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Modern communication networks require robust and adaptive communication protocols to optimize various performance metrics, such as latency and energy efficiency. Adaptive communication protocols require real-time estimation of critical system parameters, amongst which the average length of an optimal source code is of key importance, when data compression is involved. In this letter, we prove finite-sample estimates—along with their confidence levels—of the worst case average length of an optimal source code over a channel transmitting dependent data. More specifically, this is achieved by establishing a concentration inequality for the estimation of entropy of the source. Data dependence is modeled through stationary mixing. Evaluation of the proposed bounds is computationally efficient and can be used for real-time estimation.

Forward error correction (FEC) enables the receiver to detect and correct error in a packet. The fountain code, which is a subclass of FEC, is a linear code to have high scalability and low complexities, and the Luby transform (LT) code is the first practical fountain code. In this letter, we propose a new broadcast method to increase the reliability of broadcast data transfer using the LT code. The proposed method enhances the reliability of the broadcast using the LT code by adjusting the number of output packets depending on a target probability. We develop a new analytic model to derive the data restoration probability with given configuration of encoding and decoding process.

In this paper, we derive the exact expression for the packet error probability in the case of m-path diversity scheme with packet combining using majority decision technique. The individual paths are modeled as independent and slow-varying binary symmetric channels with distinct values for bit error probabilities. We introduce an equivalent channel probability and spreading coefficients to analyze the derived expression. MATLAB code for numerical evaluations and an illustrative example for cases m = 3, 5, 7, 9, and 11 were also presented.

Imperfect spectrum sensing in overlay spectrum sharing may cause collision between primary and secondary transmission resulting in performance degradation for primary users. To satisfy the quality of service requirement imposed by the primary service, the maximum probability of collision has to be kept below a given threshold. The collision, if occurs, also results in increasing error rate in the secondary system. What can be done if the secondary service needs better error rate than the value imposed by the collision constraint in the primary network? From secondary user perspective, this can be taken care of by employing channel coding techniques at the expense of effective rate reduction. Alternatively, one can increase the sensing time to reduce the collision probability at the expense of reducing the data transmission time. This also reduces the effective data rate for secondary users. In this letter, we compare these two approaches and demonstrate a situation where using rate-compatible Low-Density Parity-Check codes, the effective data rate for the coded case can be significantly more than that of the case without channel coding while exhibiting a considerably better performance. We then discuss necessary condition for such an advantage and come up with cases where increasing sensing time is preferred over adopting channel coding.

This article investigates the effect of erroneous channel estimation on performance of physical layer network coding over fading channels. In this scenario, the relay maps the superimposed noisy modulated data, received from the two end terminals, to network coded combination of the source packets. We consider channel estimation error to be Gaussian distributed and formulate the network coding error by the distance between real and estimated points in the channel coefficients plane. Using this model, we present a statistical lower bound on variance of estimation error that can be tolerated by the relay terminal without imposing a network coding error on the system.

This paper aims to explore the average achievable rate of two-user decentralized Gaussian interference channel in a non-ergodic block fading environment, assuming the channel gains are constant throughout one transmission block and vary independently for the next block. It is assumed the channel gains are not available at the transmitters, while direct and cross channel gains are perfectly available at the corresponding receivers. In this regard, under Gaussian codebook assumption and considering the signal arising from the other co-channel communication link is treated as an interference, a multi-layer coding strategy is exploited at each transmitter. Then, under individual transmit power constraints and in a Rayleigh block fading environment, the optimum power allocation across code layers is derived, showing the average achievable rate of using multi-layer coding outperforms that of using a single layer code.

We derive the random coding error exponent for dual-hop transmission over Nakagami-m fading channels with amplify-and-forward relaying. This information-theoretic measure allows us to determine the capacity and cutoff rate as well as to gain valuable insight into the inherent tradeoff between the communication reliability and transmission rate in such channels.

A closed-form upper bound on the average error probability is proposed for random block codes operating in multi-input multi-output (MIMO) systems. The bound exponentially decays to zero with increasing block length, and the obtained error exponent proves consistent with Gallager's random coding exponent and the information-theoretic channel capacity.

We derive the random coding error exponent for the time-independent flat fading channel with perfect knowledge of the channel state information (CSI) at both the receiver and the transmitter. That is, the CSI is feedback from the receiver to the transmitter. In such a situation, the transmitter is capable of optimizing the power allocation of the transmitted signal according to the fading state in order to obtain, for our case, the best error exponent. The power scheme obtained here is different from the water-pouring one, which is known to maximize the channel capacity.