In this paper, a new scheme for completely reliable transmission of the information (with an error probability tends to zero) in a wireless communication link will be proposed in which to compensate the effects of fading and multipath, adaptive modulation and coding is used. Obviously, by the practical forward error correction it is impossible to achieve error free communication. Removing the residual error is by an auto-forwarding system. Of course, if error correction coding capability is weak, number of retransmissions will be increased to the much needed and it severely undermines the system throughput. On the other hands, strong error correction capability needs high block length codes and high transmission power which are limited in practice. In this paper, a method for optimum combination of error correction and auto forwarding is provided. In this paper, link adaptation is based on imperfect Channel state information. Numerical results demonstrate efficiency of designed method.

Gaussian interference known at the transmitter can be fully canceled in a Gaussian communication Channel employing dirty paper coding, as Costa shows, when interference is independent of the Channel noise and when the Channel input designed independently of the interference. In this paper, a new and general version of the Gaussian Channel in presence of two-sided state information correlated to the Channel input and noise is considered. Determining a general achievable rate for the Channel and obtaining the capacity in a non-limiting case, we try to analyze and solve the Gaussian version of the Cover-Chiang theorem mathematically and information-theoretically. Our capacity theorem, while including all previous theorems as its special cases, explains situations that can not be analyzed by them; for example, the effect of the correlation between the side information and the Channel input on the capacity of the Channel that can not be analyzed with Costa’ s ― writing on dirty paper" theorem. Meanwhile, we try to exemplify the concept of ― cognition" of the transmitter or the receiver on a variable (here, the Channel noise) with the information-theoretic concept of ― side information" correlated to that variable and known at the transmitter or at the receiver. According to our theorem, the Channel capacity is an increasing function of the mutual information of the side information and the Channel noise.

In this paper the secrecy problem in the cognitive state-dependent interference Channel is considered. In this scenario we have a primary and a cognitive transmitter-receiver pairs. The cognitive transmitter has the message of the primary sender as side information. In addition, the state of the Channel is known at the cognitive encoder. Hence, the cognitive encoder uses this side information to cooperate with the primary transmitter. The message of the cognitive encoder must be secret at the primary receiver, i.e., the primary receiver act as an eavesdropper for the cognitive transmitter. An achievable rate region and an outer bound on the rate region in this Channel are derived. The results are extended to the previous works as special cases.

We address the throughput maximization problem for downlink transmission in DF-relay-assisted cognitive radio networks (CRNs) based on simultaneous wireless information and power transfer (SWIPT) capability. In this envisioned network, multiple-input multiple-output (MIMO) relay and secondary user (SU) equipment are designed to handle both radio frequency (RF) signal energy harvesting and SWIPT functional tasks. Additionally, the cognitive base station (CBS) communicates with the SU only via the MIMO relay. Based on the considered network model, several combined constraints of the main problem complicate the solution. Therefore, in this paper, we apply heuristic guidelines within the convex optimization framework to handle this complexity. First, consider the problem of maximizing throughput on both sides of the relay separately. Second, each side progresses to solve the complex problem optimally by adopting strategies for solving sub-problems. Finally, these optimal solutions are synthesized by proposing a heuristic iterative power allocation algorithm that satisfies the combinatorial constraints with short convergence times. The performance of the optimal proposed algorithm (OPA) is evaluated against benchmark algorithms via numerical results on optimality, convergence time, constraints’ compliance, and imperfect Channel state information (CSI) on the CBS-PU link.

In the present study, we analyze the multi-Channel service system with ordered entry from finite source and finite storage at each Channel. The arrival and service rates are assumed to be state dependent. The steady state probabilities of the system are obtained by using Chapmann-Kolmogorov equations. Some other performance indices viz. utilization of servers, expected number of units in the system and expected number of units at each Channel has been derived. A computational algorithm is developed to determine the optimal allocation of storage space facilitated in front of three heterogeneous servers. Sensitivity analysis has been carried out to study the effect of variation of different parameters on the system performance.

The progress of the technology in the recent decades has caused the video transmission by communication Channels to meet high demands. Therefore, many methods have been proposed to improve the quality of the video under Channel errors. The aim of this paper is to increase the Peak Signal to the Noise Ratio (PSNR) for video reconstructed by the receiver. This is achieved by increasing Channel encoder rate but in constant transmission rate. In the proposed method the video frames’ parts containing more energy are coded by the local Channel coding inside the source encoder. Then, the resulted data is embedded in the low power frames’ parts. The proposed method is able to increase the Channel coding rates without increasing the amount of the information for any frame. This method provides more robustness for video frames against Channel errors. The proposed method is tested for different source coding rates and several Signals to Noise Ratio (SNRs) for Channel and the obtained results are compared with a new method.

Orthogonal frequency division multiplexing (OFDM) is an effective technique for high bit rate applications in multipath Channels. Many researches have been carried out to develop and enhance OFDM efficiency. Because of the special structure of OFDM, the Channel coding is very important. In this paper, Channel coding in OFDM, the efficiency of various codes such as convolutional code, turbo code and their concatenated components with Reed-Solomon code are studied. The techniques of improving the effectiveness of Channel coding with soft decoding and the use of Channel state information are presented with simulation results. It can be seen that in a high signal to noise ratio, the coding gain of concatenated codes is more than the pure codes. The coding scheme can be chosen according to the complexity, suitable delay, and desired oding gain for the system.

In this paper, the secrecy problem in the state dependent causal cognitive interference Channel is studied. The Channel state is non-causally known at the cognitive encoder. The message of the cognitive encoder must be kept secret from the primary receiver. We use a coding scheme which is a combination of compress-and-forward strategy with Marton coding, Gel’ fand-Pinsker coding and Wyner’ s wiretap coding at the cognitive encoder. We use rate splitting for messages at both transmitters. Furthermore, the cognitive user compresses its Channel observation using Wyner-Ziv coding and splits the index of its compressed signal. By using this scheme we derive an achievable secrecy rate region for this Channel and extend the results to the Gaussian case and provide some numerical results.