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We propose a novel pilot structure for covariance matrix estimation in massive multiple-input multiple-output (MIMO) systems in which each user transmits two pilot sequences, with the second pilot sequence multiplied by a random phase-shift. The covariance matrix of a particular user is obtained by computing the sample cross-correlation of the channel estimates obtained from the two pilot sequences. This approach relaxes the requirement that all the users transmit their uplink pilots over the same set of symbols. We derive expressions for the achievable rate and the mean-squared error of the covariance matrix estimate when the proposed method is used with staggered pilots. The performance of the proposed method is compared with existing methods through simulations., 6 pages, 4 figures. Accepted for publication in IEEE Signal Processing Letters

A graphic equalizer is a high-order filter controlling the gain of several frequency bands. For good accuracy, graphic equalizers consisting of cascaded IIR filters have been of very high order. A previously proposed parallel graphic equalizer entailing twice as many second-order filter sections as there are bands can have a maximum approximation error of less than 1 dB, but its design is complicated. This letter proposes a cascade graphic equalizer having an accuracy comparable to the best parallel graphic equalizer, although only one second-order section is assigned per command gain. A key idea is to use band filters whose interaction with the two neighboring filters at their center frequency is exactly controlled. The filter gains are obtained using the least-squares method with one iteration step, which involves linear interpolation of the target gain vector, inversion of a square matrix, and a few matrix multiplications. The proposed method is compared with previous designs and is shown to be the most accurate one. The new graphic equalizer is widely useful for audio and music processing.

A joint robust transmit/receive adaptive beamforming for multiple-input multipleoutput (MIMO) radar based on probability-constrained optimization approach is developed in the case of Gaussian and arbitrary distributed mismatch present in both the transmit and receive signal steering vectors. A tight lower bound of the probability constraint is also derived by using duality theory. The formulated probability-constrained robust beamforming problem is nonconvex and NP-hard. However, we reformulate its cost function into a bi-quadratic function while the probability constraint splits into transmit and receive parts. Then, a block coordinate descent method based on second-order cone programming is developed to address the biconvex problem. Simulation results show an improved robustness of the proposed beamforming method as compared to the worst-case and other existing state-of-the-art joint transmit/receive robust adaptive beamforming methods for MIMO radar., Comment: 14 pages, 1 figure, Submitted to IEEE Signal Processing Letters on May 2015

The desired property of having the same beampattern for different columns of a beamspace transformation matrix (beamforming vectors) often plays a key importance in practical applications. At most ${2^{M - 1}} - 1$ beamforming vectors with the same beampattern can be generated from any given beamforming vector, where $M$ is the size of the beamforming vector. Thus, one can start with a single (mother) beamforming vector, which gives a desired beampattern, but may not satisfy some other desired properties, and generate all other beamforming vectors, which give the same beampattern, in a computationally efficient way. Then the beamforming vectors, which in addition satisfy other desired properties that the mother beamforming vector may not satisfy, can be selected. Such procedure is developed in this letter in the application to the transmit beamspace design that ensures practically important properties for multiple-input multiple-output radar. A computationally efficient sub-optimal method for selecting best beamforming vectors from a population of vectors that give the same beampattern is also developed.

A simple quantization scheme is proposed to adjust separately the amplitudes and phases of signals in a codebook-based Transmit Beamforming (TBF) scheme. The proposed quantization scheme is valid for both desired signal power maximization (egoistic TBF) and co-channel interference mitigation (altruistic TBF), and does not require an exhaustive search to find the optimal TBF vector. Performance results are presented when variable numbers of bits for amplitude and phase feedback resolutions are used for both egoistic and altruistic TBF schemes.

A blind target detector using the time reversal transmission is proposed in the presence of channel correlation. We calculate the exact moments of the test statistics involved. The derived moments are used to construct an accurate approximative Likelihood Ratio Test (LRT) based on multivariate Edgeworth expansion. Performance gain over an existing detector is observed in scenarios with channel correlation and relatively strong target signal., 4 pages, 2 figures. Submitted to IEEE Signal Processing Letters

Classical geometric waveforms used in virtual analog synthesis suffer from aliasing distortion when simple sampling is used. An efficient antialiasing technique is based on expressing the waveforms as a filtered sum of time-shifted approximately bandlimited polynomial-spline basis functions. It is shown that by optimizing the coefficients of the basis function so that the aliasing distortion is perceptually minimized, the alias-free bandwidth of classical waveforms can be expanded. With the best of the case examples given here, the generated impulse-train and sawtooth waveform are alias-free up to fundamental frequencies over 10 kHz when the sampling rate is 44.1 kHz.

An efficient allpass filter design method is introduced to match the dispersion characteristics of vibrating stiff strings. The proposed method designs an allpass filter in cascaded biquad form directly from the target group delay, placing the poles at frequencies at which the group delay area function achieves odd integer multiples of ?, and fixing the pole radii according to a smoothness parameter. The pole frequencies are seen to be roots of quartic polynomials, and an efficient approximation to the desired roots is provided. Design examples show the method to outperform a previous closed-form design. Furthermore, the proposed method can achieve an arbitrarily wide bandwidth of good approximation by increasing the filter order, as the method is numerically robust and yields stable allpass filters.

Heavy-tailed distributions are present in the characterization of different modern systems such as high-resolution imaging, cloud computing, and cognitive radio networks. Commonly, the cumulants of these distributions cannot be defined from a certain order, and this restricts the applicability of traditional methods. To fill this gap, the present letter extends the traditional Edgeworth and Cornish–Fisher expansions, which are based on the cumulants, to analogous asymptotic expansions based on the log-cumulants. The proposed expansions inherit the capability of log-cumulants to characterize heavy-tailed distributions and parallel traditional expansions. Thus, they are readily implemented. Interestingly, the proposed expansions are applicable for light-tailed distributions as well.