106,050 research outputs found
Efficient Integer Coefficient Search for Compute-and-Forward
Integer coefficient selection is an important decoding step in the
implementation of compute-and-forward (C-F) relaying scheme. Choosing the
optimal integer coefficients in C-F has been shown to be a shortest vector
problem (SVP) which is known to be NP hard in its general form. Exhaustive
search of the integer coefficients is only feasible in complexity for small
number of users while approximation algorithms such as Lenstra-Lenstra-Lovasz
(LLL) lattice reduction algorithm only find a vector within an exponential
factor of the shortest vector. An optimal deterministic algorithm was proposed
for C-F by Sahraei and Gastpar specifically for the real valued channel case.
In this paper, we adapt their idea to the complex valued channel and propose an
efficient search algorithm to find the optimal integer coefficient vectors over
the ring of Gaussian integers and the ring of Eisenstein integers. A second
algorithm is then proposed that generalises our search algorithm to the
Integer-Forcing MIMO C-F receiver. Performance and efficiency of the proposed
algorithms are evaluated through simulations and theoretical analysis.Comment: IEEE Transactions on Wireless Communications, to appear.12 pages, 8
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Compute-and-Forward: Finding the Best Equation
Compute-and-Forward is an emerging technique to deal with interference. It
allows the receiver to decode a suitably chosen integer linear combination of
the transmitted messages. The integer coefficients should be adapted to the
channel fading state. Optimizing these coefficients is a Shortest Lattice
Vector (SLV) problem. In general, the SLV problem is known to be prohibitively
complex. In this paper, we show that the particular SLV instance resulting from
the Compute-and-Forward problem can be solved in low polynomial complexity and
give an explicit deterministic algorithm that is guaranteed to find the optimal
solution.Comment: Paper presented at 52nd Allerton Conference, October 201
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