images
bounds. We then extend the IBC converse proof to the counterpart overloaded
MISO-BC, obtained by enabling full transmitter cooperation. This, in turn, is
utilized to show that a multi-cell variant of the SLS scheme is optimal in the
mc-SLS regime under full multi-cell cooperation, albeit only for 2-cell
networks. The overwhelming combinatorial complexity of the GDoF region stands
in the way of extending this result to larger networks. Alternatively, we
appeal to extremal network analysis, recently introduced by Chan et al., and
study the GDoF gain of multi-cell cooperation over mc-TIN in the three regimes
of interest. We show that this extremal GDoF gain is bounded by small constants
in the mc-TIN and mc-CTIN regimes, yet scales logarithmically with the number
of cells in the mc-SLS regime.Comment: Accepted for publication in the IEEE Transactions on Information
Theor