2 research outputs found
A lower bound on the data rate of dirty paper coding in general noise and interference
Dirty paper coding (DPC) allows a transmitter to send information to a
receiver in the presence of interference that is known (non-causally) to the
transmitter. The original version of DPC was derived for the case where the
noise and the interference are statistically independent Gaussian random
sequences. More recent works extended this approach to the case where the noise
and the interference are mutually independent and at least one of them is
Gaussian. In this letter we further extend the DPC scheme by relaxing the
Gaussian and statistical independence assumptions. We provide lower bounds on
the achievable data rates in a DPC setting for the case of possibly dependent
noise, interference and input signals. Also, the interference and noise terms
are allowed to have arbitrary probability distributions. The bounds are
relatively simple, are phrased in terms of second-order statistics, and are
tight when the actual noise distribution is close to Gaussian.Comment: Published in the IEEE Wireless Communications Letter
Uplink Downlink Rate Balancing and throughput scaling in FDD Massive MIMO Systems
In this work we extend the concept of uplink-downlink rate balancing to
frequency division duplex (FDD) massive MIMO systems. We consider a base
station with large number antennas serving many single antenna users. We first
show that any unused capacity in the uplink can be traded off for higher
throughput in the downlink in a system that uses either dirty paper (DP) coding
or linear zero-forcing (ZF) precoding. We then also study the scaling of the
system throughput with the number of antennas in cases of linear Beamforming
(BF) Precoding, ZF Precoding, and DP coding. We show that the downlink
throughput is proportional to the logarithm of the number of antennas. While,
this logarithmic scaling is lower than the linear scaling of the rate in the
uplink, it can still bring significant throughput gains. For example, we
demonstrate through analysis and simulation that increasing the number of
antennas from 4 to 128 will increase the throughput by more than a factor of 5.
We also show that a logarithmic scaling of downlink throughput as a function of
the number of receive antennas can be achieved even when the number of transmit
antennas only increases logarithmically with the number of receive antennas.Comment: Submitted to the IEEE Transactions on Signal Processin