Current Issue : July - September Volume : 2014 Issue Number : 3 Articles : 5 Articles
Affine arithmetic (AA) is widely used in range analysis in word-length optimization of hardware designs. To reduce the\nuncertainty in the AA and achieve efficient and accurate range analysis of multiplication, this paper presents a novel\nrefined affine approximation method, Approximation Affine based on Space Extreme Estimation (AASEE). The affine\nform of multiplication is divided into two parts. The first part is the approximate affine form of the operation. In the\nsecond part, the equivalent affine form of the estimated range of the difference, which is introduced by the\napproximation, is represented by an extra noise symbol. In AASEE, it is proven that the proposed approximate affine\nform is the closest to the result of multiplication based on linear geometry. The proposed equivalent affine form of\nAASEE is more accurate since the extreme value theory of multivariable functions is used to minimize the difference\nbetween the result of multiplication and the approximate affine form. The computational complexity of AASEE is the\nsame as that of trivial range estimation (AATRE) and lower than that of Chebyshev approximation (AACHA). The\nproposed affine form of multiplication is demonstrated with polynomial approximation, B-splines, and multivariate\npolynomial functions. In experiments, the average of the ranges derived by AASEE is 59% and 89% of that by AATRE\nand AACHA, respectively. The integer bits derived by AASEE are 2 and 1 b less than that by AATRE and AACHA at most,\nrespectively....
Matrix theory plays an important role in precoding methodology for multiple input multiple output (MIMO) systems.\nIn this paper, an improved block diagonal (BD) precoding scheme is proposed for a MIMO multicast channel with two\nusers, where the unitary precoding matrix is constructed in a block-wise form by joint triangularization\ndecomposition. In order to reduce large signal-to-noise ratios (SNRs) spread across different transmitted data streams\nand users, the combination of joint equi-diagonal triangularization (JET) and joint geometric mean decomposition\n(JGMD) is applied to submatrix construction in the inner process of this precoding scheme. An elaborate\nimplementation is presented, and the existence condition of JGMD is also investigated for two complex-valued\nmatrices with two columns, where the analytical result reveals the connection with the particular channel realization\nand essentially determines when to consider JGMD for submatrix construction. In addition, the properties of the\ndiagonal elements generated by joint triangularization decomposition are discussed as well as the computational\ncomplexity of the proposed scheme. Simulation results indicate that in general, JGMD is employed with high\nprobability in the hybrid model, and the proposed scheme readily outperforms the JET scheme in terms of bit error\nrate (BER) performance in the moderate to high SNR regimes....
In this paper, a cooperative transmission protocol for cognitive radio systems is proposed. In this protocol, the\nprimary system comprises a transmitter (PT), a receiver (PR), and a decode-and-forward relay (Relay), while the\nsecondary system comprises a transmitter (ST) and a receiver (SR). Both the ST and the Relay assist the transmissions\nof the primary users together. The outage probabilities of the primary system and the secondary system are analyzed\nand verified through simulations. In order to decrease outage probability of the secondary system, power allocation\nis performed at the ST. However, it will lead to deterioration of outage performance of the primary system. In order\nto guarantee outage performance of the primary system, a Relay is employed. Compared with two existing protocols,\none without cooperation and the other with cooperation of the secondary system only, the proposed protocol\nis able to better balance outage performances of the primary system and the secondary system....
This paper presents a joint time-delay and channel estimator to assess the achievable positioning performance of the\nLong Term Evolution (LTE) system in multipath channels. LTE is a promising technology for localization in urban and\nindoor scenarios, but its performance is degraded due to the effect of multipath. In those challenging environments,\nLTE pilot signals are of special interest because they can be used to estimate the multipath channel and counteract its\neffect. For this purpose, a channel estimation model based on equi-spaced taps is combined with the time-delay\nestimation, leading to a low-complexity estimator. This model is enhanced with a novel channel parameterization\nable to characterize close-in multipath, by introducing an arbitrary tap with variable position between the first two\nequi-spaced taps. This new hybrid approach is adopted in the joint maximum likelihood (JML) time-delay estimator to\nimprove the ranging performance in the presence of short-delay multipath. The JML estimator is then compared with\nthe conventional correlation-based estimator in usual LTE conditions. These conditions are characterized by the\nextended typical urban (ETU) multipath channel model, additive white Gaussian noise (AWGN) and LTE signal\nbandwidths equal to 1.4, 5 and 10 MHz. The resulting time-delay estimation performance is assessed by computing\nthe cumulative density function (CDF) of the errors in the absence of noise and the root-mean-square error (RMSE)\nand bias for signal-to-noise ratio (SNR) values between -20 and 30 dB....
In this paper, the important problem of single-channel noise reduction is treated from a new perspective. The\nproblem is posed as a filtering problem based on joint diagonalization of the covariance matrices of the desired and\nnoise signals. More specifically, the eigenvectors from the joint diagonalization corresponding to the least significant\neigenvalues are used to form a filter, which effectively estimates the noise when applied to the observed signal. This\nestimate is then subtracted from the observed signal to form an estimate of the desired signal, i.e., the speech signal.\nIn doing this, we consider two cases, where, respectively, no distortion and distortion are incurred on the desired\nsignal. The former can be achieved when the covariance matrix of the desired signal is rank deficient, which is the\ncase, for example, for voiced speech. In the latter case, the covariance matrix of the desired signal is full rank, as is the\ncase, for example, in unvoiced speech. Here, the amount of distortion incurred is controlled via a simple, integer\nparameter, and the more distortion allowed, the higher the output signal-to-noise ratio (SNR). Simulations\ndemonstrate the properties of the two solutions. In the distortionless case, the proposed filter achieves only a slightly\nworse output SNR, compared to the Wiener filter, along with no signal distortion. Moreover, when distortion is\nallowed, it is possible to achieve higher output SNRs compared to the Wiener filter. Alternatively, when a lower output\nSNR is accepted, a filter with less signal distortion than the Wiener filter can be constructed...
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