1,663 research outputs found
Interference Exploitation-based Hybrid Precoding with Robustness Against Phase Errors
Hybrid analog-digital precoding significantly reduces the hardware costs in
massive MIMO transceivers when compared to fully-digital precoding at the
expense of increased transmit power. In order to mitigate the above shortfall,
we use the concept of constructive interference-based precoding, which has been
shown to offer significant transmit power savings when compared with the
conventional interference suppression-based precoding in fully-digital
multiuser MIMO systems. Moreover, in order to circumvent the potential
quality-of-service degradation at the users due to the hardware impairments in
the transmitters, we judiciously incorporate robustness against such
vulnerabilities in the precoder design. Since the undertaken constructive
interference-based robust hybrid precoding problem is nonconvex with infinite
constraints and thus difficult to solve optimally, we decompose the problem
into two subtasks, namely, analog precoding and digital precoding. In this
paper, we propose an algorithm to compute the optimal constructive
interference-based robust digital precoders. Furthermore, we devise a scheme to
facilitate the implementation of the proposed algorithm in a low-complexity and
distributed manner. We also discuss block-level analog precoding techniques.
Simulation results demonstrate the superiority of the proposed algorithm and
its implementation scheme over the state-of-the-art methods
Two-Stage Subspace Constrained Precoding in Massive MIMO Cellular Systems
We propose a subspace constrained precoding scheme that exploits the spatial
channel correlation structure in massive MIMO cellular systems to fully unleash
the tremendous gain provided by massive antenna array with reduced channel
state information (CSI) signaling overhead. The MIMO precoder at each base
station (BS) is partitioned into an inner precoder and a Transmit (Tx) subspace
control matrix. The inner precoder is adaptive to the local CSI at each BS for
spatial multiplexing gain. The Tx subspace control is adaptive to the channel
statistics for inter-cell interference mitigation and Quality of Service (QoS)
optimization. Specifically, the Tx subspace control is formulated as a QoS
optimization problem which involves an SINR chance constraint where the
probability of each user's SINR not satisfying a service requirement must not
exceed a given outage probability. Such chance constraint cannot be handled by
the existing methods due to the two stage precoding structure. To tackle this,
we propose a bi-convex approximation approach, which consists of three key
ingredients: random matrix theory, chance constrained optimization and
semidefinite relaxation. Then we propose an efficient algorithm to find the
optimal solution of the resulting bi-convex approximation problem. Simulations
show that the proposed design has significant gain over various baselines.Comment: 13 pages, accepted by IEEE Transactions on Wireless Communication
Linear Transceiver design for Downlink Multiuser MIMO Systems: Downlink-Interference Duality Approach
This paper considers linear transceiver design for downlink multiuser
multiple-input multiple-output (MIMO) systems. We examine different transceiver
design problems. We focus on two groups of design problems. The first group is
the weighted sum mean-square-error (WSMSE) (i.e., symbol-wise or user-wise
WSMSE) minimization problems and the second group is the minimization of the
maximum weighted mean-squareerror (WMSE) (symbol-wise or user-wise WMSE)
problems. The problems are examined for the practically relevant scenario where
the power constraint is a combination of per base station (BS) antenna and per
symbol (user), and the noise vector of each mobile station is a zero-mean
circularly symmetric complex Gaussian random variable with arbitrary covariance
matrix. For each of these problems, we propose a novel downlink-interference
duality based iterative solution. Each of these problems is solved as follows.
First, we establish a new mean-square-error (MSE) downlink-interference
duality. Second, we formulate the power allocation part of the problem in the
downlink channel as a Geometric Program (GP). Third, using the duality result
and the solution of GP, we utilize alternating optimization technique to solve
the original downlink problem. For the first group of problems, we have
established symbol-wise and user-wise WSMSE downlink-interference duality.Comment: IEEE TSP Journa
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