Improving the system capacity of broadband services using multiple high-altitude platforms

A method of significantly improving the capacity of high-altitude platform (HAP) communications networks operating in the millimeter-wave bands is presented. It is shown how constellations of HAPs can share a common frequency allocation by exploiting the directionality of the user antenna. The system capacity of such constellations is critically affected by the minimum angular separation of the HAPs and the sidelobe level of the user antenna. For typical antenna beamwidths of approximately 5/spl deg/ an inter-HAP spacing of 4 km is sufficient to deliver optimum performance. The aggregate bandwidth efficiency is evaluated, both theoretically using the Shannon equation, and using practical modulation and coding schemes, for multiple HAP configurations delivering either single or multiple cells. For the user antenna beamwidths used, it is shown that capacity increases are commensurate with the increase in the number of platforms, up to 10 HAPs. For increases beyond this the choice of constellation strategy becomes increasingly important

High-altitude platforms for wireless communications

The demand for high-capacity wireless services is bringing increasing challenges, especially for delivery of the “last mile”. Terrestrially, the need for line-of-sight propagation paths represents a constraint unless very large numbers of base-station masts are deployed, while satellite systems have capacity limitations. An emerging solution is offered by high-altitude platforms (HAPs) operating in the stratosphere at altitudes of up to 22 km to provide communication facilities that can exploit the best features of both terrestrial and satellite schemes. This paper outlines the application and features of HAPs, and some specific development programmes. Particular consideration is given to the use of HAPs for delivery of future broadband wireless communications

Multiplication-free iterative algorithm for the LS problem

Many iterative techniques are available to solve normal equations appearing in the linear least-squares (LS) problem. However, because of multiplications and divisions they cannot be effectively implemented in real time. A novel multiplication-free and division-free iterative technique, the dichotomous co-ordinate descent algorithm, which guarantees convergence to the true solution under realistic assumptions, is proposed

DFT-based frequency estimators with narrow acquisition range

The authors propose new frequency estimators, with narrow frequency acquisition range, which are based on the calculation of the discrete Fourier transform (DFT) of the input signal. The algorithms consist of two steps: coarse and fine search of the periodogram peak. This frequency estimator structure employing either parabolic interpolation, dichotomous search, two-rate spectral estimation or their combination for fine search allows a considerable decrease in computational load with respect to known estimators. The proposed estimators are shown to have accuracy performance close to that of the maximum likelihood (ML) estimator

Frequency estimation in slowly fading multipath channels

This paper concerns the estimation of a frequency offset of a known (pilot) signal propagated through a slowly fading multipath channel, such that channel parameters are considered to he constant over the observation interval. We derive a maximum-likelihood (ML) frequency estimation algorithm for additive Gaussian noise and path amplitudes having complex Gaussian distribution when covariance matrices of the fading and noise are known; we consider in detail the algorithm for the white noise and Rayleigh fading, in particular, for independent fading of path amplitudes and pilot signals with diagonal autocorrelation matrices. For the latter scenario, we also derive an ML frequency estimator when the power delay profile is unknown, but the noise variance and bounds for the path amplitude variances are specified; in particular, this algorithm can be used when path delays and amplitude variances are unknown. Finally, we consider frequency estimators which do not use a priori information about the noise variance; these algorithms are also operable without timing synchronization. All the frequency estimators exploit the multipath diversity by combining periodograms of multipath signal components and searching for the maximum of the combined statistic. For implementation of the algorithms, we use a fast Fourier transform-based coarse search and fine dichotomous search. We perform simulations to compare the algorithms. The simulation results demonstrate high accuracy performance of the proposed frequency estimators in wide signal-to-noise ratio and frequency acquisition range

Acoustic echo cancellation using frequency-domain spline identification

Low-complexity delayless acoustic echo cancellation techniques based on frequency-domain spline-identification are proposed and investigated. Two methods of approximation of the acoustic frequency response, both using B-splines, are considered: the optimal-spline method and the local-spline method. The optimal-spline method seeks the solution of a least squares problem. The most computationally demanding part of the method, solution of the normal equations, is implemented by using the low-complexity dichotomous coordinate descent algorithm. The local-spline method avoids solving the normal equations, enabling further simplification; this is at the expense of a slight degradation in the cancellation performance. A novel efficient double-talk detector is also proposed, being an inherent feature of the frequency-domain identification. Open-loop and closed-loop identification schemes with cubic splines are studied by simulation and compared with the fast affine projection (FAP) algorithm. The proposed techniques provide cancellation performance better than that of the FAP algorithm, especially in double-talk and noisy environments, with a lower complexity