25,446 research outputs found
Parallel QR decomposition in LTE-A systems
The QR Decomposition (QRD) of communication channel matrices is a fundamental
prerequisite to several detection schemes in Multiple-Input Multiple-Output
(MIMO) communication systems. Herein, the main feature of the QRD is to
transform the non-causal system into a causal system, where consequently
efficient detection algorithms based on the Successive Interference
Cancellation (SIC) or Sphere Decoder (SD) become possible. Also, QRD can be
used as a light but efficient antenna selection scheme. In this paper, we
address the study of the QRD methods and compare their efficiency in terms of
computational complexity and error rate performance. Moreover, a particular
attention is paid to the parallelism of the QRD algorithms since it reduces the
latency of the matrix factorization.Comment: The eleventh IEEE International Workshop on Signal Processing
Advances for Wireless Communications, 5 pages, 4 figures, 4 algorithms, 1
tabl
Adaptive and Iterative Multi-Branch MMSE Decision Feedback Detection Algorithms for MIMO Systems
In this work, decision feedback (DF) detection algorithms based on multiple
processing branches for multi-input multi-output (MIMO) spatial multiplexing
systems are proposed. The proposed detector employs multiple cancellation
branches with receive filters that are obtained from a common matrix inverse
and achieves a performance close to the maximum likelihood detector (MLD).
Constrained minimum mean-squared error (MMSE) receive filters designed with
constraints on the shape and magnitude of the feedback filters for the
multi-branch MMSE DF (MB-MMSE-DF) receivers are presented. An adaptive
implementation of the proposed MB-MMSE-DF detector is developed along with a
recursive least squares-type algorithm for estimating the parameters of the
receive filters when the channel is time-varying. A soft-output version of the
MB-MMSE-DF detector is also proposed as a component of an iterative detection
and decoding receiver structure. A computational complexity analysis shows that
the MB-MMSE-DF detector does not require a significant additional complexity
over the conventional MMSE-DF detector, whereas a diversity analysis discusses
the diversity order achieved by the MB-MMSE-DF detector. Simulation results
show that the MB-MMSE-DF detector achieves a performance superior to existing
suboptimal detectors and close to the MLD, while requiring significantly lower
complexity.Comment: 10 figures, 3 tables; IEEE Transactions on Wireless Communications,
201
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