4 research outputs found
Block diagonal GMD for zero-padded MIMO frequency selective channels with zero-forcing DFE
In the class of systems with linear precoder and zero-forcing (ZF) DFE for zero-padded MIMO frequency selective channels, existing optimal transceiver designs present two major drawbacks. First, the optimal system requires a large number of bits to encode the full precoding matrix. Second, the full precoding matrix leads to complex computations. These disadvantages become more severe as bandwidth (BW) efficiency increases. In this article, we propose using the block diagonal geometric mean decomposition (BD-GMD) technique to design an alternative transceiver. The proposed ZF-BD-GMD system uses a block diagonal orthogonal precoder matrix structure to reduce the required number of encoding bits and simplifies the computation. While solving the current optimal system's drawbacks, the ZF-BD-GMD system also produces a similar bit error rate (BER) performance when the block size is large. In other words, the ZF-BD-GMD system is asymptotically optimal in the class of communication systems with linear precoder and ZF-DFE receiver
Precoded FIR and Redundant V-BLAST Systems for Frequency-Selective MIMO Channels
The vertical Bell labs layered space-time (V-BLAST) system is a multi-input multioutput (MIMO) system designed to achieve good multiplexing gain. In recent literature, a precoder, which exploits channel information, has been added in the V-BLAST transmitter. This precoder forces each symbol stream to have an identical mean square error (MSE). It can be viewed as an alternative to the bit-loading method. In this paper, this precoded V-BLAST system is extended to the case of frequency-selective MIMO channels. Both the FIR and redundant types of transceivers, which use cyclic-prefixing and zero-padding, are considered. A fast algorithm for computing a cyclic-prefixing-based precoded V-BLAST transceiver is developed. Experiments show that the proposed methods with redundancy have better performance than the SVD-based system with optimal powerloading and bit loading for frequency-selective MIMO channels. The gain comes from the fact that the MSE-equalizing precoder has better bit-error rate performance than the optimal bitloading method
Block Diagonal GMD for Zero-Padded MIMO Frequency Selective Channels
In the class of systems with linear precoder and
decision feedback equalizers (DFE) for zero-padded (ZP) multiple-
input multiple-output (MIMO) frequency selective channels,
existing optimal transceiver designs present two drawbacks. First,
the optimal systems require a large number of feedback bits from
the receiver to encode the full precoding matrix. Second, the full
precoding matrix leads to complex computations. These disadvantages
become more severe as the bandwidth (BW) efficiency
increases. In this paper, we propose using block diagonal geometric
mean decomposition (BD-GMD) to design the transceiver.
Two new BD-GMD transceivers are proposed: the ZF-BD-GMD
system, where the receiver is a zero-forcing DFE (ZF-DFE), and
the MMSE-BD-GMD system, where the receiver is a minimummean-
square-error DFE (MMSE-DFE). The BD-GMD systems
introduced here have the following four properties: a) They use
the block diagonal unitary precoding technique to reduce the
required number of encoding bits and simplify the computation.
b) For any block size, the BD-GMD systems are optimal within
the family of systems using block diagonal unitary precoders and
DFEs. As block size gets larger, the BD-GMD systems produce
uncoded bit error rate (BER) performance similar to the optimal
systems using unitary precoders and DFEs. c) For the two ZF
transceivers (ZF-Optimal and ZF-BD-GMD) and the two MMSE
transceivers (MMSE-Optimal and MMSE-BD-GMD), the average
BER degrades as the BW efficiency increases. d) In the case of
single-input single-output (SISO) channels, the BD-GMD systems
have the same performance as those of the lazy precoder transceivers.
These properties make the proposed BD-GMD systems
more favorable designs in practical implementation than the
optimal systems