7,447 research outputs found
Quantum Random Access Codes with Shared Randomness
We consider a communication method, where the sender encodes n classical bits
into 1 qubit and sends it to the receiver who performs a certain measurement
depending on which of the initial bits must be recovered. This procedure is
called (n,1,p) quantum random access code (QRAC) where p > 1/2 is its success
probability. It is known that (2,1,0.85) and (3,1,0.79) QRACs (with no
classical counterparts) exist and that (4,1,p) QRAC with p > 1/2 is not
possible.
We extend this model with shared randomness (SR) that is accessible to both
parties. Then (n,1,p) QRAC with SR and p > 1/2 exists for any n > 0. We give an
upper bound on its success probability (the known (2,1,0.85) and (3,1,0.79)
QRACs match this upper bound). We discuss some particular constructions for
several small values of n.
We also study the classical counterpart of this model where n bits are
encoded into 1 bit instead of 1 qubit and SR is used. We give an optimal
construction for such codes and find their success probability exactly--it is
less than in the quantum case.
Interactive 3D quantum random access codes are available on-line at
http://home.lanet.lv/~sd20008/racs .Comment: 51 pages, 33 figures. New sections added: 1.2, 3.5, 3.8.2, 5.4 (paper
appears to be shorter because of smaller margins). Submitted as M.Math thesis
at University of Waterloo by M
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
Joint data detection and channel estimation for OFDM systems
We develop new blind and semi-blind data detectors and channel estimators for orthogonal frequency-division multiplexing (OFDM) systems. Our data detectors require minimizing a complex, integer quadratic form in the data vector. The semi-blind detector uses both channel correlation and noise variance. The quadratic for the blind detector suffers from rank deficiency; for this, we give a low-complexity solution. Avoiding a computationally prohibitive exhaustive search, we solve our data detectors using sphere decoding (SD) and V-BLAST and provide simple adaptations of the SD algorithm. We consider how the blind detector performs under mismatch, generalize the basic data detectors to nonunitary constellations, and extend them to systems with pilots and virtual carriers. Simulations show that our data detectors perform well
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