Shiwani Dogra ¹, Navjot Kaur ¹

Affiliations
1 School of Electronics and Electrical Engineering, Lovely Professional University, Phagwara - 144411, Punjab, IN

Abstract

MIMO gives high data rates and increase spectral efficiency through spatial diversity and multiplexing using STBC (space time block code) technique. STBC improve the reliability of wireless link. The main goal is to maximize the average spectral efficiency (ASE) under the constraints that the A-BER should be lower. In Optimal method, A-BER approach, the objective is to boost the ASE under the requirement that the A-BER ought to be lower. In Sub optimal method, the SNR range appointed to a high request regulation builds, the ASE increments while the BER additionally increments in the same time. Better ASE (Area spectral efficiency) performance than the static MIMO mode switching scheme with adaptive modulation.  In the traditional static mode, the   MIMO mode change depending upon the normal SNR rather than the prompt channel condition.A rate-versatile modulation plan combined with mode exchanging between spatial multiplexing and orthogonal space-time piece coding. Initially discover which regulation level and mode amplify the phantom productivity with a given target bit blunder proportion (BER). In the event that the rates of the two MIMO modes are the same, select one mode that gives lower BER than the other. MIMO technology can be used in non-wireless communications systems. One example is the home networking standard ITU-T G.9963, which defines a power line communications system that uses MIMO techniques to transmit multiple signals over multiple AC wires.

Keywords

MIMO (multiple input multiple output); Assorted qualities (spatial diversity); Spatial multiplexing; Versatile MIMO switching scheme.

Full Text

   

Rahul Singh ¹, Someet Singh ¹, Navjot Kaur ¹

Affiliations
1 Lovely Professonal University, Phagwara – 144411, Punjab, IN

Abstract

Objective: Here we are going to describe the technique to detect vehicle in foggy environment. Vehicle detection in foggy weather is important because poor visibility is the major reason of the accidents and collision of vehicle. LiDAR and cameras are often used for better performance. Method: The image which is received from the camera in foggy condition is totally distorted and blurred and it will not clear up to the desired level so that the vehicle in front is clearly visible to us, so in order to deblur our image and make it clear we will use Adaptive Gaussian Thresholding Technique. In this technique threshold value is the weighted sum of the neighborhood pixel values which will make our image clearer and clean as compared to the original image. In addition with camera we are using low cost LiDAR which consists of a laser and a camera both of these devices are combined to measure accurate distance up to 10 meter. This LiDAR will used to measure the distance from front vehicle and provide warning according to the measured distance. Finding: The coding of this system is completely based on the python which is faster and lightweight as compared to the MATLAB. And our LiDAR is also more accurate and fast as compared to the traditional LiDAR system its major plus point is that it is of low cost. The combination of LiDAR and camera make our system more powerful and efficient.

Keywords

Adaptive Gaussian Thresholding, Computer Vision, LiDAR, Python.

Full Text

   

Manpreet Kaur ¹, Navjot Kaur ¹

Affiliations
1 School of Electronics & Electrical Engineering, Lovely Professional University, Phagwara − 144402, Jalandhar, Punjab, IN

Abstract

Multiple Input Multiple Output (MIMO) low complexity receiver which utilizes the compressive sensing detection for Spatial Modulation in large scale MIMO system in order to reduce the system complexity. In conventional MIMO system; huge amount of antennas is used at both ends to exploit the multipath propagation. This system maximizes the throughput performance and data rates are increased but only at the cost of high hardware complexity and increased power-consumption. Spatial Modulation Matching Pursuit (SMMP) is the proposed enhanced CS technique used for the improvement of detection performance. Hence, this paper reviews recent research findings concerning normalized Compressive Sensing (CS) detection algorithm, used for Spatial Modulation (SM) in massive MIMO, to lowers the signal processing complexity, which in result improves the energy efficiency of system against that of conventional MIMO system.This strategy is achieved by involving additional structures and sparsity in which a single transmitter antenna or a subset of it is turned on at each case to transmit a certain data. The subset of antenna which is turned on for transmission depends on approaching data bits. Therefore, the total increase in the spectral efficiency of the system is given as base-two logarithm of whole antennas at the transmitter. It reduces the signal processing load at base station and doesn’t depend upon any synchronization between transmitters. The Spatial Modulation Matching Pursuit used prevents the Inter Channel Interference (ICI) of the system which in result improves the Bit Error Rate (BER) performance than the typical MIMO system.

Keywords

Compressive Sensing, Energy Efficiency, Large-Scale MIMO, Spatial Modulation.

Full Text

   

Shakti Raj Chopra ¹, Navjot Kaur ¹, Himanshu Monga ¹

Affiliations
1 Department of Electronics and Communication Engineering, Lovely Professional University Phagwara – 144411,Punjab, IN

Abstract

This paper explore the basic approaches used for of space-time coding technique. The emerging field of wireless evaluation such as Multiple Input Multiple Output (MIMO) and Antenna diversity plays an important role in space-time code design. Spatial diversity techniques by the means of multiple transmitting and receiving antennas and the performance of MIMO systems has been discussed for different space-time coding structures such as Alamouti, OSTBC3, OSTBC4 etc. Space-time coding techniques rely on the construction of matrices and the signal is to be transmitted at different period of time from multiple of antennas. These code structures utilises the diversity schemes to improve the bit error rate and thus to achieve higher data rates without bandwidth expansion.

Keywords

BER, Multiple Input Multiple Output (MIMO), OSTBC3, OSTBC4, SNR, Spatial Diversity, STBC, STTC

Full Text