A lower bound on the cutoff rate for Gaussian channels withpeak-limited inputs

A lower bound on the cutoff rate R_O of a dispersive Gaussian channel with peak- rather than average-power-limited input is evaluated and compared to the lower bound on capacity under the same input constraints. It is assumed that the input symbols are independent and uniformly distributed. Both bounds exhibit the same behavior as a function of an appropriately defined signal-to-noise ratio (SNR), with a discrepancy of 1.68 dB to the disadvantage of R_O, at high SNRs. The lower bound on R_O is evaluated for peak- and slope-limited signals that model magnetic recording systems and is compared to the lower bound on capacity     

Information rates for magnetic recording channels with peak- andslope-limited magnetization

A model for magnetic recording is proposed which uses two parameters to describe the limitations on the remanent magnetization in the medium: the dimensionless peak value A_m and the steepest slope B(s^-1). A low-pass bandwidth restriction W(s^-1) due to read circuits is also included. Lower and upper bounds on the achievable transmission rates are derived in terms of the signal-to-noise ratio. For the case of ideal low-pass restriction with B≪W, the bounds increase linearly, logarithmically, and as the cube root, with low, medium, and large ρ_B, respectively. With B≪ W the problem reduces to the one with no restriction on the slope     

Capacity and coding for the Gilbert-Elliot channels

The Gilbert-Elliott channel, a varying binary symmetric channel, with crossover probabilities determined by a binary-state Markov process, is treated. In general, such a channel has a memory that depends on the transition probabilities between the states. A method of calculating the capacity of this channel is introduced and applied to several examples, and the question of coding is addressed. In the conventional usage of varying channels, a code suitable for memoryless channels is used in conjunction with an interleaver, with the decoder considering the deinterleaved symbol stream as the output of a derived memoryless channel. The transmission rate is limited by the capacity of this memoryless channel, which is often considerably less than the capacity of the original channel. A decision-feedback decoding algorithm that completely recovers this capacity loss is introduced. It is shown that the performance of a system incorporating such an algorithm is determined by an equivalent genie-aided channel, the capacity of which equals that of the original channel. The calculated random coding exponent of the genie-aided channel indicates a considerable increase in the cutoff rate over that of the conventionally derived memoryless channel     

On information transfer by envelope-constrained signals over theAWGN channel

Using T.E. Duncan's theorem (1970) on the relation between mutual information and the mean-square error of the optimum causal estimator of a random signal in additive white Gaussian noise (AWGN), the maximum achievable information transfer over the AWGN channel is derived with the random telegraph wave input. The information transfer is bounded and symptotically determined for the Wiener phase-modulated process input at large signal-to-noise ratio (SNR). Both results are compared to the information transfer for the capacity-achieving Gauss-Markov input process. For both the Wiener phase-modulated and the Gauss-Markov processes the information transfer increases asymptotically as the square root of SNR, but for the random telegraph wave it increases only as its logarithm     

Augmented APP (A2P2) module for a posterioriprobability calculation and channel parameter tracking

The augmented a posteriori probability (APP) module, denoted by A ²P², comprises two mutually supporting algorithms: (1) a soft-input soft-output (SISO) APP module, adjusted to output edge metric information and (2) a recursive estimator for the channel parameters that benefits from this information at each step of the recursion. The thus-estimated parameters appropriately transform, in turn, the channel output signals that feed the SISO module. When applied to decoding a parallel concatenated convolutional code (PCCC) transmitted by binary phase-shift keying through a channel with frequency offset (0.08/T_s Hz) and phase jitter (0.23-rad RMS), concentrated at 0.01/T_s Hz, (T_s-symbol duration), the degradation compared to fully coherent reception is a small fraction of 1 dB, without use of a preamble     

Collision resolution algorithms in multistation packet-radionetworks

The performance of a multistation packet-radio network in which the nodes of the network employ some collision resolution algorithm (CRA) for accessing a shared radio channel is analyzed. The two CRAs considered here are the binary-tree CRA (BTCRA) and the clipped binary-tree CRA (CBTCRA). The exact analysis of a multistation network with these access schemes is intractable. Therefore, the authors present an approximate method that captures the interactions among the nodes of different stations. The mean idea is to view the interference among the nodes of different stations as independent random noises and compute the probabilities of these noises, taking into account the interactions between the nodes. Numerical results of the approximate analysis are presented and compared with the results of simulations