Engineering topics
Publications and source records attributed to Pollara, F..
We propose a new solution to parallel concatenation of trellis codes with multilevel amplitude/phase modulations and a suitable iterative decoding structure. Examples are given for throughputs 2 bits/sec/Hz with 8PSK and 16QAM signal constellations.
In this article, we design new turbo codes that can achieve near-Shannon-limit performance. The design criterion for random interleavers is based on maximizing the effective free distance of the turbo code, i.e., the minimum output weight of codewords due to weight-2 input sequences. An upper bound on the effective free distance of a turbo code is derived. This upper bound can be achieved if the feedback connection of convolutional codes uses primitive polynomials. We review multiple turbo codes (parallel concatenation of q convolutional codes), which increase the so-called 'interleaving gain' as q and the interleaver size increase, and a suitable decoder structure derived from an approximation to the maximum a posteriori probability decision rule. We develop new rate 1/3, 2/3, 3/4, and 4/5 constituent codes to be used in the turbo encoder structure. These codes, for from 2 to 32 states, are designed by using primitive polynomials. The resulting turbo codes have rates b/n (b = 1, 2, 3, 4 and n = 2, 3, 4, 5, 6), and include random interleavers for better asymptotic performance. These codes are suitable for deep-space communications with low throughput and for near-Earth communications where high throughput is desirable. The performance of these codes is within 1 dB of the Shannon limit at a bit-error rate of 10(exp -6) for throughputs from 1/15 up to 4 bits/s/Hz.
A description is given of multiple turbo codes and a suitable decoder structure derived from an approximation to the maximum a posteriori probability (MAP) decision rule, which is substantially different from the decoder for two-code-based encoders.
It is shown how turbo codes and decoders can be used to improve the coding gain for deep-space communications, while decreasing the decoding complexity with respect to the large constraint length convolutional codes currently in use. Similar code constructions were used to build multiple-encoder turbo codes. This generalizes the turbo decoding concept to a truly distributed decoding system.
In this article we apply transfer function bounding techniques to obtain upper bounds on the bit-error rate for maximum likelihood decoding of turbo codes constructed with random permutations. These techniques are applied to two turbo codes with constraint length 3 and later extended to other codes. The performance predicted by these bounds is compared with simulation results. The bounds are useful in estimating the 'error floor' that is difficult to measure by simulation, and they provide insight on how to lower this floor. More refined bounds are needed for accurate performance measures at lower signal-to-noise ratios.
Automatic repeat request (ARQ) methods cannot increase the capacity of a memoryless channel. However, they can be used to decrease the complexity of the channel-coding system to achieve essentially error-free transmission and to reduce link margins when the channel characteristics are poorly predictable. This article considers ARQ methods on a power-limited channel (e.g., the deep-space channel), where it is important to minimize the total power needed to transmit the data, as opposed to a bandwidth-limited channel (e.g., terrestrial data links), where the spectral efficiency or the total required transmission time is the most relevant performance measure. In the analysis, we compare the performance of three reference concatenated coded systems used in actual deep-space missions to that obtainable by ARQ methods using the same codes, in terms of required power, time to transmit with a given number of retransmissions, and achievable probability of word error. The ultimate limits of ARQ with an arbitrary number of retransmissions are also derived.
A number of the claims for turbo codes as a great advance in coding theory are confirmed, and a complete description is presented of an encoder/decoder pair that could be suitable for PCS applications. A new simple method for trellis termination is described, the effect of interleaver choice on the weight distribution of the code is analyzed, and unequal rate components (which yield better performance) are introduced.
The relationship between transmission rate and source and channel signal-to-noise ratios (SNR's) is discussed for the transmission of a Gaussian source over a binary input, additive Gaussian channel, with a mean-squared distortion criterion. We point out that for any finite rate, and sufficiently high channel SNR, the fidelity criterion (reproduction SNR) is upper bounded by a function of the transmission rate. Thus, the performance becomes rate limited rather than power limited. This effect is not observed with the binary symmetric source, the binary-input Gaussian channel combination, or the Gaussian source, unconstrained-input Gaussian channel combination.
In this article, we introduce multiple turbo codes and a suitable decoder structure derived from an approximation to the maximum a posteriori probability (MAP) decision rule, which is substantially different from the decoder for two-code-based encoders. We analyze the effect of interleaver choice on the weight distribution of the code, and we describe simulation results on the improved performance of these new codes.
This article presents a study of seismic data compression techniques and a compression algorithm based on subband coding. The algorithm includes three stages: a decorrelation stage, a quantization stage that introduces a controlled amount of distortion to allow for high compression ratios, and a lossless entropy coding stage based on a simple but efficient arithmetic coding method. Subband coding methods are particularly suited to the decorrelation of nonstationary processes such as seismic events. Adaptivity to the nonstationary behavior of the waveform is achieved by dividing the data into separate blocks that are encoded separately with an adaptive arithmetic encoder. This is done with high efficiency due to the low overhead introduced by the arithmetic encoder in specifying its parameters. The technique could be used as a progressive transmission system, where successive refinements of the data can be requested by the user. This allows seismologists to first examine a coarse version of waveforms with minimal usage of the channel and then decide where refinements are required. Rate-distortion performance results are presented and comparisons are made with two block transform methods.
This paper presents a study of seismic data compression techniques and a compression algorithm based on subband coding. The compression technique described could be used as a progressive transmission system, where successive refinements of the data can be requested by the user. This allows seismologists to first examine a coarse version of waveforms with minimal usage of the channel and then decide where refinements are required. Rate-distortion performance results are presented and comparisons are made with two block transform methods.
Turbo codes were recently proposed by Berrou, Glavieux, and Thitimajshima, and it has been claimed these codes achieve near-Shannon-limit error correction performance with relatively simple component codes and large interleavers. A required E(b)/N(o) of 0.7 dB was reported for a bit error rate of 10(exp -5), using a rate 1/2 turbo code. However, some important details that are necessary to reproduce these results were omitted. This article confirms the accuracy of these claims, and presents a complete description of an encoder/decoder pair that could be suitable for deep-space applications, where lower rate codes can be used. We describe a new simple method for trellis termination, analyze the effect of interleaver choice on the weight distribution of the code, and introduce the use of unequal rate component codes, which yield better performance.
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We are interested in the problem of finding good codes for the Gaussian channel at low signal-to-noise ratio, and in estimating as accurately as possible their probability of error.
The coding performance of the Probe-Orbiter-Earth communication link is analyzed and compared for several cases. It is assumed that the coding system consists of a convolutional code at the Probe, a quantizer and another convolutional code at the Orbiter, and two cascaded Viterbi decoders or a combined decoder on the ground.
The performance achieved by some specific data compression algorithms is compared with absolute limits prescribed by rate distortion theory for Gaussian sources under the mean square error distortion criterion. These results show the gains available from source coding and can be used as a reference for the evaluation of future compression schemes. Some current schemes perform well, but there is still room for improvement.