387 research outputs found
Estimation and detection techniques for doubly-selective channels in wireless communications
A fundamental problem in communications is the estimation of the channel.
The signal transmitted through a communications channel undergoes distortions
so that it is often received in an unrecognizable form at the receiver.
The receiver must expend significant signal processing effort in order to be
able to decode the transmit signal from this received signal. This signal processing
requires knowledge of how the channel distorts the transmit signal,
i.e. channel knowledge. To maintain a reliable link, the channel must be
estimated and tracked by the receiver.
The estimation of the channel at the receiver often proceeds by transmission
of a signal called the 'pilot' which is known a priori to the receiver.
The receiver forms its estimate of the transmitted signal based on how this
known signal is distorted by the channel, i.e. it estimates the channel from
the received signal and the pilot. This design of the pilot is a function of the
modulation, the type of training and the channel. [Continues.
From Linear Equalization to Lattice-Reduction-Aided Sphere-Detector as an Answer to the MIMO Detection Problematic in Spatial Multiplexing Systems
ISBN 978-953-307-223-4International audienc
Joint transceiver design for MIMO channel shortening.
Channel shortening equalizers can be employed
to shorten the effective impulse response of a long intersymbol
interference (ISI) channel in order, for example, to decrease the
computational complexity of a maximum-likelihood sequence
estimator (MLSE) or to increase the throughput efficiency of an
orthogonal frequency-division multiplexing (OFDM) transmission
scheme. In this paper, the issue of joint transmitter–receiver filter
design is addressed for shortening multiple-input multiple-output
(MIMO) ISI channels. A frequency-domain approach is adopted
for the transceiver design which is effectively equivalent to an
infinite-length time-domain design. A practical space–frequency
waterfilling algorithm is also provided. It is demonstrated that the
channel shortening equalizer designed according to the time-domain
approach suffers from an error-floor effect. However, the
proposed techniques are shown to overcome this problem and
outperform the time-domain channel shortening filter design. We
also demonstrate that the proposed transceiver design can be considered
as a MIMO broadband beamformer with constraints on
the time-domain multipath length. Hence, a significant diversity
gain could also be achieved by choosing strong eigenmodes of the
MIMO channel. It is also found that the proposed frequency-domain
methods have considerably low computational complexity as
compared with their time-domain counterparts
Generalized feedback detection for spatial multiplexing multi-antenna systems
We present a unified detection framework for spatial multiplexing multiple-input multiple-output (MIMO) systems by generalizing Heller’s classical feedback decoding algorithm for convolutional codes. The resulting generalized feedback detector (GFD) is characterized by three parameters: window size, step size and branch factor. Many existing MIMO detectors are turned out to be special cases of the GFD. Moreover, different parameter choices can provide various performance-complexity tradeoffs. The connection between MIMO detectors and tree search algorithms is also established. To reduce redundant computations in the GFD, a shared computation technique is proposed by using a tree data structure. Using a union bound based analysis of the symbol error rates, the diversity order and signal-to-noise ratio (SNR) gain are derived analytically as functions of the three parameters; for example, the diversity order of the GFD varies between 1 and N. The complexity of the GFD varies between those of the maximum-likelihood (ML) detector and the zero-forcing decision feedback detector (ZFDFD). Extensive computer simulation results are also provided
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