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At least 19 records

Bandwidth limitations on noiseless optical channel capacity

The channel capacity of an optical communications link utilizing direct photon detection can be substantially larger than the heterodyne detection quantum limit. In the limit of a noiseless channel the capacity per received photon can even be infinite. In most communications systems the real constraint is to deliver a certain throughput capacity measured in nats/second. The current investigation has the objective to show that due to physical limitations on the minimum time resolution which can be achieved, and for any given throughput capacity in nats/second, there exists an optimum PPM word size which maximizes the 'power efficiency capacity' expressed in nats/photon. Such an optimization will allow the system-designer to minimize the amount of power needed to achieve the desired throughput without violating his bandwidth constraint.

Butman, S. A.

Channel capacity of an array system for Gaussian channels with applications to combining and noise cancellation

A closed-form expression for the capacity of an array of correlated Gaussian channels is derived. It is shown that when signal and noise are independent, the array of observables can be replaced with a single observable without diminishing the capacity of the array channel. Examples are provided to illustrate the dependence of channel capacity on noise correlation for two- and three-channel arrays.

Cheung, K. M.

Channel Capacity of an Array System for Gaussian Channels With Applications to Combining and Noise Cancellation

A closed-form expression for the capacity of an array of correlated Gaussian channels is derived. It is shown that when signal and noise are independent, the array of observables can be replaced with a single observable without diminishing the capacity of the array channel. Examples are provided to illustrate the dependence of channel capacity on noise correlation for two- and three-channel arrays.

Cheung, K.-M.

Large Array Channel Capacity 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 tropospheric channel variations. Channel capacity is expressed as the ratio of determinants of covariance matrices characterizing source, interference, and additive noise, and then reduced to a simpler quadratic form more amenable to analysis and numerical computation. 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.

Vilnrotter, V.

Error Rates and Channel Capacities in Multipulse PPM

A method of computing channel capacities and error rates in multipulse pulse-position modulation (multipulse PPM) has been developed. The method makes it possible, when designing an optical PPM communication system, to determine whether and under what conditions a given multipulse PPM scheme would be more or less advantageous, relative to other candidate modulation schemes. In conventional M-ary PPM, each symbol is transmitted in a time frame that is divided into M time slots (where M is an integer >1), defining an M-symbol alphabet. A symbol is represented by transmitting a pulse (representing 1) during one of the time slots and no pulse (representing 0 ) during the other M 1 time slots. Multipulse PPM is a generalization of PPM in which pulses are transmitted during two or more of the M time slots.

Hamkins, Jon

Channel capacity of Moore automata.

Algorithm for calculating Moore automaton or connected network channel capacity and source of input symbols for full capacity utilization

Conant, R. C.

Asynchronous multiple-access channel capacity

The capacity region for the discrete memoryless multiple-access channel without time synchronization at the transmitters and receivers is shown to be the same as the known capacity region for the ordinary multiple-access channel. The proof utilizes time sharing of two optimal codes for the ordinary multiple-access channel and uses maximum likelihood decoding over shifts of the hypothesized transmitter words.

Cover, T. M.

Radiometric resolution enhancement by lossy compression as compared to truncation followed by lossless compression

Recent advances in imaging technology make it possible to obtain imagery data of the Earth at high spatial, spectral and radiometric resolutions from Earth orbiting satellites. The rate at which the data is collected from these satellites can far exceed the channel capacity of the data downlink. Reducing the data rate to within the channel capacity can often require painful trade-offs in which certain scientific returns are sacrificed for the sake of others. In this paper we model the radiometric version of this form of lossy compression by dropping a specified number of least significant bits from each data pixel and compressing the remaining bits using an appropriate lossless compression technique. We call this approach 'truncation followed by lossless compression' or TLLC. We compare the TLLC approach with applying a lossy compression technique to the data for reducing the data rate to the channel capacity, and demonstrate that each of three different lossy compression techniques (JPEG/DCT, VQ and Model-Based VQ) give a better effective radiometric resolution than TLLC for a given channel rate.

Tilton, James C.

Capacity of a direct detection optical communication channel

The capacity of a free space optical channel using a direct detection receiver is derived under both peak and average signal power constraints and without a signal bandwidth constraint. The addition of instantaneous noiseless feedback from the receiver to the transmitter does not increase the channel capacity. In the absence of received background noise, an optimally coded PPM system is shown to achieve capacity in the limit as signal bandwidth approaches infinity. In the case of large peak to average signal power ratios, an interleaved coding scheme with PPM modulation is shown to have a computational cutoff rate far greater than ordinary coding schemes.

Tan, H. H.

Bandwidth efficient coding: Theoretical limits and real achievements. Error control techniques for satellite and space communications

In his seminal 1948 paper 'The Mathematical Theory of Communication,' Claude E. Shannon derived the 'channel coding theorem' which has an explicit upper bound, called the channel capacity, on the rate at which 'information' could be transmitted reliably on a given communication channel. Shannon's result was an existence theorem and did not give specific codes to achieve the bound. Some skeptics have claimed that the dramatic performance improvements predicted by Shannon are not achievable in practice. The advances made in the area of coded modulation in the past decade have made communications engineers optimistic about the possibility of achieving or at least coming close to channel capacity. Here we consider the possibility in the light of current research results.

Costello, Daniel J., Jr.

The Future of the Deep Space Network: Technology Development for K2-Band Deep Space Communications

Projections indicate that in the future the number of NASA's robotic deep space missions is likely to increase significantly. A launch rate of up to 4-6 launches per year is projected with up to 25 simultaneous missions active [I]. Future high resolution mapping missions to other planetary bodies as well as other experiments are likely to require increased downlink capacity. These future deep space communications requirements will, according to baseline loading analysis, exceed the capacity of NASA's Deep Space Network in its present form. There are essentially two approaches for increasing the channel capacity of the Deep Space Network. Given the near-optimum performance of the network at the two deep space communications bands, S-Band (uplink 2.025-2.120 GHz, downlink 2.2-2.3 GHz), and X-Band (uplink 7.145-7.19 GHz, downlink 8.48.5 GHz), additional improvements bring only marginal return for the investment. Thus the only way to increase channel capacity is simply to construct more antennas, receivers, transmitters and other hardware. This approach is relatively low-risk but involves increasing both the number of assets in the network and operational costs.

Bhanji, Alaudin M.