Single Perceptron Model for Smart Beam forming in Array Antennas

In this paper, a single neuron neural network beamformer is proposed. A perceptron model is designed to optimize the complex weights of a dipole array antenna to steer the beam to desired directions. The objective is to reduce the complexity by using a single neuron neural network and utilize it for adaptive beamforming in array antennas. The selection of nonlinear activation function plays the pivotal role in optimization depends on whether the weights are real or complex. We have appropriately proposed two types of activation functions for respective real and complex weight values.   The optimized radiation patterns obtained from the single neuron neural network are compared with the respective optimized radiation patterns from the traditional Least Mean Square (LMS) method. Matlab is used to optimize the weights in neural network and LMS method as well as display the radiation patterns

Socio-Economic Profiling of Tribal Dairy Farmers in Northern Hills Zone of Chhattisgarh

Chhattisgarh is traditionally known as the Rice Bowl of Central India. Chhattisgarh state has one of highest shares of Scheduled Tribe (ST) population within a state, accounting for about 10 per cent of the STs in India. Scheduled Castes and STs together constitute more than 50 per cent of the state’s population. Agriculture is counted as the chief economic occupation of the state. About 80% of the population of the state is rural and the main livelihood of the villagers is agriculture and agriculture-based small industry. This exploratory study was conducted in the tribal populated districts of Chhattisgarh state. In this paper, socio-economic profile of tribal farmers are discussed in detail. About 65.33 percent of the tribal farmers were between 36 and 50 years of age group, more than one fourth (34.67%) of the farmers were educated up to primary school level, less than half  (39.00%) of the respondents had subsistence dairy farming + Minor forest products collection + labour as their sole occupations, nearly half (43.67%) of the respondents were marginal farmers, more than half (62.00 %) of the farmers were found with medium level of farming experience, about half (49.00 %) of the respondents were at the income range of Rs. 25,001 to Rs. 75,000, about half (44.67 %) of the respondents falling under the category of medium herd size followed by 35.67 percent in small and 19.66 percent in large herd size, more than half (56.33%) of the tribal dairy farmers falling under the category of subsistence level of dairy production system

A single beam smart antenna for wireless communication in a highly reflective and narrow environment

Multipath reflections are prevalent in underground mine wireless communication systems and are less constructive when an omnidirectional antenna is used. This phenomenon can be significantly controlled by eliminating the source of all multipaths with a single beam. The single beam must be rotatable towards the desired user to be of any use. The single directed beam will avoid generating multipath reflections and efficiently consume the valuable stored energy. In this paper we present an analysis of an array antenna using dipoles that forms a single beam without the need for reflectors or any complex arrangement of the array elements. It can be shown that dipole elements placed in a straight line are not effective in minimizing energy consumption and a minimum of three elements are sufficient for forming a single directed beam that is electronically rotatable to all directions. We have compared three, four and six elements for the accuracy. It is also shown that the elements of the array antenna should b placed on the circumference of a circle to avoid re-computation of weights to rotate the beam on to any desired direction, thus significantly reducing the computational burden of the single beam, steerable smart antenna

Accuracy of Perceptron based beamforming for embedded smart and MIMO antennas

Array antennas have a nonlinear, complex relationship between the antenna beams generated and the array input functions that generate the steerable beams. In this paper we demonstrate the use of a simple, computationally less intensive Perceptron Neural Network with non-linear sigmoid activation function to do the synthesis of the desired antenna beam. The single neuron is used, where its optimized weights will yield the beam shape required. This paper presents a successfully implemented Perceptron and discusses the error between the desired and Perceptron generated beams The successful beam control gives high accuracy in the maximum radiation direction of the desired beam, as well as optimization in the direction of null points. Moreover, a comparison between the array antenna beams obtained using the Perceptron Single Neuron Weight Optimization method (SNWOM) and the optimized beams obtained using the Least Mean Square (LMS) method, further demonstrates the reliability and accuracy of the Perceptron based beamformer. The tests were performed for two different desired antenna beams: one braod side beam and the other with the antenna radiating in four different desired directions. The Perceptron based antenna may be embedded in the Arduino microcontroller used. It is also shown why it is not possible to get a single beam, linear array antenna with the Perceptron based array reported herein

Polygonal Dipole Placements for Efficient, Rotatable, Single Beam Smart Antennas in 5G Aerospace and Ground Wireless Systems

In telecommunication systems and radars, the common practice in using array antennas is to place a reflector behind the array so as to reflect the backward signal also in the forward direction. Moreover, in the 5G wireless systems, smart antennas, especially those with a single beam, are expected to play a critical role in its successful launching in 2020. We show in this paper that a linear array antenna necessarily ends up with symmetrical beamforming on both sides of the array axis. Thus, single direction (forward direction) beamforming cannot be achieved by placing the electromagnetic radiators (e.g. dipole elements) in a straight line. We propose that in situations where a smart array structure demands single rotatable beams, that single rotatable beamforming can be achieved by changing the geometrical shape of the array. However, the computational intensity involved in finding optimized weight coefficients for beamforming over the entire 360o space turns into the major challenge. In order to minimize the computational repetition of optimizing weights for every direction, a regular polygon array antenna is proposed. We show that an array antenna placed in a regular polygon yields a smart antenna with a highly effective and computationally fast, reduced memory and electronically rotatable single beam

A Review of a Single Neuron Weight Optimization Model for Adaptive Beam Forming

In this paper, we review our recent, reported work on using artificial intelligence based software technique to control electronic sensor or wireless communication equipment in narrow and diverging paths such as in underground tunnels and at traffic junctions. In order to make the systems fast as well as needing minimal computational calculations and memory – thus to extend the battery life and minimize cost – we used the single layer Perceptron to successfully accomplish the formation of beams which may be changed according to the nature of the junctions and diverging paths the mobile or stationary system is to handle. Moreover, the beams that survey the scenario around (e.g. in case of guiding a driverless vehicle) or communicating along tunnels (e.g. underground mines) need to be kept narrow and focused to avoid reflections from buildings or rough surfaced walls which will tend to significantly degrade the reliability and accuracy of the sensor or communicator. These requirements were successfully achieved by the artificial intelligence system we developed and tested on software, awaiting prototype development in the near future

Measurement of the total cross section and ρ -parameter from elastic scattering in pp collisions at √s=13 TeV with the ATLAS detector

In a special run of the LHC with β⋆=2.5 km, proton–proton elastic-scattering events were recorded at s√=13 TeV with an integrated luminosity of 340 μb−1 using the ALFA subdetector of ATLAS in 2016. The elastic cross section was measured differentially in the Mandelstam t variable in the range from −t=2.5⋅10−4 GeV2 to −t=0.46 GeV2 using 6.9 million elastic-scattering candidates. This paper presents measurements of the total cross section σtot, parameters of the nuclear slope, and the ρ-parameter defined as the ratio of the real part to the imaginary part of the elastic-scattering amplitude in the limit t→0. These parameters are determined from a fit to the differential elastic cross section using the optical theorem and different parameterizations of the t-dependence. The results for σtot and ρ are σtot(pp→X)=104.7±1.1 mb ,ρ=0.098±0.011. The uncertainty in σtot is dominated by the luminosity measurement, and in ρ by imperfect knowledge of the detector alignment and by modelling of the nuclear amplitude.publishedVersio