I Gede Puja Astawa

Performance of MIMO-OFDM System Based on Channel Estimation for IEEE 802.11n

IEEE 802.11n is considered as the current development of standard communication WLAN IEEE 802.11 providing the increase throughput relatively standard to IEEE802.11a/g. The increase of various transmission channel in the wireless communication makes the antenna receiver work harder as the noise and fading happen in the channel. A certain method is needed to predict the channel description between the transmitter and receiver for standard communication WLAN IEEE802.11n. This research does an estimated channel simulation using minimum mean square error (MMSE) method on the MIMO-OFDM system in scheme antennas 2 × 2 and 2 × 4. The rectangular shaping on the time domain is used as channel model approach. The operation of system is stated into impulse responses sent from Tx transmitter antenna to Rx receiver output from the channel estimated output. The computer simulation program shows that the estimated channel works well on the antenna schemes 2 × 2 and 2 × 4.

Performance of MIMO-OFDM using convolution codes with QAM modulation

Performance of Orthogonal Frequency Division Multiplexing (OFDM) system can be improved by adding channel coding (error correction code) to detect and correct errors that occur during data transmission. One can use the convolution code. This paper present performance of OFDM using Space Time Block Codes (STBC) diversity technique use QAM modulation with code rate ½. The evaluation is done by analyzing the value of Bit Error Rate (BER) vs Energy per Bit to Noise Power Spectral Density Ratio (Eb/No). This scheme is conducted 256 subcarrier which transmits Rayleigh multipath fading channel in OFDM system. To achieve a BER of 10-3 is required 10dB SNR in SISO-OFDM scheme. For 2×2 MIMO-OFDM scheme requires 10 dB to achieve a BER of 10-3. For 4×4 MIMO-OFDM scheme requires 5 dB while adding convolution in a 4x4 MIMO-OFDM can improve performance up to 0 dB to achieve the same BER. This proves the existence of saving power by 3 dB of 4×4 MIMO-OFDM system without coding, power saving 7 dB of 2×2 MIMO-OFDM and significant power savings from SISO-OFDM system.

Skema Lokalisasi Posisi Node Terdistribusi pada Lingkungan Free Space Path Loss

A wireless sensor network consists of interconnected nodes that exchange information and use shared resource in a wireless transmission medium. Sensor nodes are randomly deployed in observation area in static or moving term. During this situation, the position of each sensor nodes is required to be known to monitor the circumstances around the node according to the information collected by sensor. Localization is the process to determine the position of nodes. This process could be done in centralized or distributed manner. In this paper, a distributed localization mechanism is proposed, where the calculation of node position is carried out on the node itself. Trilateration method is employed to calculate the position of node based on estimated distance measured by Received Signal Strength Indicator (RSSI) technique using Zigbee module in Free-Space Path Loss (FSPL) outdoor area. The experiment result shows that, based on log-normal shadowing model, the path loss coefficient for observation area is 2.5443, whereas average estimated position error from three different measured nodes are 23.504 m, 17.369 m, and 17.95 m respectively. Each node needs 2.73 second to undertake localization process completely.

Performance analysis of MIMO-OFDM systems with SIC detection based on single-RF with convolutional code

As the development of wireless communicationstechnology, the requirement to provide high speed data services and wide bandwidth increases. MIMO-OFDM (Multi Input Multi Output — Orthogonal Frequency Division Multiplexing) can provide greater information capacity and provide the quality of high-speed information in real time on a better multipath fading channel. The large number of antenna in MIMOsystemresulted inpowerbeingconsumed increasingly large. The antenna system with Single Radio Frequency energy that can streamline lower cost. The combination of MIMO-OFDM basedsingle RF produces modern technology for the development of telecommunications in thefuture. In this paper, research and analysis on performance of MIMO systems SIC-based detection usingasingle RF using convolutional code. This analysis is done by creating a simulation of MATLAB programs. The modulation technique used is QAM modulation. Channel model that will be used in this simulation is Rayleigh fading with added noise AWGN. The detector used in this system is the SIC (Successive Interference Cancellation). Channel estimation is performed using the MMSE (Minimum Mean Square Error). By having this information channel estimation of channel can be known for the sake of achievement of a high transmission rate and goodquality. The result of this paper is the resulting performance of the system is expressed in the form of the curve of BER as a function of SNR with the amount of different modulation curve and the channel estimations that are displayed with the estimated magnitude and phase curves to change index subcarrier.

Performance Analysis of Video Transmission Using Sequential Distortion Minimization Method for Digital Video Broadcasting Terrestrial

This paper presents about the transmission of Digital Video Broadcasting system with streaming video resolution 640x480 on different IQ rate and modulation. In the video transmission, distortion often occurs, so the received video has bad quality. Key frames selection algorithm is flexibel on a change of video, but on these methods, the temporal information of a video sequence is omitted. To minimize distortion between the original video and received video, we aimed at adding methodology using sequential distortion minimization algorithm. Its aim was to create a new video, better than original video without significant loss of content between the original video and received video, fixed sequentially. The reliability of video transmission was observed based on a constellation diagram, with the best result on IQ rate 2 Mhz and modulation 8 QAM. The best video transmission was also investigated using SEDIM (Sequential Distortion Minimization Method) and without SEDIM. The experimental result showed that the PSNR (Peak Signal to Noise Ratio) average of video transmission using SEDIM was an increase from 19,855 dB to 48,386 dB and SSIM (Structural Similarity) average increase 10,49%. The experimental results and comparison of proposed method obtained a good performance. USRP board was used as RF front-end on 2,2 GHz.

Performance Analysis of CP-Based and CAZAC Training Sequence-Based Synchronization in OFDM System

Orthogonal Frequency Division Multiplexing (OFDM) is a popular wireless data transmission scheme. However, its synchronization is still being a major problem when it is applied in real hardware. Cyclic Prefix (CP) based synchronization is one of the solutions in this problem, but CP has high crest factor. In the other hand, CAZAC sequence is another solution with lower crest factor but the higher complexity and also CAZAC has potential in security and channel estimation implementation. The performance between CP and CAZAC sequence based synchronization in OFDM system is analyzed in this paper. The real hardware, Universal Software Rado Peripheral (USRP), is used to prove the analysis. The CAZAC sequence has 10% performance increased in frequency offset than CP based synchronization.

Performance Comparison of Coded and Uncoded MIMO-OFDM with Linear and Non-Linear Detector

Background/Objectives: Orthogonal Frequency Division Multiplexing (OFDM) is a very popular data transmission technique that can be easily applied in wire line or wireless data communication applications. But this OFDM system has several weaknesses; one of them is the complexity of OFDM system. This complexity problem can lead to the decreasing performance of OFDM when it is applied in real hardware. Methods/Statistical Analysis: In this paper, we investigate the performance of one of the most complex OFDM system, Multiple Input Multiple Output (MIMO) OFDM, with channel code and linear detector, and MIMO-OFDM without channel code and non-linear detector, to find which MIMO-OFDM system has lower complexity and decent performance. We calculate its complexity by analyzing how many mathematical operations needed to implement the system. Findings: The analytical and simulation results indicate that MIMO-OFDM with channel coding and linear detector has lower complexity than MIMO-OFDM with non-linear detector. Although the performance is slightly lower than the system with non-linear detector, the system with channel coding and linear detector is more suitable for hardware implementation. Application/Improvements: For future enhancement, this system needs to be applied in the real hardware system to analyze the performance further

Reduce complexity computation of MIMO decomposition based on single RF using Kalman filter

Multiple Input Multiple Output (MIMO) systems based on single radio frequency (RF) receiver have been shown to achieve high data rates due to the exploitation of spatial diversity with the use of multiple antennas at the transmitters and/or receivers. However, exploiting the full multiplexing gain of the MIMO channel requires a RF front end and analog to digital converters for each antenna to process each data stream at baseband, which implies an increase in hardware size, cost computation, and power consumption with respect to single-input-single-output (SISO) systems. This technique can be great, which we can not get the additional diversity gain using the linear MIMO decomposition method. The resulting performance trends showed a significant increase when compared to MIMO-OFDM schemes using conventional antenna. But the complexity of computational cost is high, especially for the larger antenna size. For that we propose to reduce the complexity of computation cost hence technology of a RF signal processing for MIMO-OFDM can reliable applied. In this research we proposes a technique to reduce complexity of computational cost using Kalman filter as MIMO equalizer. In this technique we perform the reduction of the larger matrix size into lower matrix size. In additional part we use an error correction coding (ECC) technique using convolution code and Viterbi algorithm decoding applied at receiver side. Computer simulation result showed that our proposed scheme give low computation.