554 research outputs found
Elevated Multiplexing and Signal Space Partitioning in the 2 User MIMO IC with Partial CSIT
The user MIMO interference channel with arbitrary antenna configurations
is studied under arbitrary levels of partial CSIT for each of the channels, to
find the degrees of freedom (DoF) achievable by either user while the other
user achieves his full interference-free DoF. The goal is to gain new insights
due to the inclusion of MIMO (multiple antennas at both transmitters and
receivers) into the signal space partitioning schemes associated with partial
CSIT. An interesting idea that emerges from this study is "elevated
multiplexing" where the signals are split into streams and transmitted from
separate antennas at elevated power levels, which allows these signals to be
jointly decoded at one receiver which has fewer spatial dimensions with lower
interference floors, while another receiver is simultaneously able to
separately decode these signals with a higher interference floor but across a
greater number of spatial dimensions. Remarkably, we find that there is a DoF
benefit from increasing the number of antennas at a transmitter even if that
transmitter already has more antennas than its desired receiver and has no
CSIT.Comment: Submitted as an invited paper to IEEE SPAW
Coordinated Beamforming with Relaxed Zero Forcing: The Sequential Orthogonal Projection Combining Method and Rate Control
In this paper, coordinated beamforming based on relaxed zero forcing (RZF)
for K transmitter-receiver pair multiple-input single-output (MISO) and
multiple-input multiple-output (MIMO) interference channels is considered. In
the RZF coordinated beamforming, conventional zero-forcing interference leakage
constraints are relaxed so that some predetermined interference leakage to
undesired receivers is allowed in order to increase the beam design space for
larger rates than those of the zero-forcing (ZF) scheme or to make beam design
feasible when ZF is impossible. In the MISO case, it is shown that the
rate-maximizing beam vector under the RZF framework for a given set of
interference leakage levels can be obtained by sequential orthogonal projection
combining (SOPC). Based on this, exact and approximate closed-form solutions
are provided in two-user and three-user cases, respectively, and an efficient
beam design algorithm for RZF coordinated beamforming is provided in general
cases. Furthermore, the rate control problem under the RZF framework is
considered. A centralized approach and a distributed heuristic approach are
proposed to control the position of the designed rate-tuple in the achievable
rate region. Finally, the RZF framework is extended to MIMO interference
channels by deriving a new lower bound on the rate of each user.Comment: Lemma 1 proof corrected; a new SOPC algorithm invented; K > N case
considere
On Precoding for Constant K-User MIMO Gaussian Interference Channel with Finite Constellation Inputs
This paper considers linear precoding for constant channel-coefficient
-User MIMO Gaussian Interference Channel (MIMO GIC) where each
transmitter- (Tx-), requires to send independent complex symbols
per channel use that take values from fixed finite constellations with uniform
distribution, to receiver- (Rx-) for . We define the
maximum rate achieved by Tx- using any linear precoder, when the
interference channel-coefficients are zero, as the signal to noise ratio (SNR)
tends to infinity to be the Constellation Constrained Saturation Capacity
(CCSC) for Tx-. We derive a high SNR approximation for the rate achieved by
Tx- when interference is treated as noise and this rate is given by the
mutual information between Tx- and Rx-, denoted as . A set of
necessary and sufficient conditions on the precoders under which
tends to CCSC for Tx- is derived. Interestingly, the precoders designed for
interference alignment (IA) satisfy these necessary and sufficient conditions.
Further, we propose gradient-ascent based algorithms to optimize the sum-rate
achieved by precoding with finite constellation inputs and treating
interference as noise. Simulation study using the proposed algorithms for a
3-user MIMO GIC with two antennas at each node with for all , and
with BPSK and QPSK inputs, show more than 0.1 bits/sec/Hz gain in the ergodic
sum-rate over that yielded by precoders obtained from some known IA algorithms,
at moderate SNRs.Comment: 15 pages, 9 figure
GDoF of the MISO BC: Bridging the gap between finite precision CSIT and perfect CSIT
This work bridges the gap between sharply contrasting results on the degrees of freedom of the K user broadcast channel where the transmitter is equipped with K transmit antennas and each of the K receivers is equipped with a single antenna. This channel has K DoF when channel state information at the transmitter (CSIT) is perfect, but as shown recently, it has only 1 DoF when the CSIT is limited to finite precision. By considering the full range of partial CSIT assumptions parameterized by β ⋯ [0,1], such that the strength of the channel estimation error terms scales as ∼ SNR-β relative to the channel strengths which scale as ∼ SNR, it is shown that this channel has 1 - β + Kβ DoF. For K = 2 users with arbitrary βij parameters, the DoF are shown to be 1 + mini,j βij. To explore diversity of channel strengths, the results are further extended to the symmetric Generalized Degrees of Freedom setting where the direct channel strengths scale as ∼ SNR and the cross channel strengths scale as ∼ SNRα, α ⋯ [0,1], β ⋯ [0,α]. Here, the roles of α and β are shown to counter each other on equal terms, so that the sum GDoF value in the K user setting is (α - β) + K(1 - (α-β )) and for the 2 user setting with arbitrary βij, is 2 - α + mini,j βij
Robust Monotonic Optimization Framework for Multicell MISO Systems
The performance of multiuser systems is both difficult to measure fairly and
to optimize. Most resource allocation problems are non-convex and NP-hard, even
under simplifying assumptions such as perfect channel knowledge, homogeneous
channel properties among users, and simple power constraints. We establish a
general optimization framework that systematically solves these problems to
global optimality. The proposed branch-reduce-and-bound (BRB) algorithm handles
general multicell downlink systems with single-antenna users, multiantenna
transmitters, arbitrary quadratic power constraints, and robustness to channel
uncertainty. A robust fairness-profile optimization (RFO) problem is solved at
each iteration, which is a quasi-convex problem and a novel generalization of
max-min fairness. The BRB algorithm is computationally costly, but it shows
better convergence than the previously proposed outer polyblock approximation
algorithm. Our framework is suitable for computing benchmarks in general
multicell systems with or without channel uncertainty. We illustrate this by
deriving and evaluating a zero-forcing solution to the general problem.Comment: Published in IEEE Transactions on Signal Processing, 16 pages, 9
figures, 2 table
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