Fountain Capacity

Fountain codes are currently employed for reliable and efficient transmission of information via erasure channels with unknown erasure rates. This correspondence introduces the notion of fountain capacity for arbitrary channels. In contrast to the conventional definition of rate, in the fountain setup the definition of rate penalizes the reception of symbols by the receiver rather than their transmission. Fountain capacity measures the maximum rate compatible with reliable reception regardless of the erasure pattern. We show that fountain capacity and Shannon capacity are equal for stationary memoryless channels. In contrast, Shannon capacity may exceed fountain capacity if the channel has memory or is not stationary

Fountain Capacity

Fountain codes are currently employed for reliable and efficient transmission of information via erasure channels with unknown erasure rates. This correspondence introduces the notion of fountain capacity for arbitrary channels. In contrast to the conventional definition of rate, in the fountain setup the definition of rate penalizes the reception of symbols by the receiver rather than their transmission. Fountain capacity measures the maximum rate compatible with reliable reception regardless of the erasure pattern. We show that fountain capacity and Shannon capacity are equal for stationary memoryless channels. In contrast, Shannon capacity may exceed fountain capacity if the channel has memory or is not stationary

Distributed Information Bottleneck for a Primitive Gaussian Diamond MIMO Channel

This paper considers the distributed information bottleneck (D-IB) problem for a primitive Gaussian diamond channel with two relays and MIMO Rayleigh fading. The channel state is an independent and identically distributed (i.i.d.) process known at the relays but unknown to the destination. The relays are oblivious, i.e., they are unaware of the codebook and treat the transmitted signal as a random process with known statistics. The bottleneck constraints prevent the relays to communicate the channel state information (CSI) perfectly to the destination. To evaluate the bottleneck rate, we provide an upper bound by assuming that the destination node knows the CSI and the relays can cooperate with each other, and also two achievable schemes with simple symbol-by-symbol relay processing and compression. Numerical results show that the lower bounds obtained by the proposed achievable schemes can come close to the upper bound on a wide range of relevant system parameters

Hadamard upper bound on optimum joint decoding capacity of Wyner Gaussian cellular MAC

This article presents an original analytical expression for an upper bound on the optimum joint decoding capacity of Wyner circular Gaussian cellular multiple access channel (C-GCMAC) for uniformly distributed mobile terminals (MTs). This upper bound is referred to as Hadamard upper bound (HUB) and is a novel application of the Hadamard inequality established by exploiting the Hadamard operation between the channel fading matrix G and the channel path gain matrix Ω. This article demonstrates that the actual capacity converges to the theoretical upper bound under the constraints like low signal-to-noise ratios and limiting channel path gain among the MTs and the respective base station of interest. In order to determine the usefulness of the HUB, the behavior of the theoretical upper bound is critically observed specially when the inter-cell and the intra-cell time sharing schemes are employed. In this context, we derive an analytical form of HUB by employing an approximation approach based on the estimation of probability density function of trace of Hadamard product of two matrices, i.e., G and Ω. A closed form of expression has been derived to capture the effect of the MT distribution on the optimum joint decoding capacity of C-GCMAC. This article demonstrates that the analytical HUB based on the proposed approximation approach converges to the theoretical upper bound results in the medium to high signal to noise ratio regime and shows a reasonably tighter bound on optimum joint decoding capacity of Wyner GCMAC

Secured Communication over Frequency-Selective Fading Channels: a practical Vandermonde precoding

In this paper, we study the frequency-selective broadcast channel with confidential messages (BCC) in which the transmitter sends a confidential message to receiver 1 and a common message to receivers 1 and 2. In the case of a block transmission of N symbols followed by a guard interval of L symbols, the frequency-selective channel can be modeled as a N * (N+L) Toeplitz matrix. For this special type of multiple-input multiple-output (MIMO) channels, we propose a practical Vandermonde precoding that consists of projecting the confidential messages in the null space of the channel seen by receiver 2 while superposing the common message. For this scheme, we provide the achievable rate region, i.e. the rate-tuple of the common and confidential messages, and characterize the optimal covariance inputs for some special cases of interest. It is proved that the proposed scheme achieves the optimal degree of freedom (d.o.f) region. More specifically, it enables to send l <= L confidential messages and N-l common messages simultaneously over a block of N+L symbols. Interestingly, the proposed scheme can be applied to secured multiuser scenarios such as the K+1-user frequency-selective BCC with K confidential messages and the two-user frequency-selective BCC with two confidential messages. For each scenario, we provide the achievable secrecy degree of freedom (s.d.o.f.) region of the corresponding frequency-selective BCC and prove the optimality of the Vandermonde precoding. One of the appealing features of the proposed scheme is that it does not require any specific secrecy encoding technique but can be applied on top of any existing powerful encoding schemes.Comment: To appear in EURASIP journal on Wireless Communications and Networking, special issue on Wireless Physical Security, 200

Power-Law Inter-Spike Interval Distributions Infer a Conditional Maximization of Entropy in Cortical Neurons

The brain is considered to use a relatively small amount of energy for its efficient information processing. Under a severe restriction on the energy consumption, the maximization of mutual information (MMI), which is adequate for designing artificial processing machines, may not suit for the brain. The MMI attempts to send information as accurate as possible and this usually requires a sufficient energy supply for establishing clearly discretized communication bands. Here, we derive an alternative hypothesis for neural code from the neuronal activities recorded juxtacellularly in the sensorimotor cortex of behaving rats. Our hypothesis states that in vivo cortical neurons maximize the entropy of neuronal firing under two constraints, one limiting the energy consumption (as assumed previously) and one restricting the uncertainty in output spike sequences at given firing rate. Thus, the conditional maximization of firing-rate entropy (CMFE) solves a tradeoff between the energy cost and noise in neuronal response. In short, the CMFE sends a rich variety of information through broader communication bands (i.e., widely distributed firing rates) at the cost of accuracy. We demonstrate that the CMFE is reflected in the long-tailed, typically power law, distributions of inter-spike intervals obtained for the majority of recorded neurons. In other words, the power-law tails are more consistent with the CMFE rather than the MMI. Thus, we propose the mathematical principle by which cortical neurons may represent information about synaptic input into their output spike trains

On exploiting the interference structure for reliable communications

Abstract-1Consider an additive Gaussian noise channel affected by an additive interference sequence, taken from a given codebook, which is known non-causally at the transmitter (e.g., via prior decoding). It is known that in this case optimal performance is attained by Dirty Paper Coding, which treats the interference signal as unstructured. In other words, for this example, the knowledge of the specific interferer&apos;s codebook at the decoder is not useful in terms of capacity. In this paper, two variations of this basic scenario are presented in which treating interference as unstructured is instead generally suboptimal. In the first case, a second encoder of the source message is present in the system that is not aware of the interferer&apos;s sequence, and source and interference messages are uncorrelated; In the second case, the sources encoded by the informed transmitter and interferer are correlated (and an uninformed encoder may or may not be present). Results are given in terms of conditions for achievability for both discrete and Gaussian models of the scenarios discussed above, and corroborated by numerical results. Optimal strategies are also identified in special cases. The conclusions herein point to the importance of exploiting the interfererence structure in multiterminal and source-channel coding scenarios. I

Compound relay channel with informed relay and destination

A two-state compound relay channel is considered where the relay and the destination are informed about the channel state while the source is not. Achievable rates and upper bounds are derived for discrete memoryless and Gaussian models, and specialized to a scenario with orthogonal components. It is shown that, apart from some special cases, optimality conditions valid for decode-and-forward (DF)-based solutions on a standard relay channel do not carry over to a compound setting, and more fl exible transmission strategies are generally advantageous. For instance, partial decode-and-forward (PDF) that superimposes transmission of three layers and uses joint decoding at the destination performs better than the standard two-layer PDF with successive decoding, even when the latter is optimal for the regular relay channel. Moreover, the capacity is derived in the special case in which the relay is not active in one state. Extension to the broadcast coding approach, as an alternative to the compound model, is also discussed. ©2009 IEEE