15,565 research outputs found
On the High-SNR Capacity of the Gaussian Interference Channel and New Capacity Bounds
The best outer bound on the capacity region of the two-user Gaussian
Interference Channel (GIC) is known to be the intersection of regions of
various bounds including genie-aided outer bounds, in which a genie provides
noisy input signals to the intended receiver. The Han and Kobayashi (HK) scheme
provides the best known inner bound. The rate difference between the best known
lower and upper bounds on the sum capacity remains as large as 1 bit per
channel use especially around , where is the symmetric power
constraint and is the symmetric real cross-channel coefficient. In this
paper, we pay attention to the \emph{moderate interference regime} where
. We propose a new upper-bounding technique
that utilizes noisy observation of interfering signals as genie signals and
applies time sharing to the genie signals at the receivers. A conditional
version of the worst additive noise lemma is also introduced to derive new
capacity bounds. The resulting upper (outer) bounds on the sum capacity
(capacity region) are shown to be tighter than the existing bounds in a certain
range of the moderate interference regime. Using the new upper bounds and the
HK lower bound, we show that characterizes the capacity of the symmetric real
GIC to within bit per channel use in the moderate interference regime
at any signal-to-noise ratio (SNR). We further establish a high-SNR
characterization of the symmetric real GIC, where the proposed upper bound is
at most bit far from a certain HK achievable scheme with Gaussian
signaling and time sharing for . In particular,
is achievable at high SNR by the proposed HK scheme and turns out to be the
high-SNR capacity at least at .Comment: Submitted to IEEE Transactions on Information Theory on June 2015,
revised on November 2016, and accepted for publication on Feb. 28, 201
Achieving Global Optimality for Weighted Sum-Rate Maximization in the K-User Gaussian Interference Channel with Multiple Antennas
Characterizing the global maximum of weighted sum-rate (WSR) for the K-user
Gaussian interference channel (GIC), with the interference treated as Gaussian
noise, is a key problem in wireless communication. However, due to the users'
mutual interference, this problem is in general non-convex and thus cannot be
solved directly by conventional convex optimization techniques. In this paper,
by jointly utilizing the monotonic optimization and rate profile techniques, we
develop a new framework to obtain the globally optimal power control and/or
beamforming solutions to the WSR maximization problems for the GICs with
single-antenna transmitters and single-antenna receivers (SISO), single-antenna
transmitters and multi-antenna receivers (SIMO), or multi-antenna transmitters
and single-antenna receivers (MISO). Different from prior work, this paper
proposes to maximize the WSR in the achievable rate region of the GIC directly
by exploiting the facts that the achievable rate region is a "normal" set and
the users' WSR is a "strictly increasing" function over the rate region.
Consequently, the WSR maximization is shown to be in the form of monotonic
optimization over a normal set and thus can be solved globally optimally by the
existing outer polyblock approximation algorithm. However, an essential step in
the algorithm hinges on how to efficiently characterize the intersection point
on the Pareto boundary of the achievable rate region with any prescribed "rate
profile" vector. This paper shows that such a problem can be transformed into a
sequence of signal-to-interference-plus-noise ratio (SINR) feasibility
problems, which can be solved efficiently by existing techniques. Numerical
results validate that the proposed algorithms can achieve the global WSR
maximum for the SISO, SIMO or MISO GIC.Comment: This is the longer version of a paper to appear in IEEE Transactions
on Wireless Communication
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