Systems Seminar
Combined Transmitter Diversity and Multiuser Precoding for CDMA Channels
Dr. Secin Guncavdi
UW ECE Department
Abstract
Under severe channel conditions (i.e., multipath), the multiple access
interference (MAI) becomes the major source of performance degradation for
direct sequence CDMA (DS/CDMA) systems. This is because of the loss of
orthogonality between the spreading codes used by each user due to the
multipath channel effects. To overcome this problem, many receiver based
multiuser detection (MUD) techniques have been proposed. These techniques
demand high computational complexity, power and knowledge of spreading codes
of all users. As a result, in the downlink of a CDMA system it is not
feasible to employ such methods at the MS. Alternatively, transmitter based
techniques were proposed to shift computational complexity and power
consumption to the BS, where they can be afforded. It was shown that these
methods are very effective in removing the MAI. Although these methods are
powerful, they are high in complexity and require the accurate knowledge of
the channel since MAI cancellation filters need to be updated continuously
as fading coefficients vary. We propose a less complex method with similar
performance improvements. In the proposed method, the functions of multipath
combining and MAI cancellation are separated. Thus the MAI cancellation
matrix does not depend on rapidly time-varying fading coefficients.
Transmitter diversity and multiuser precoding can be combined to further
improve the performance. Multiuser precoding preserves the multipath
diversity while removing the MAI. Extending multiuser precoding to multiple
antennas results in space diversity in addition to multipath diversity. Both
transmitter diversity and multiuser precoding require the knowledge of the
channel state information (CSI). The CSI can be estimated at the receiver
and sent to the transmitter via a feedback channel. To enable the studied
adaptive techniques for practical systems, we employ the long range
prediction (LRP) algorithm, which characterizes the fading channel using the
autoregressive (AR) model and computes the Minimum Mean Squared Error (MMSE)
estimate of a future fading coefficient sample based on a number of past
observations. Numerical, simulation and theoretical results are presented to
show that transmitter diversity and multiuser precoding can be used to
remove MAI and achieve frequency and space diversity through multipath
channels and multiple antennas.
Time and Place: Wed., Nov. 19, at 3:30 pm in 4610 Engr. Hall.
SYSTEMS SEMINAR WEB PAGE:
http://www.cae.wisc.edu/~gubner/seminar/