MULTIPLEXER Circuit is a data selector. It is a device that selects between several analog or digital input signals and forwards the selected input to a single output line.
In this you learn about the topic multiplexer and De-multiplexer in a very easy method.
You learn types of Multiplexer, Types of De-multiplexer,
Relation between Multiplexer (MUX) and De-Multiplexer (Dmux).
Difference between MUX and DMUX
A multiplexer is a device that selects one of several analog or digital input signals and forwards the selected input into a single line. It has multiple data inputs, a single output, and select lines that determine which input is directed to the output. A demultiplexer performs the opposite function, taking a single input and distributing it to one of multiple outputs based on the select lines. Multiplexers and demultiplexers come in various configurations depending on the number of inputs and outputs, such as 2:1, 4:1, 16:1 or 32:1. They are basic building blocks used in digital systems and communication networks to efficiently route signals.
The document discusses multiplexers and demultiplexers. A multiplexer is a combinational logic circuit that selects one of several input lines and outputs the selected signal on a single line, controlled by a selection input. It has multiple data inputs, selection inputs, and a single output. A demultiplexer is the reverse, with one input and multiple outputs, using a selection input to direct the input signal to one of the output lines. The document outlines multiplexer and demultiplexer symbols, diagrams, truth tables, and applications in communication systems and computer memory.
The document discusses multiplexers and demultiplexers. It defines a multiplexer as a combinational circuit that selects one digital input from several sources and transmits it on a single output line. A demultiplexer is the reverse, taking a single input and transmitting it on one of several output lines. Applications of multiplexers and demultiplexers include increasing efficiency in communication systems by transmitting different data types over a single line, and reducing wiring in computer memory systems.
Bit Error Rate Performance of MIMO Spatial Multiplexing with MPSK Modulation ...ijsrd.com
Wireless communication is one of the most effective areas of technology development of our time. Wireless communications today covers a very wide array of applications. In this, we study the performance of general MIMO system, the general V-BLAST architecture with MPSK Modulation in Rayleigh fading channels. Based on bit error rate, we show the performance of the 2x2 schemes with MPSK Modulation in noisy environment. We also show the bit error rate performance of 2x2, 3x3, 4x4 systems with BPSK modulation. We see that the bit error rate performance of 2x2 systems with QPSK modulation gives us the best performance among other schemes analysed here.
Multiplexer & Demultiplexer by Dr. Arvind Nautiyal.pptAswathAwin
This document provides an overview of multiplexers and de-multiplexers. It defines a multiplexer as a digital logic circuit that selects one input from several sources and transmits it to a single output line. A de-multiplexer is described as performing the reverse operation of a multiplexer by taking a single input and transmitting it to one of several output lines. Applications of multiplexers and de-multiplexers in communication systems and computer memory are discussed.
In this you learn about the topic multiplexer and De-multiplexer in a very easy method.
You learn types of Multiplexer, Types of De-multiplexer,
Relation between Multiplexer (MUX) and De-Multiplexer (Dmux).
Difference between MUX and DMUX
A multiplexer is a device that selects one of several analog or digital input signals and forwards the selected input into a single line. It has multiple data inputs, a single output, and select lines that determine which input is directed to the output. A demultiplexer performs the opposite function, taking a single input and distributing it to one of multiple outputs based on the select lines. Multiplexers and demultiplexers come in various configurations depending on the number of inputs and outputs, such as 2:1, 4:1, 16:1 or 32:1. They are basic building blocks used in digital systems and communication networks to efficiently route signals.
The document discusses multiplexers and demultiplexers. A multiplexer is a combinational logic circuit that selects one of several input lines and outputs the selected signal on a single line, controlled by a selection input. It has multiple data inputs, selection inputs, and a single output. A demultiplexer is the reverse, with one input and multiple outputs, using a selection input to direct the input signal to one of the output lines. The document outlines multiplexer and demultiplexer symbols, diagrams, truth tables, and applications in communication systems and computer memory.
The document discusses multiplexers and demultiplexers. It defines a multiplexer as a combinational circuit that selects one digital input from several sources and transmits it on a single output line. A demultiplexer is the reverse, taking a single input and transmitting it on one of several output lines. Applications of multiplexers and demultiplexers include increasing efficiency in communication systems by transmitting different data types over a single line, and reducing wiring in computer memory systems.
Bit Error Rate Performance of MIMO Spatial Multiplexing with MPSK Modulation ...ijsrd.com
Wireless communication is one of the most effective areas of technology development of our time. Wireless communications today covers a very wide array of applications. In this, we study the performance of general MIMO system, the general V-BLAST architecture with MPSK Modulation in Rayleigh fading channels. Based on bit error rate, we show the performance of the 2x2 schemes with MPSK Modulation in noisy environment. We also show the bit error rate performance of 2x2, 3x3, 4x4 systems with BPSK modulation. We see that the bit error rate performance of 2x2 systems with QPSK modulation gives us the best performance among other schemes analysed here.
Multiplexer & Demultiplexer by Dr. Arvind Nautiyal.pptAswathAwin
This document provides an overview of multiplexers and de-multiplexers. It defines a multiplexer as a digital logic circuit that selects one input from several sources and transmits it to a single output line. A de-multiplexer is described as performing the reverse operation of a multiplexer by taking a single input and transmitting it to one of several output lines. Applications of multiplexers and de-multiplexers in communication systems and computer memory are discussed.
This document provides an overview of multiplexers and de-multiplexers. It defines a multiplexer as a digital logic circuit that selects one input from several sources and transmits it to a single output line. A de-multiplexer is described as performing the reverse operation of a multiplexer by taking a single input and transmitting it to one of several output lines. Applications of multiplexers and de-multiplexers in communication systems and computer memory are discussed.
Performance Analysis of Various Symbol Detection Techniques in Wireless MIMO ...IOSR Journals
Wireless communication is one of the most effective areas of technology development of our time.
Wireless communications today covers a very wide array of applications. In this paper, we study the
performance of general MIMO system, the performance of Zero Forcing (ZF), Linear Least Square Estimator
(LLSE), V-BLAST/ZF, V-BLAST/LLSE of 4x4, 4x6 & 4x8 with 4-QAM & 16-QAM modulation in i i d Rayleigh
fading channel. We seen that SER performance of 4x8 antennas and 4-QAM modulation scheme outperforms
others. Result shows that for higher modulation schemes SER performance degrades as well as SER
performance increases for higher no of receiver antennas
Performance Analysis of Various Symbol Detection Techniques in Wireless MIMO ...IOSR Journals
Abstract : Wireless communication is one of the most effective areas of technology development of our time. Wireless communications today covers a very wide array of applications. In this paper, we study the performance of general MIMO system, the performance of Zero Forcing (ZF), Linear Least Square Estimator (LLSE), V-BLAST/ZF, V-BLAST/LLSE of 4x4, 4x6 & 4x8 with 4-QAM & 16-QAM modulation in i i d Rayleigh fading channel. We seen that SER performance of 4x8 antennas and 4-QAM modulation scheme outperforms others. Result shows that for higher modulation schemes SER performance degrades as well as SER performance increases for higher no of receiver antennas. Keywords - Multi Input Multi Output, Zero-forcing receiver, Linear Least Square Estimation, V-BLAST.
Performance Analysis of Various Symbol Detection Techniques in Wireless MIMO ...IOSR Journals
Abstract : Wireless communication is one of the most effective areas of technology development of our time. Wireless communications today covers a very wide array of applications. In this paper, we study the performance of general MIMO system, the performance of Zero Forcing (ZF), Linear Least Square Estimator (LLSE), V-BLAST/ZF, V-BLAST/LLSE of 4x4, 4x6 & 4x8 with 4-QAM & 16-QAM modulation in i i d Rayleigh fading channel. We seen that SER performance of 4x8 antennas and 4-QAM modulation scheme outperforms others. Result shows that for higher modulation schemes SER performance degrades as well as SER performance increases for higher no of receiver antennas. Keywords - Multi Input Multi Output, Zero-forcing receiver, Linear Least Square Estimation, V-BLAST.
This document summarizes a research paper that proposes and analyzes a beam selection algorithm called Interference Aware - Maximization of SINR (IA-MSS) selection for 5G millimeter-wave MIMO systems. The algorithm aims to maximize signal-to-interference ratio (SINR) by first classifying users into interference users and non-interference users based on their strongest beams, and then selecting beams to minimize multi-user interference while achieving high SINR. Analysis shows the IA-MSS algorithm achieves higher power efficiency than alternatives by exploiting sparse properties of beamspace channels in mmWave massive MIMO.
IN THIS SLIDE WE HAVE COVERED THE TOPIC OF DIGITAL ELECTRONIS MULTIPLEXER AND DE MULTIPLEXER TOPIC OF COMBINATIONAL CIRCUIT
THANKS FOR READING MY ANIMATION
Intersymbol interference caused by multipath in band limited frequency selective time dispersive channels distorts the transmitted signal, causing bit error at receiver. ISI is the major obstacle to high speed data transmission over wireless channels. Channel estimation is a technique used to combat the intersymbol interference. The objective of this paper is to improve channel estimation accuracy in MIMO-OFDM system by using modified variable step size leaky Least Mean Square (MVSSLLMS) algorithm proposed for MIMO OFDM System. So we are going to analyze Bit Error Rate for different signal to noise ratio, also compare the proposed scheme with standard LMS channel estimation method.
Multiuser MIMO Gaussian Channels: Capacity Region and DualityShristi Pradhan
In this paper, I present the MIMO channel for single user case, discuss the decomposition of MIMO into parallel independent channels, and estimate the MIMO channel capacity. Then, I discuss on computation of capacity region for multiuser MIMO broadcast and multiple access channel and plot capacity regions for two users case. I conclude by showing the duality relationship between the multiple access and broadcast channel and show its significance for numerical standpoint.
At this present scenario, the demand of the system capacity is very high in wireless network. MIMO
technology is used from the last decade to provide this requirement for wireless network antenna
technology. MIMO channels are mostly used for advanced antenna array technology. But it is most
important to control the error rate with enhanced system capacity in MIMO for present-day progressive
wireless communication. This paper explores the frame error rate with respect to different path gain of
MIMO channel. This work has been done in different fading scenario and produces a comparative analysis
of MIMO on the basis of those fading models in various conditions. Here, it is to be considered that
modulation technique as QPSK to observe these comparative evaluations for different Doppler frequencies.
From the comparative analysis, minimum amount of frame error rate is viewed for Rician distribution at
LOS path Doppler shift of 0 Hz. At last, this work is concluded with a comparative bit error rate study on
the basis of singular parameters at different SNR levels to produce the system performance for uncoded
QPSK modulation.
MIMO Channel Estimation Using the LS and MMSE AlgorithmIOSRJECE
Wireless Communication Technology has developed over the past few yearsfor other objectives.The Multiple InputMultiple Output (MIMO) is one of techniques that is used to enhancethe data rates, in which multiple antennas are employed both the transmitter and receiver. Multiple signals are transmitted from different antennas at the transmitter using the same frequency and separated space. Various channel estimation techniques are employed in order to judge the physical effects of the medium present. In this paper, we analyze and implementvarious estimation techniques for MIMO Systems such as Least Squares (LS), Minimum Mean Square Error (MMSE),these techniques are therefore compared to effectively estimate the channel in MIMO System. The results demonstrate that SNR required to support different values of bit error rate varies depending on different low correlation between the transmitting and the receiving antennas .In addition, it is illustrated that when the number of transmitter and receiver antennas increases, the performance of TBCE schemes significantly improves. The Same behavior isalso observed for MIMO system. Performance of both MMSE and LSestimation are the same for allkinds of modulation at small value of SNR but the more we increase the SNR value the more performance gap goes on increasing.
BER Performance of MU-MIMO System using Dirty Paper CodingIJEEE
In this paper Dirty Paper Coding for communication system is implemented. MIMO application that involves devices such as cell phones, pocket PCs require closely spaced antenna, which suffers from mutual coupling among antennas and high spatial correlation for signals. DPC is used for compensating the degradation due to correlation and mutual coupling.
This document discusses a vector precoding scheme for multi-user MIMO systems. It proposes using vector precoding to circumvent the channel inversion required for zero forcing precoding. The scheme develops a joint transmitter-receiver design where the transmitter precoder lies in the null space of other users' channels to eliminate multi-user interference. Simulation results show the proposed approach improves bit error rate performance by an order of magnitude compared to zero forcing, and increases MIMO broadcast channel capacity with lower complexity than inversion-based techniques.
Hardware efficient singular value decomposition in mimo ofdm systemIAEME Publication
This document describes a hardware efficient method for performing singular value decomposition (SVD) in MIMO-OFDM systems. The proposed method uses an adaptive hardware design to compute the SVD of channel characteristic matrices up to size 4x4. It utilizes features of FPGAs like pipelining to speed up operations and reduce resource usage. The method first extends the channel matrix with zero padding. It then uses techniques like deflation, updating, and partial updating to sequentially estimate the singular values and vectors. For non-square matrices, remaining values are obtained via Gram-Schmidt orthogonalization. Simulation results show the proposed method reduces FPGA resource utilization compared to previous methods, lowering overall implementation costs.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
Peak to-average power ratio reduction of ofdm siganlseSAT Journals
Abstract Orthogonal frequency division multiplexing (OFDM) is a form of multicarrier modulation technique with high spectral efficiency and immunity to interference. Despite of many advantages the main disadvantage of OFDM is that the time domain of OFDM signal which is a sum of subcarrier sinusoids leads to high Peak-to-Average power ratio (PAPR). A simple technique used to reduce the PAPR of OFDM signals is to clip the signal to a maximum allowed value, at the cost of bit error rate(BER) degradation and out-of-band radiation. The other method is Selective mapping method(SLM) technique which is a probabilistic technique for PAPR reduction with aim of reducing the occurrence of peaks in a signal. In this project partial transmit (PTS) scheme along with the threshold technique has been simulated using Matlab and the simulation results shows that the technique performs better. To compare the results SLM and clipping methods are also simulated. Index Terms –Orthogonal Frequency Division Multiplexing (OFDM), Peak-to-Average power ratio (PAPR), Inverse Discrete Fourier Transform (IDFT), Inverse Fast Fourier Transform (IFFT), Partial Transmit Scheme (PTS), Selective Mapping Method (SLM) and Bit Error Rate (BER) degradation.
Computationally Efficient Multi-Antenna Techniques for Multi-User Two-Way Wire...IJECEIAES
In this work, we are interested in implementing, developing and evaluating multi-antenna techniques used for multi-user two-way wireless relay networks that provide a good tradeoff between the computational complexity and performance in terms of symbol error rate and achievable data rate. In particular, a variety of newly multi-antenna techniques is proposed and studied. Some techniques based on orthogonal projection enjoy low computational complexity. However, the performance penalty associated with them is high. Other techniques based on maximum likelihood strategy enjoy high performance, however, they suffer from very high computational complexity. The Other techniques based on randomization strategy provide a good trade-off between the computational complexity and performance where they enjoy low computational complexity with almost the same performance as compared to the techniques based on maximum likelihood strategy.
The document discusses multiplexers and demultiplexers. A multiplexer takes multiple input signals and selects one to output, while a demultiplexer takes a single input signal and distributes it to multiple outputs. The key differences are that multiplexers perform a parallel-to-serial conversion by selecting one of several inputs, while demultiplexers perform a serial-to-parallel conversion by distributing a single input to multiple outputs. Both are used in communication systems, with multiplexers at the transmitter end and demultiplexers at the receiver end.
MIMO system (potential candidate for 4G system)Virak Sou
This document provides an overview of MIMO (multiple-input multiple-output) systems in wireless communications. It discusses how MIMO can provide various performance improvements, including array gain through signal combining, diversity gain to combat fading, and multiplexing gain to increase spectral efficiency. It also covers MIMO channel capacity calculations for different channel models, as well as techniques for maximizing diversity or throughput such as space-time coding and spatial multiplexing. The key advantages of MIMO for future wireless systems are higher data rates, quality of service, coverage, and spectral efficiency.
The document provides an overview of MIMO (multiple-input multiple-output) systems in wireless communications. It discusses how MIMO can provide array gain, diversity gain, and multiplexing gain to improve spectral efficiency, coverage, and quality of service. It also describes how MIMO reduces co-channel interference. The document covers MIMO channel models and capacity results for different scenarios. It concludes by discussing how MIMO can be used to maximize diversity or throughput through different transmission techniques.
KuberTENes Birthday Bash Guadalajara - K8sGPT first impressionsVictor Morales
K8sGPT is a tool that analyzes and diagnoses Kubernetes clusters. This presentation was used to share the requirements and dependencies to deploy K8sGPT in a local environment.
Comparative analysis between traditional aquaponics and reconstructed aquapon...bijceesjournal
The aquaponic system of planting is a method that does not require soil usage. It is a method that only needs water, fish, lava rocks (a substitute for soil), and plants. Aquaponic systems are sustainable and environmentally friendly. Its use not only helps to plant in small spaces but also helps reduce artificial chemical use and minimizes excess water use, as aquaponics consumes 90% less water than soil-based gardening. The study applied a descriptive and experimental design to assess and compare conventional and reconstructed aquaponic methods for reproducing tomatoes. The researchers created an observation checklist to determine the significant factors of the study. The study aims to determine the significant difference between traditional aquaponics and reconstructed aquaponics systems propagating tomatoes in terms of height, weight, girth, and number of fruits. The reconstructed aquaponics system’s higher growth yield results in a much more nourished crop than the traditional aquaponics system. It is superior in its number of fruits, height, weight, and girth measurement. Moreover, the reconstructed aquaponics system is proven to eliminate all the hindrances present in the traditional aquaponics system, which are overcrowding of fish, algae growth, pest problems, contaminated water, and dead fish.
Más contenido relacionado
Similar a MULTIPLEXER Circuit in Digital system/electronics/logic
This document provides an overview of multiplexers and de-multiplexers. It defines a multiplexer as a digital logic circuit that selects one input from several sources and transmits it to a single output line. A de-multiplexer is described as performing the reverse operation of a multiplexer by taking a single input and transmitting it to one of several output lines. Applications of multiplexers and de-multiplexers in communication systems and computer memory are discussed.
Performance Analysis of Various Symbol Detection Techniques in Wireless MIMO ...IOSR Journals
Wireless communication is one of the most effective areas of technology development of our time.
Wireless communications today covers a very wide array of applications. In this paper, we study the
performance of general MIMO system, the performance of Zero Forcing (ZF), Linear Least Square Estimator
(LLSE), V-BLAST/ZF, V-BLAST/LLSE of 4x4, 4x6 & 4x8 with 4-QAM & 16-QAM modulation in i i d Rayleigh
fading channel. We seen that SER performance of 4x8 antennas and 4-QAM modulation scheme outperforms
others. Result shows that for higher modulation schemes SER performance degrades as well as SER
performance increases for higher no of receiver antennas
Performance Analysis of Various Symbol Detection Techniques in Wireless MIMO ...IOSR Journals
Abstract : Wireless communication is one of the most effective areas of technology development of our time. Wireless communications today covers a very wide array of applications. In this paper, we study the performance of general MIMO system, the performance of Zero Forcing (ZF), Linear Least Square Estimator (LLSE), V-BLAST/ZF, V-BLAST/LLSE of 4x4, 4x6 & 4x8 with 4-QAM & 16-QAM modulation in i i d Rayleigh fading channel. We seen that SER performance of 4x8 antennas and 4-QAM modulation scheme outperforms others. Result shows that for higher modulation schemes SER performance degrades as well as SER performance increases for higher no of receiver antennas. Keywords - Multi Input Multi Output, Zero-forcing receiver, Linear Least Square Estimation, V-BLAST.
Performance Analysis of Various Symbol Detection Techniques in Wireless MIMO ...IOSR Journals
Abstract : Wireless communication is one of the most effective areas of technology development of our time. Wireless communications today covers a very wide array of applications. In this paper, we study the performance of general MIMO system, the performance of Zero Forcing (ZF), Linear Least Square Estimator (LLSE), V-BLAST/ZF, V-BLAST/LLSE of 4x4, 4x6 & 4x8 with 4-QAM & 16-QAM modulation in i i d Rayleigh fading channel. We seen that SER performance of 4x8 antennas and 4-QAM modulation scheme outperforms others. Result shows that for higher modulation schemes SER performance degrades as well as SER performance increases for higher no of receiver antennas. Keywords - Multi Input Multi Output, Zero-forcing receiver, Linear Least Square Estimation, V-BLAST.
This document summarizes a research paper that proposes and analyzes a beam selection algorithm called Interference Aware - Maximization of SINR (IA-MSS) selection for 5G millimeter-wave MIMO systems. The algorithm aims to maximize signal-to-interference ratio (SINR) by first classifying users into interference users and non-interference users based on their strongest beams, and then selecting beams to minimize multi-user interference while achieving high SINR. Analysis shows the IA-MSS algorithm achieves higher power efficiency than alternatives by exploiting sparse properties of beamspace channels in mmWave massive MIMO.
IN THIS SLIDE WE HAVE COVERED THE TOPIC OF DIGITAL ELECTRONIS MULTIPLEXER AND DE MULTIPLEXER TOPIC OF COMBINATIONAL CIRCUIT
THANKS FOR READING MY ANIMATION
Intersymbol interference caused by multipath in band limited frequency selective time dispersive channels distorts the transmitted signal, causing bit error at receiver. ISI is the major obstacle to high speed data transmission over wireless channels. Channel estimation is a technique used to combat the intersymbol interference. The objective of this paper is to improve channel estimation accuracy in MIMO-OFDM system by using modified variable step size leaky Least Mean Square (MVSSLLMS) algorithm proposed for MIMO OFDM System. So we are going to analyze Bit Error Rate for different signal to noise ratio, also compare the proposed scheme with standard LMS channel estimation method.
Multiuser MIMO Gaussian Channels: Capacity Region and DualityShristi Pradhan
In this paper, I present the MIMO channel for single user case, discuss the decomposition of MIMO into parallel independent channels, and estimate the MIMO channel capacity. Then, I discuss on computation of capacity region for multiuser MIMO broadcast and multiple access channel and plot capacity regions for two users case. I conclude by showing the duality relationship between the multiple access and broadcast channel and show its significance for numerical standpoint.
At this present scenario, the demand of the system capacity is very high in wireless network. MIMO
technology is used from the last decade to provide this requirement for wireless network antenna
technology. MIMO channels are mostly used for advanced antenna array technology. But it is most
important to control the error rate with enhanced system capacity in MIMO for present-day progressive
wireless communication. This paper explores the frame error rate with respect to different path gain of
MIMO channel. This work has been done in different fading scenario and produces a comparative analysis
of MIMO on the basis of those fading models in various conditions. Here, it is to be considered that
modulation technique as QPSK to observe these comparative evaluations for different Doppler frequencies.
From the comparative analysis, minimum amount of frame error rate is viewed for Rician distribution at
LOS path Doppler shift of 0 Hz. At last, this work is concluded with a comparative bit error rate study on
the basis of singular parameters at different SNR levels to produce the system performance for uncoded
QPSK modulation.
MIMO Channel Estimation Using the LS and MMSE AlgorithmIOSRJECE
Wireless Communication Technology has developed over the past few yearsfor other objectives.The Multiple InputMultiple Output (MIMO) is one of techniques that is used to enhancethe data rates, in which multiple antennas are employed both the transmitter and receiver. Multiple signals are transmitted from different antennas at the transmitter using the same frequency and separated space. Various channel estimation techniques are employed in order to judge the physical effects of the medium present. In this paper, we analyze and implementvarious estimation techniques for MIMO Systems such as Least Squares (LS), Minimum Mean Square Error (MMSE),these techniques are therefore compared to effectively estimate the channel in MIMO System. The results demonstrate that SNR required to support different values of bit error rate varies depending on different low correlation between the transmitting and the receiving antennas .In addition, it is illustrated that when the number of transmitter and receiver antennas increases, the performance of TBCE schemes significantly improves. The Same behavior isalso observed for MIMO system. Performance of both MMSE and LSestimation are the same for allkinds of modulation at small value of SNR but the more we increase the SNR value the more performance gap goes on increasing.
BER Performance of MU-MIMO System using Dirty Paper CodingIJEEE
In this paper Dirty Paper Coding for communication system is implemented. MIMO application that involves devices such as cell phones, pocket PCs require closely spaced antenna, which suffers from mutual coupling among antennas and high spatial correlation for signals. DPC is used for compensating the degradation due to correlation and mutual coupling.
This document discusses a vector precoding scheme for multi-user MIMO systems. It proposes using vector precoding to circumvent the channel inversion required for zero forcing precoding. The scheme develops a joint transmitter-receiver design where the transmitter precoder lies in the null space of other users' channels to eliminate multi-user interference. Simulation results show the proposed approach improves bit error rate performance by an order of magnitude compared to zero forcing, and increases MIMO broadcast channel capacity with lower complexity than inversion-based techniques.
Hardware efficient singular value decomposition in mimo ofdm systemIAEME Publication
This document describes a hardware efficient method for performing singular value decomposition (SVD) in MIMO-OFDM systems. The proposed method uses an adaptive hardware design to compute the SVD of channel characteristic matrices up to size 4x4. It utilizes features of FPGAs like pipelining to speed up operations and reduce resource usage. The method first extends the channel matrix with zero padding. It then uses techniques like deflation, updating, and partial updating to sequentially estimate the singular values and vectors. For non-square matrices, remaining values are obtained via Gram-Schmidt orthogonalization. Simulation results show the proposed method reduces FPGA resource utilization compared to previous methods, lowering overall implementation costs.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
Peak to-average power ratio reduction of ofdm siganlseSAT Journals
Abstract Orthogonal frequency division multiplexing (OFDM) is a form of multicarrier modulation technique with high spectral efficiency and immunity to interference. Despite of many advantages the main disadvantage of OFDM is that the time domain of OFDM signal which is a sum of subcarrier sinusoids leads to high Peak-to-Average power ratio (PAPR). A simple technique used to reduce the PAPR of OFDM signals is to clip the signal to a maximum allowed value, at the cost of bit error rate(BER) degradation and out-of-band radiation. The other method is Selective mapping method(SLM) technique which is a probabilistic technique for PAPR reduction with aim of reducing the occurrence of peaks in a signal. In this project partial transmit (PTS) scheme along with the threshold technique has been simulated using Matlab and the simulation results shows that the technique performs better. To compare the results SLM and clipping methods are also simulated. Index Terms –Orthogonal Frequency Division Multiplexing (OFDM), Peak-to-Average power ratio (PAPR), Inverse Discrete Fourier Transform (IDFT), Inverse Fast Fourier Transform (IFFT), Partial Transmit Scheme (PTS), Selective Mapping Method (SLM) and Bit Error Rate (BER) degradation.
Computationally Efficient Multi-Antenna Techniques for Multi-User Two-Way Wire...IJECEIAES
In this work, we are interested in implementing, developing and evaluating multi-antenna techniques used for multi-user two-way wireless relay networks that provide a good tradeoff between the computational complexity and performance in terms of symbol error rate and achievable data rate. In particular, a variety of newly multi-antenna techniques is proposed and studied. Some techniques based on orthogonal projection enjoy low computational complexity. However, the performance penalty associated with them is high. Other techniques based on maximum likelihood strategy enjoy high performance, however, they suffer from very high computational complexity. The Other techniques based on randomization strategy provide a good trade-off between the computational complexity and performance where they enjoy low computational complexity with almost the same performance as compared to the techniques based on maximum likelihood strategy.
The document discusses multiplexers and demultiplexers. A multiplexer takes multiple input signals and selects one to output, while a demultiplexer takes a single input signal and distributes it to multiple outputs. The key differences are that multiplexers perform a parallel-to-serial conversion by selecting one of several inputs, while demultiplexers perform a serial-to-parallel conversion by distributing a single input to multiple outputs. Both are used in communication systems, with multiplexers at the transmitter end and demultiplexers at the receiver end.
MIMO system (potential candidate for 4G system)Virak Sou
This document provides an overview of MIMO (multiple-input multiple-output) systems in wireless communications. It discusses how MIMO can provide various performance improvements, including array gain through signal combining, diversity gain to combat fading, and multiplexing gain to increase spectral efficiency. It also covers MIMO channel capacity calculations for different channel models, as well as techniques for maximizing diversity or throughput such as space-time coding and spatial multiplexing. The key advantages of MIMO for future wireless systems are higher data rates, quality of service, coverage, and spectral efficiency.
The document provides an overview of MIMO (multiple-input multiple-output) systems in wireless communications. It discusses how MIMO can provide array gain, diversity gain, and multiplexing gain to improve spectral efficiency, coverage, and quality of service. It also describes how MIMO reduces co-channel interference. The document covers MIMO channel models and capacity results for different scenarios. It concludes by discussing how MIMO can be used to maximize diversity or throughput through different transmission techniques.
Similar a MULTIPLEXER Circuit in Digital system/electronics/logic (20)
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MULTIPLEXER Circuit in Digital system/electronics/logic
1. MULTIPLEXER(MUX)
A P R ES E N TAT I O N A B O U T M U LT I P L E X I N G
Mehedi Hasan
CSE, DIU
(b-74)
2. Index
• Introduction
• A Closer look at Multiplexer
• Implementing minterm function in MUX
• Circuit Diagram
• De-MUX
3. Intro_
Multiplexing
Multiplexing is the process of combining one or more signals and transmitting on a single channel. In analog communication systems, a
communication channel is a scarce quantity, which must be properly used. For cost-effective and efficient use of a channel, the concept of
Multiplexing is very useful as it allows multiple users to share a single channel in a logical way.
The three common types of Multiplexing approaches are:
1. Time
2. Frequency
3. Space
Two of the best examples of Multiplexing Systems used in our day-to-day life are the landline telephone network and the Cable TV.
4. A Closer look at Multiplexer
What is Multiplexer
A Digital Multiplexer is a combinational circuit that select a Binary information from one of many input lines and more than one select line.
The multiplexer or MUX is a digital switch, also called as data selector. The basic idea of multiplexing is shown in figure below in which data
from several sources are routed to the single output line when the enable switch is ON. This is why, multiplexers are also called as ‘many to
one’ combinational circuits.
If there are m selection lines, then the number of possible input lines is 2m. Alternatively, we can say that if the number of input lines is
equal to 2m, then m selection lines are required to select one of n (consider 2m = n) input lines.
This type of multiplexer is referred to as 2n × 1 multiplexer or 2n-to-1 multiplexer. For example, if the number of input lines is 4, then two
select lines are required. Similarly, to select one of 8 input lines, three select lines are required.
5. Implementing min-term function in MUX
Boolean function implementation
Any n-variable logic function can be implemented using a smaller 2n-1-to-1 multiplexer and a single inverter.
D.Q. Implement the function F(X,Y,Z) = S(1,3,5,6) using an 8-to-1 mux.
Connect the input variables X, Y, Z to mux select lines. Mux data input lines 1, 3, 5, 6 that correspond to the function min-terms are
connected to 1. The remaining mux data input lines 0, 2, 4, 7 are connected to 0.
6. Implementing min-term function in MUX
X Y Z F
0 0 0 0
0 0 1 1
0 1 0 0
0 1 1 1
1 0 0 0
1 0 1 1
1 1 0 1
1 1 1 0
In the 8 to 1 multiplexer, there are total eight inputs, i.e., A0, A1, A2, A3, A4,
A5, A6, and A7,
3 selection lines, i.e., X, Y and Z and single output, i.e., F.
On the basis of the combination of inputs that are present at the selection
lines X, Y, and Z, one of these 8 inputs are connected to the output. The
block diagram and the truth table of the 8×1 multiplexer
8. De-Multiplexer
A De-multiplexer is a combinational circuit that has only 1 input line and 2N output lines. Simply, the multiplexer is a single-input and multi-
output combinational circuit. The information is received from the single input lines and directed to the output line. On the basis of the
values of the selection lines, the input will be connected to one of these outputs. De-multiplexer is opposite to the multiplexer.
Unlike encoder and decoder, there are n selection lines and 2n outputs. So, there is a total of 2n possible combinations of inputs. De-
multiplexer is also treated as De-mux.
Block Diagram
9. Implementing min-term function in De-MUX
1×8 De-multiplexer
In 1 to 8 De-multiplexer, there are total of eight outputs, i.e., Y0, Y1, Y2, Y3, Y4, Y5, Y6, and Y7, 3 selection lines, i.e., S0, S1and S2 and single
input, i.e., A. On the basis of the combination of inputs which are present at the selection lines S0, S1 and S2, the input will be connected to
one of these outputs. The block diagram and the truth table of the 1×8 de-multiplexer