ESTIMATION OF THE MESSAGE TRANSMISSION PROBABILITY IN CHANNELS WITH ERRORS PACKETS

Рассмотрена передача сообщений в каналах с пачками ошибок. Реализована модель дискретного канала с формированием как одиночных, так и пачек ошибок с заданной вероятностью. Модель позволяет получить оценки вероятности потери сообщений для различных условий. Представлены результаты моделирования. The paper deals with the transmission of messages over channels with error packets. A model of a discrete channel has been designed with the formation of both single errors and packets of errors with a given probability. The model provides estimates of the message error rate for various conditions. The results of the numerical simulation are presented.

Joint Power and Channel Optimization of Agricultural Wireless Sensor Networks Based on Hybrid Deep Reinforcement Learning

The reduction of maintenance costs in agricultural wireless sensor networks (WSNs) requires reducing energy consumption. At the same time, care should be taken not to affect communication quality and network lifetime. This paper studies a joint optimization algorithm for transmitted power and channel allocation based on deep reinforcement learning. First, an optimization model to measure network reward was established under the constraint of the signal-to-interference plus-noise-ratio (SINR) threshold, which includes continuous power variables and discrete channel variables. Secondly, considering the dynamic changes of agricultural WSNs, the network control is described as a Markov decision process with continuous state and action space. A deep deterministic policy gradient (DDPG) reinforcement learning scheme suitable for mixed variables was designed. This method could obtain a control scheme that maximizes network reward by means of black-box optimization for continuous transmitted power and discrete channel allocation. Experimental results indicated that the studied algorithm has stable convergence. Compared with traditional protocols, it can better control the transmitted power and allocate channels. The joint power and channel optimization provides a reference solution for constructing an energy-balanced network.

The Ribaucour families of discrete R-congruences

While a generic smooth Ribaucour sphere congruence admits exactly two envelopes, a discrete R-congruence gives rise to a 2-parameter family of discrete enveloping surfaces. The main purpose of this paper is to gain geometric insights into this ambiguity. In particular, discrete R-congruences that are enveloped by discrete channel surfaces and discrete Legendre maps with one family of spherical curvature lines are discussed.

Discrete channel surfaces

We present a definition of discrete channel surfaces in Lie sphere geometry, which reflects several properties for smooth channel surfaces. Various sets of data, defined at vertices, on edges or on faces, are associated with a discrete channel surface that may be used to reconstruct the underlying particular discrete Legendre map. As an application we investigate isothermic discrete channel surfaces and prove a discrete version of Vessiot’s Theorem.

Joint Resource Allocation for Frequency-Domain Artificial Noise Assisted Multiuser Wiretap OFDM Channels with Finite-Alphabet Inputs

The security issue on the physical layer is of significant challenge yet of paramount importance for 5G communications. In some previous works, transmit power allocation has already been studied for orthogonal frequency division multiplexing (OFDM) secure communication with Gaussian channel inputs for both a single user and multiple users. Faced with peak transmission power constraints, we adopt discrete channel inputs (e.g., equiprobable Quadrature Phase Shift Keying (QPSK) with symmetry) in a practical communication system, instead of Gaussian channel inputs. Finite-alphabet inputs impose a more significant challenge as compared with conventional Gaussian random inputs for the multiuser wiretap OFDM systems. This paper considers the joint resource allocation in frequency-domain artificial noise (AN) assisted multiuser wiretap OFDM channels with discrete channel inputs. This security problem is formulated as nonconvex sum secrecy rate optimization by jointly optimizing the subcarrier allocation, information-bearing power, and AN-bearing power. To this end, with a suboptimal subcarrier allocation scheme, we propose an efficient iterative algorithm to allocate the power between the information and the AN via the Lagrange duality method. Finally, we carry out some numerical simulations to demonstrate the performance of the proposed algorithm.

Some Combinatorial Logic Examples

The entire point of Shannon's 1948 “A Mathematical Theory of Communication” was to study the theoretical limits on the transmission of information from point A (the source) to point B (the receiver) through an intervening medium (the channel). The information is imagined first to be encoded in some manner before being sent through the channel. Shannon considers two distinct types of channels: the so-called continuous channel that would carry, for example, a continuous signal like the human voice; and the so-called discrete channel that would carry, again for example, a keyboard's output in the form of a digital stream of bits. This chapter focuses on this second case. In a perfect world the digital stream would arrive at the receiver exactly as it was sent, but in the real world the channel is noisy and so, occasionally, a bit will arrive in error.