Capacity of large array receivers for deep-space communications in the presence of interference

We develop a model for a large array ground receiver system for use in deep space communications, and analyze the resulting array channel capacity. The model includes effects of array geometry, time-dependent spacecraft orbital trajectory, point and extended interference sources, and elevation- dependent noise and atmospheric channel variations. Channel capacity is expressed as a simple quadratic form dependent upon covariance matrices characterizing the source, interference, and additive noise. This formulation facilitates inclusion of array and channel characteristics into the model, as well as comparison of optimal, suboptimal and equivalent single-antenna configurations on achievable throughput. Realistic examples of ground array channel capacity calculations are presented, demonstrating the impact of array geometry, planetary interference sources, and array combining algorithm design upon the achievable data throughput.     

Adaptive detector arrays for optical communications receivers

An optimal adaptive array receiver for use in groundbased optical communications is investigated. Kolmogorov phase screen simulations are used to generate realistic focal-plane distributions of the received optical fields in the presence of turbulence. The array detection concept reduces interference from background radiation by effectively assigning higher confidence levels at each instant of time to those detector elements that contain significant signal energy and suppressing those that do not. A simpler suboptimum structure that replaces the continuous weighting of the optimal receiver by a hard decision over each detector element is also described. It is shown that, for photon counting receivers observing Poisson distributed signals, performance improvements of up to 5 dB can be obtained over conventional single-detector photon counting receivers when observing turbulent optical fields in high background environments.     

Performance analysis and tradeoffs for dual-pulse PPM on optical communication channels with direct detection

The performance and tradeoffs of multipulse position modulation (MPPM) are investigated and compared with that of the traditional (single) pulse position modulation (PPM) scheme typically employed on the optical direct-detection channel. While the primary motivation for the consideration of the problem is to provide performance improvement for deep-space optical communications where narrow high-peak-power transmitted pulses offer significant advantages in terms of detection probabilities and background suppression capabilities at the receiver, the results obtained are sufficiently generic as to apply to other applications.     

Adaptive acquisition and tracking for deep space array feed antennas

The use of radial basis function (RBF) networks and least squares algorithms for acquisition and fine tracking of NASA's 70-m-deep space network antennas is described and evaluated. We demonstrate that such a network, trained using the computationally efficient orthogonal least squares algorithm and working in conjunction with an array feed compensation system, can point a 70-m-deep space antenna with root mean square (rms) errors of 0.1-0.5 millidegrees (mdeg) under a wide range of signal-to-noise ratios and antenna elevations. This pointing accuracy is significantly better than the 0.8 mdeg benchmark for communications at Ka-band frequencies (32 GHz). Continuous adaptation strategies for the RBF network were also implemented to compensate for antenna aging, thermal gradients, and other factors leading to time-varying changes in the antenna structure, resulting in dramatic improvements in system performance. The systems described here are currently in testing phases at NASA's Goldstone Deep Space Network (DSN) and were evaluated using Ka-band telemetry from the Cassini spacecraft.     

Maximum likelihood detection of PPM signals governed by arbitrarypoint-process plus additive Gaussian noise

The maximum likelihood decision statistic for pulse-position modulated (PPM) signals governed by an arbitrary discrete point process in the presence of additive Gaussian noise is derived. Sufficient conditions are given for determining when the optimum PPM symbol detection strategy is to choose the PPM symbol corresponding to the maximum slot statistic. In particular, it is shown that for the important case of Webb distributed avalanche photodiode output electrons in the presence of Gaussian noise, the optimum decision rule is to choose the largest slot observable     

Alamouti-type space-time coding for free-space optical communication with direct detection

A modification of the Alamouti code originally proposed for RF wireless applications is described that allows it to be applied in scenarios such as free-space optical communication with direct detection where unipolar modulations like pulse-position modulation and on-off keying are traditionally used to convey the information. The modification of the code and associated decision metric is such as to maintain all of the desirable properties of the original scheme.     

Real-time combining of residual carrier array signals using MLweight estimates

A real-time digital signal combining system for use with array feeds is proposed. The combining system attempts to compensate for signal-to-noise ratio (SNR) loss resulting from antenna deformations induced by gravitational and atmospheric effects. The combining weights are obtained directly from the observed residual carrier samples in each channel using a `sliding-window' implementation of a maximum-likelihood (ML) parameter estimator. It is shown that with averaging times of about 0.1 s, combining loss for a seven-element array can be limited to about 0.1 dB in a realistic operational environment. This result suggests that the real-time combining system proposed is capable of recovering virtually all of the signal power captured by the array feed, even in the presence of severe wind gusts and similar disturbances     

Channel assignments for improved gain in baseband array feedcompensation systems

The performance of a real-time digital combining system for use with array feeds has been considered in previous articles. The purpose of the combining operation is to recover signal-to-noise ratio (SNR) losses due to antenna deformations and atmospheric effects. Previously, arbitrary signal powers and noise variances were assumed, but no attempt was made to match the receiver channels to the available signal powers. Here it is shown that for any signal power and noise variance distribution, a “best” channel assignment exists that maximizes the combined SNR in the limit of vanishingly small combining losses. This limit can be approached in practice by observing sufficiently many samples. Specific signal power and noise variance distributions are considered, and it is shown that even relatively “noisy” channels can be used effectively to recover SNR losses resulting from signals diverted out of a “high-quality” channel by antenna deformations