University of Minnesota

Georgia Tech Research Corporation

Cisco Technology, Inc.

Xiaoli Ma

Georgios B Giannakis

Qi Zhou

Brian Gestner

David Verl Anderson

Wei Zhang

Brian Donald Hart

Matthew Aaron Silverman

Qingsong Wen

Hongyi Fu

Techniques are described for carrier frequency offset (CFO) and channel estimation of orthogonal frequency division multiplexing (OFDM) transmissions over multiple-input multiple-output (MIMO) frequency-selective fading channels. A wireless transmitter forms blocks of symbols by inserting training symbols within two or more blocks of information-bearing symbols. The transmitter applies a hopping code to each of the blocks of symbols to insert a null subcarrier at a different position within each of the blocks of symbols, and a modulator outputs a wireless signal in accordance with the blocks of symbols. A receiver receives the wireless signal and estimates the CFO, and outputs a stream of estimated symbols based on the estimated CFO.

Estimating frequency-offsets and multi-antenna channels in MIMO OFDM systems

A wireless device, such as an wireless access point, receives signals detected by a plurality of antennas of a wireless device to produce a plurality of antenna-specific receive signals potentially representing a wireless transmission received from each of one or a plurality of devices. A signal processing component of the wireless device, such as a modem, performs several operations on the antenna-specific receive signals, including building a first space-time equalizer to be applied to the plurality of antenna-specific receive signals to recover a transmission from a first device by both equalizing channel effects and canceling out effects associated with transmissions from devices other than the first device, and building a second space-time equalizer to be applied to the plurality of antenna-specific receive signals to recover a transmission from a second device by both equalizing channel effects and canceling out effects associated with transmissions from devices other than the second device.

Multi-user-MIMO detection using space-time equalization

Methods and apparatus reducing or eliminating the number of multipliers in Schnorr-Euchner expansion algorithms are disclosed. Methods and apparatus for implementing Schnorr-Euchner expansion algorithms with a reduced number of multipliers or without any multipliers are also disclosed. Also disclosed is a Schnorr-Euchner expansion method for a multiple-input multiple-output communication system. The method includes receiving, by a plurality of input terminals, a plurality of input signals. The method also includes detecting a symbol transmitted by each input signal. The detection includes identifying a list of possible symbols that may be transmitted by each input signal. A cost value for each possible symbol is determined based on a cost function. The cost function is implemented without requiring a multiplier. The possible symbol with a lowest cost value is identified as the transmitted symbol.

Schnorr-euchner expansions and their fast implementations

Embodiments of the present invention provide efficient greedy LLL algorithms that not only converge faster but also exhibit much lower complexity than the existing greedy LLL variants while similar error performance is maintained. First, a relaxed Lov&#xe1;sz condition is designed for searching the candidate set of LLL iterations with column swap operations. This relaxation does not need size reduction operations so that it can save complexity compared to the existing greedy LLL algorithms. Further, a relaxed criterion of the decrease in LLL potential is designed to select the optimal one in the candidate set of LLL iterations, which also exhibits lower complexity than the existing greedy LLL algorithms. Furthermore, simulations show that the inventive algorithm needs less LLL iterations compared to the existing greedy LLL algorithms.

Multi-input multi-output (MIMO) detection systems

Systems and methods are disclosed for detecting a symbol in large-scale multiple-input multiple-output communication systems. The detection is based on an improved lattice-reduction-aided K-best algorithm. The detection finds K best candidate symbols with minimum costs for each layer based on a priority queue and an on-demand expansion. In a complex domain, the detection may include a 2-dimensional Schnorr-Euchner expansion or, in the alternative, a two-stage 1-dimensional Schnorr-Euchner expansion.

Lattice-reduction-aided K-best algorithm for low complexity and high performance communications

An exemplary embodiment of the present invention provides a lattice reduction method comprising obtaining a preliminary estimate of a transformation matrix, generating a covariance matrix based on the preliminary estimate of the transformation matrix, reducing diagonal elements of the covariance matrix to generate a unimodular transformation matrix, and using the unimodular transformation matrix to obtain an estimate of an input.

Enhanced lattice reduction systems and methods

An exemplary embodiment of the present invention provides an incremental lattice reduction method comprising: receiving an input signal at a plurality of input terminals; evaluating a reliability assessment condition using a primary symbol vector estimate of at least a portion of the input signal; terminating the incremental lattice reduction method if the reliability assessment condition is satisfied; and if the reliability assessment condition is not satisfied, performing at least one iteration of a lattice reduction detection sub-method to obtain a secondary symbol vector estimate.

Incremental lattice reduction systems and methods

Disclosed herein are lattice reduction systems and methods for a MIMO communication system. One such method includes providing a channel matrix corresponding to a channel in a MIMO communication system, preprocessing the channel matrix to form at least an upper triangular matrix, implementing a relaxed size reduction process, and implementing a basis update process. Implementing the relaxed size reduction process comprises choosing a first relaxed size reduction parameter for a first-off-diagonal element of the upper triangular matrix, choosing a second relaxed size reduction parameter, which is greater than the first relaxed size reduction parameter, for a second-off-diagonal element of the upper triangular matrix evaluating whether a first relaxed size reduction condition is satisfied for the first-off-diagonal element of the upper triangular matrix, and evaluating whether a second relaxed size reduction condition is satisfied for the second-off-diagonal element of the upper triangular matrix.

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Norcross, GA, United States of America

Xiaoli Ma