98,725 research outputs found
Blind joint maximum likelihood channel estimation and data detection for SIMO systems
No full textA blind adaptive scheme is proposed for joint maximum likelihood (ML) channel estimation and data detection of single-input multiple-output (SIMO) systems. The joint ML optimisation over channel and data is decomposed into an iterative optimisation loop. An efficient global optimisation algorithm called the repeated weighted boosting search is employed at the upper level to optimally identify the unknown SIMO channel model, and the Viterbi algorithm is used at the lower level to produce the maximum likelihood sequence estimation of the unknown data sequence. A simulation example is used to demonstrate the effectiveness of this joint ML optimisation scheme for blind adaptive SIMO systems
Constant modulus algorithm aided soft decision directed scheme for blind space-time equalisation of SIMO channels
No full textThis paper investigates a blind space–time equaliser (STE) designed for single-input multiple-output (SIMO) systems that employ high-throughput quadrature amplitude modulation schemes. A constant modulus algorithm (CMA) aided soft decision-directed (SDD) scheme, originally derived for low-complexity blind equalisation of single-input single-output channels, is extended to the SIMO scenario. Simulations are conducted to compare the performance of this blind adaptive scheme with another low-complexity blind STE referred to as the CMA aided decision directed (DD) scheme. The results obtained demonstrate that for SIMO systems the CMA aided SDD scheme exhibits advantages over the CMA aided DD arrangement, in terms of its faster convergence speed and lower computational complexity
Blind joint maximum likelihood channel estimation and data detection for single-input multiple-output systems
No full textA blind adaptive scheme is proposed for joint maximum likelihood (ML) channel estimation and data detection of single-input multiple-output (SIMO) systems. The joint ML optimization of the channel and data estimation is decomposed into an iterative optimization loop. An efficient global optimization algorithm termed as the repeated weighted boosting aided search is employed first to identify the unknown SIMO channel model, and then the Viterbi algorithm is used for the maximum likelihood sequence estimation of the unknown data sequence. A simulation example is used for demonstrating the efficiency of this joint ML optimization scheme designed for blind adaptive SIMO systems
Joshua Davis: Author of Spare Parts
No full textCitation: K-State First (2016). Joshua Davis: Author of Spare Parts [Flier]. Manhattan, Kansas: K-State First.Flyer advertising Joshua Davis's author talk at Kansas State University
Steven Johnson Author Talk Poster
No full textK-State Book NetworkA poster advertising an author talk by Steven Johnson at Kansas State University on September 3, 2014. Steven Johnson's book "The Ghost Map" was the 2014-2015 common book
On physical-layer security over SIMO generalized–K fading channels
No full textIn this paper, we consider the transmission of confidential message through single-input-multiple-output (SIMO) identically and independent generalized-K fading channels in the presence of an eavesdropper. We derive the analytical expressions for the probability of strictly positive secrecy capacity (SPSC), secure outage probability (SOP), and average secrecy capacity (ASC) of SIMO systems. Numerical results are presented and verified via Monte Carlo simulation
Symmetric Radial Basis Function Assisted Space-Time Equalisation for Multiple Receive-Antenna Aided Systems
No full textThis contribution considers nonlinear space-time equalisation (STE) designed for single-input multiple-output (SIMO) systems. By exploiting the inherent symmetry of the underlying optimal Bayesian STE solution, a novel symmetric radial basis function (RBF) based STE scheme is proposed, which is capable of achieving the optimal Bayesian equalisation performance. The adaptive adjustment of the STE taps of this symmetric RBF (SRBF) based STE can be achieved by estimating the SIMO channel encountered using the classic least mean square channel estimator and computing the optimal RBF centres from the resultant SIMO channel matrix estimate. Our simulation results demonstrate that the performance of this SRBF based STE is robust with respect to the choice of the algorithmic parameters
Adaptive Bayesian Space-Time Equalisation for Multiple Receive-Antenna Assisted Single-Input Multiple-Output Systems
No full textThis contribution considers nonlinear space–time equalisation (STE) for multiple receive-antenna induced single-input multipleoutput (SIMO) systems. By exploiting the inherent symmetry of the underlying optimal Bayesian STE solution, a novel symmetric radial basis function (RBF) based STE scheme is proposed, which is capable of approaching the optimal Bayesian equalisation performance. Adaptive implementation of this symmetric RBF (SRBF) based STE can be achieved conveniently by estimating the SIMO channels using the least mean square channel estimator and computing the optimal RBF centres from the resulting SIMO channel matrix estimate. Simulation results also demonstrate that the performance of this SRBF based STE is robust with respect to the choice of the RBF variance value. The proposed adaptive solution is then extended to the space–time decision feedback equalisation (ST-DFE) structure
Coverage probability and achievable rate analysis of FFR-aided multi-user OFDM-based MIMO and SIMO systems
No full textExpressions are derived for the coverage probability and average rate of both multi-user multiple input multiple output (MU-MIMO) and single input multiple output (SIMO) systems in the context of a fractional frequency reuse (FFR) scheme. In particular, given a reuse region of 1 3 (FR3) and a reuse region of 1 (FR1) as well as a Signal-to-Interference-plus-noise- Ratio (SINR) threshold Sth, which decides the user assignment to either the FR1 or FR3 regions, we theoretically show that: (i) The optimal choice of Sth which maximizes the coverage probability is Sth = T , where T is the target SINR required for ensuring adequate coverage, and (ii) The optimal choice of Sth which maximizes the average rate is given by Sth = T ?, where T ? is a function of the path loss exponent, the number of antennas and of the fading parameters. The impact of frequency domain correlation amongst the OFDM sub-bands allocated to the FR1 and FR3 cell-regions is analysed and it is shown that the presence of correlation reduces both the coverage probability and the average throughput of the FFR network. Furthermore, the performance of our FFR-aided MU-MIMO and SIMO systems is compared. Our analysis shows that the (2×2) MU-MIMO system achieves 22.5% higher rate than the (1 × 3) SIMO system and for lower target SINRs, the coverage probability of a (2×2) MUMIMO system is comparable to a (1 × 3) SIMO system. Hence the former one may be preferred over the latter. Our simulation results closely match the analytical result
Going Beyond Counting First Authors in Author Co-citation Analysis
No full textThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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