3 research outputs found
Sum Rate Maximization using Linear Precoding and Decoding in the Multiuser MIMO Downlink
We propose an algorithm to maximize the instantaneous sum data rate
transmitted by a base station in the downlink of a multiuser multiple-input,
multiple-output system. The transmitter and the receivers may each be equipped
with multiple antennas and each user may receive more than one data stream. We
show that maximizing the sum rate is closely linked to minimizing the product
of mean squared errors (PMSE). The algorithm employs an uplink/downlink duality
to iteratively design transmit-receive linear precoders, decoders, and power
allocations that minimize the PMSE for all data streams under a sum power
constraint. Numerical simulations illustrate the effectiveness of the algorithm
and support the use of the PMSE criterion in maximizing the overall
instantaneous data rate.Comment: 6 pages, 4 figures, uses ieeetran.cl
Linear Processing and Sum Throughput in the Multiuser MIMO Downlink
We consider linear precoding and decoding in the downlink of a multiuser
multiple-input, multiple-output (MIMO) system, wherein each user may receive
more than one data stream. We propose several mean squared error (MSE) based
criteria for joint transmit-receive optimization and establish a series of
relationships linking these criteria to the signal-to-interference-plus-noise
ratios of individual data streams and the information theoretic channel
capacity under linear minimum MSE decoding. In particular, we show that
achieving the maximum sum throughput is equivalent to minimizing the product of
MSE matrix determinants (PDetMSE). Since the PDetMSE minimization problem does
not admit a computationally efficient solution, a simplified scalar version of
the problem is considered that minimizes the product of mean squared errors
(PMSE). An iterative algorithm is proposed to solve the PMSE problem, and is
shown to provide near-optimal performance with greatly reduced computational
complexity. Our simulations compare the achievable sum rates under linear
precoding strategies to the sum capacity for the broadcast channel.Comment: Accepted for publication in IEEE Transactions on Wireless
Communication
Sum Rate Maximization using Linear Precoding and Decoding in the Multiuser MIMO Downlink
Abstract—We propose an algorithm to maximize the instantaneous sum data rate transmitted by a base station in the downlink of a multiuser multiple-input, multiple-output system. The transmitter and the receivers may each be equipped with multiple antennas and each user may receive more than one data stream. We show that maximizing the sum rate is closely linked to minimizing the product of mean squared errors (PMSE). The algorithm employs an uplink/downlink duality to iteratively design transmit-receive linear precoders, decoders, and power allocations that minimize the PMSE for all data streams under a sum power constraint. Numerical simulations illustrate the effectiveness of the algorithm and support the use of the PMSE criterion in maximizing the overall instantaneous data rate. I