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At least 127 records · Page 7

Information transmission with continuous variable quantum erasure channels

Quantum capacity, as the key figure of merit for a given quantum channel, upper bounds the channel's ability in transmitting quantum information. Identifying different types of channels, evaluating the corresponding quantum capacity, and finding the capacity-approaching coding scheme are the major tasks in quantum communication theory. Quantum channel in discrete variables has been discussed enormously based on various error models, while error model in the continuous variable channel has been less studied due to the infinite dimensional problem. In this paper, we investigate a general continuous variable quantum erasure channel. By defining an effective subspace of the continuous variable system, we find a continuous variable random coding model. We then derive the quantum capacity of the continuous variable erasure channel in the framework of decoupling theory. The discussion in this paper fills the gap of a quantum erasure channel in continuous variable setting and sheds light on the understanding of other types of continuous variable quantum channels.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

On the delay analysis of a TDMA channel with finite buffer capacity

The throughput performance of a TDMA channel with finite buffer capacity for transmitting data messages is considered. Each station has limited message buffer capacity and has Poisson message arrivals. Message arrivals will be blocked if the buffers are congested. Using the embedded Markov chain model, the solution procedure for the limiting system-size probabilities is presented in a recursive fashion. Numerical examples are given to demonstrate the tradeoffs between the blocking probabilities and the buffer sizing strategy.

Yan, T.-Y.↗

Capacity, cutoff rate, and coding for a direct-detection optical channel

It is shown that Pierce's pulse position modulation scheme with 2 to the L pulse positions used on a self-noise-limited direct detection optical communication channel results in a 2 to the L-ary erasure channel that is equivalent to the parallel combination of L completely correlated binary erasure channels. The capacity of the full channel is the sum of the capacities of the component channels, but the cutoff rate of the full channel is shown to be much smaller than the sum of the cutoff rates. An interpretation of the cutoff rate is given that suggests a complexity advantage in coding separately on the component channels. It is shown that if short-constraint-length convolutional codes with Viterbi decoders are used on the component channels, then the performance and complexity compare favorably with the Reed-Solomon coding system proposed by McEliece for the full channel. The reasons for this unexpectedly fine performance by the convolutional code system are explored in detail, as are various facets of the channel structure.

Massey, J. L.↗

Capacity, cutoff rate, and coding for a direct-detection optical channel

It is shown that when Pierce's pulse-position modulation scheme with 2 to the L power positions (where L is some positive integer) is used on a self-noise-limited direct-detection optical communication channel, there results a (2 to the L power)-ary erasure channel that is equivalent to the parallel combination of L completely correlated binary erasure channels. The capacity of the full channel is the sum of the capacities of the component channels, but the cutoff rate of the full channel is shown to be much smaller than the sum of the cutoff rates. An interpretation of the cutoff rate is given that suggests a complexity advantage in coding separately on the component channels. It is shown that if short-constraint length convolutional codes with Viterbi decoders are used on the component channels, then the performance and complexity compare favorably with the Reed-Solomon coding system proposed by McEliece (1979) for the full channel. The reasons for this unexpectedly fine performance by the convolutional code system are explored in detail, as are various facets of the channel structure.

Massey, J. L.↗

Figure of merit for direct-detection optical channels

The capacity and sensitivity of a direct-detection optical channel are calculated and compared to those of a white Gaussian noise channel. Unlike Gaussian channels in which the receiver performance can be characterized using the noise temperature, the performance of the direct-detection channel depends on both signal and background noise, as well as the ratio of peak to average signal power. Because of the signal-power dependence of the optical channel, actual performance of the channel can be evaluated only by considering both transmit and receive ends of the systems. Given the background noise power and the modulation bandwidth, however, the theoretically optimum receiver sensitivity can be calculated. This optimum receiver sensitivity can be used to define the equivalent receiver noise temperature and calculate the corresponding G/T product. It should be pointed out, however, that the receiver sensitivity is a function of signal power, and care must be taken to avoid deriving erroneous projections of the direct-detection channel performance.

Chen, C.-C.↗

Capacity of the Generalized Pulse-Position Modulation Channel

We show the capacity of a generalized pulse-position modulation (PPM) channel, where the input vectors may be any set that allows a transitive group of coordinate permutations, is achieved by a uniform input distribution. We derive a simple expression in terms of the Kullback Leibler distance for the binary case, and the asymptote in the PPM order. We prove a sub-additivity result for the PPM channel and use it to show PPM capacity is monotonic in the order.

Hamkins, J.↗

Capacity and capacity sensitivity of soft output optical channels

In this paper, we derive the capacity of pulse position modulation (PPM) on a general soft output, memoryless channel, and evaluate the capacity formula for a variety of optical channel models, including AWGN, webb (1), and Webb plus Gaussian distributions.

capacity↗

Capacity of noncoherent MFSK channels

Performance limits theoretically achievable over noncoherent channels perturbed by additive Gaussian noise in hard decision, optimal, and soft decision receivers are computed as functions of the number of orthogonal signals and the predetection signal-to-noise ratio. Equations are derived for orthogonal signal capacity, the ultimate MFSK capacity, and the convolutional coding and decoding limit. It is shown that performance improves as the signal-to-noise ratio increases, provided the bandwidth can be increased, that the optimum number of signals is not infinite (except for the optimal receiver), and that the optimum number decreases as the signal-to-noise ratio decreases, but is never less than 7 for even the hard decision receiver.

Bar-David, I.↗

Capacity of Pulse-Position Modulation (PPM) on Gaussian and Webb Channels

This article computes the capacity of various idealized soft-decision channels modeling an optical channel using an avalanche photodiode detector (APD) and pulse-position modulation (PPM). The capacity of this optical channel depends in a complicated way on the physical parameters of the APD and the constraints imposed by the PPM orthogonal signaling set. This article attempts to identify and separate the effects of several fundamental parameters on the capacity of the APD-detected optical PPM channel. First, an overall signal-to-noise ratio (SNR) parameter is de ned such that the capacity as a function of a bit-normalized version of this SNR drops precipitously toward zero at quasi-brick-wall limits on bit SNR that are numerically the same as the well-understood brick-wall limits for the standard additive white Gaussian noise (AWGN) channel. A second parameter is used to quantify the effects on capacity of one unique facet of the optical PPM channel (as compared with the standard AWGN channel) that causes the noise variance to be higher in signal slots than in nonsignal slots. This nonuniform noise variance yields interesting capacity effects even when the channel model is AWGN. A third parameter is used to measure the effects on capacity of the difference between an AWGN model and a non-Gaussian model proposed by Webb (see reference in [2]) for approximating the statistics of the APD-detected optical channel. Finally, a fourth parameter is used to quantify the blending of a Webb model with a pure AWGN model to account for thermal noise. Numerical results show that the capacity of M-ary orthogonal signaling on the Webb channel exhibits the same brick-wall Shannon limit, (M ln 2)=(M 1), as on the AWGN channel ( 1:59 dB for large M). Results also compare the capacity obtained by hard- and soft-output channels and indicate that soft-output channels o er a 3-dB advantage.

Dolinar, S.↗

Capacity of PPM on Gaussian and Webb Channels

This paper computes and compares the capacities of M-ary PPM on various idealized channels that approximate the optical communication channel: (1) the standard additive white Gaussian noise (AWGN) channel;(2) a more general AWGN channel (AWGN2) allowing different variances in signal and noise slots;(3) a Webb-distributed channel (Webb2);(4) a Webb+Gaussian channel, modeling Gaussian thermal noise added to Webb-distributed channel outputs.

Capacity PPM Webb Optical↗

Design, modeling, and analysis of multi-channel demultiplexer/demodulator

Traditionally, satellites have performed the function of a simple repeater. Newer data distribution satellite architectures, however, require demodulation of many frequency division multiplexed uplink channels by a single demultiplexer/demodulator unit, baseband processing and routing of individual voice/data circuits, and remodulation into time division multiplexed (TDM) downlink carriers. The TRW MCDD (Multichannel Demultiplexer/Multirate Demodulator) operates on a 37.4 MHz composite input signal. Individual channel data rates are either 64 Kbps or 2.048 Mbps. The wideband demultiplexer divides the input signal into 1.44 MHz segments containing either a single 2.048 Mbps channel or thirty two 64 Kbps channels. In the latter case, the narrowband demultiplexer further divides the single 1.44 MHz wideband channel into thirty two 45 KHz narrowband channels. With this approach the time domain Fast Fourier Transformation (FFT) channelizer processing capacity is matched well to the bandwidth and number of channels to be demultiplexed. By using a multirate demodulator fewer demodulators are required while achieving greater flexibility. Each demodulator can process a wideband channel or thirty two narrowband channels. Either all wideband channels, a mixture of wideband and narrowband channels, or all narrowband channels can be demodulated. The multirate demodulator approach also has lower nonrecurring costs since only one design and development effort is needed. TRW has developed a proof of concept (POC) model which fully demonstrates the signal processing fuctions of MCDD. It is capable of processing either three 2.048 Mbps channels or two 2.048 Mbps channels and thirty two 64 Kbps channels. An overview of important MCDD system engineering issues is presented as well as discussion on some of the Block Oriented System Simulation analyses performed for design verification and selection of operational parameters of the POC model. Systems engineering analysis of the POC model confirmed that the MCDD concepts are not only achievable but also balance the joint goals of minimizing on-board complexity and cost of ground equipment, while retaining the flexibility needed to meet a wide range of system requirements.

Lee, David D.↗

Maximizing throughput over an average-power-limited and band-limited optical pulse position modulation channel

Given an optical pulse position modulation (PPM) channel, with an average power constraint and a bandwidth constraint, the word length needed to maximize the information throughput achievable by the channel is determined. It is shown that, to achieve the maximal capacity, the channel must be operated with a high erasure probability. This implies that coding schemes capable of compensating for a high percentage of erasures are needed for the PPM channel.

Zwillinger, D.↗

A minimum assumption approach to MEG sensor array design

Objective. Our objective is to formulate the problem of the magnetoencephalographic (MEG) sensor array design as a well-posed engineering problem of accurately measuring the neuronal magnetic fields. This is in contrast to the traditional approach that formulates the sensor array design problem in terms of neurobiological interpretability the sensor array measurements. Approach. We use the vector spherical harmonics (VSH) formalism to define a figure-of-merit for an MEG sensor array. We start with an observation that, under certain reasonable assumptions, any array of m perfectly noiseless sensors will attain exactly the same performance, regardless of the sensors' locations and orientations (with the exception of a negligible set of singularly bad sensor configurations). We proceed to the conclusion that under the aforementioned assumptions, the only difference between different array configurations is the effect of (sensor) noise on their performance. We then propose a figure-of-merit that quantifies, with a single number, how much the sensor array in question amplifies the sensor noise. Main results. We derive a formula for intuitively meaningful, yet mathematically rigorous figure-of-merit that summarizes how desirable a particular sensor array design is. We demonstrate that this figure-of-merit is well-behaved enough to be used as a cost function for a general-purpose nonlinear optimization methods such as simulated annealing. We also show that sensor array configurations obtained by such optimizations exhibit properties that are typically expected of 'high-quality' MEG sensor arrays, e.g. high channel information capacity. Significance. Our work paves the way toward designing better MEG sensor arrays by isolating the engineering problem of measuring the neuromagnetic fields out of the bigger problem of studying brain function through neuromagnetic measurements.

60 APPLIED LIFE SCIENCES↗

What exactly does Bekenstein bound?

The Bekenstein bound posits a maximum entropy for matter with finite energy confined to a spatial region. It is often interpreted as a fundamental limit on the information that can be stored by physical objects. In this work, we test this interpretation by asking whether the Bekenstein bound imposes constraints on a channel's communication capacity, a context in which information can be given a mathematically rigorous and operationally meaningful definition. We study specifically the Unruh channel that describes a stationary Alice exciting different species of free scalar fields to send information to an accelerating Bob, who is confined to a Rindler wedge and exposed to the noise of Unruh radiation. We show that the classical and quantum capacities of the Unruh channel obey the Bekenstein bound that pertains to the decoder Bob. In contrast, even at high temperatures, the Unruh channel can transmit a significant number of zero-bits , which are quantum communication resources that can be used for quantum identification and many other primitive protocols. Therefore, unlike classical bits and qubits, zero-bits and their associated information processing capability are generally not constrained by the Bekenstein bound. However, we further show that when both the encoder and the decoder are restricted, the Bekenstein bound does constrain the channel capacities, including the zero-bit capacity.

Hayden, Patrick [Stanford University, CA (United S↗

Capacity limit of the noiseless, energy-efficient optical PPM channel

It is shown that even though the capacity per photon can be made to increase without bound, the capacity per channel use (for best power efficiency) is always less than 2 nats per symbol. Furthermore, it approaches 2 nats per symbol as the bandwidth expansion factor goes to infinity.

Lesh, J. R.↗