483 research outputs found
Cooperative Multi-Cell Block Diagonalization with Per-Base-Station Power Constraints
Block diagonalization (BD) is a practical linear precoding technique that
eliminates the inter-user interference in downlink multiuser multiple-input
multiple-output (MIMO) systems. In this paper, we apply BD to the downlink
transmission in a cooperative multi-cell MIMO system, where the signals from
different base stations (BSs) to all the mobile stations (MSs) are jointly
designed with the perfect knowledge of the downlink channels and transmit
messages. Specifically, we study the optimal BD precoder design to maximize the
weighted sum-rate of all the MSs subject to a set of per-BS power constraints.
This design problem is formulated in an auxiliary MIMO broadcast channel (BC)
with a set of transmit power constraints corresponding to those for individual
BSs in the multi-cell system. By applying convex optimization techniques, this
paper develops an efficient algorithm to solve this problem, and derives the
closed-form expression for the optimal BD precoding matrix. It is revealed that
the optimal BD precoding vectors for each MS in the per-BS power constraint
case are in general non-orthogonal, which differs from the conventional
orthogonal BD precoder design for the MIMO-BC under one single sum-power
constraint. Moreover, for the special case of single-antenna BSs and MSs, the
proposed solution reduces to the optimal zero-forcing beamforming (ZF-BF)
precoder design for the weighted sum-rate maximization in the multiple-input
single-output (MISO) BC with per-antenna power constraints. Suboptimal and
low-complexity BD/ZF-BF precoding schemes are also presented, and their
achievable rates are compared against those with the optimal schemes.Comment: accepted in JSAC, special issue on cooperative communications on
cellular networks, June 201
Improved Linear Precoding over Block Diagonalization in Multi-cell Cooperative Networks
In downlink multiuser multiple-input multiple-output (MIMO) systems, block
diagonalization (BD) is a practical linear precoding scheme which achieves the
same degrees of freedom (DoF) as the optimal linear/nonlinear precoding
schemes. However, its sum-rate performance is rather poor in the practical SNR
regime due to the transmit power boost problem. In this paper, we propose an
improved linear precoding scheme over BD with a so-called
"effective-SNR-enhancement" technique. The transmit covariance matrices are
obtained by firstly solving a power minimization problem subject to the minimum
rate constraint achieved by BD, and then properly scaling the solution to
satisfy the power constraints. It is proved that such approach equivalently
enhances the system SNR, and hence compensates the transmit power boost problem
associated with BD. The power minimization problem is in general non-convex. We
therefore propose an efficient algorithm that solves the problem heuristically.
Simulation results show significant sum rate gains over the optimal BD and the
existing minimum mean square error (MMSE) based precoding schemes.Comment: 21 pages, 4 figure
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