Physical (PHY) Layer Analysis of Data Transmission in MIMO Wireless Networks in Line- of-Sight (LoS) Environments (original) (raw)
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2017
1,2 Student, M.Tech 1st year, Dept. Of Electronics and Communication Engineering, Anjuman College Of Engineering & Technology, Nagpur, Maharashtra, India ---------------------------------------------------------------------***--------------------------------------------------------------------Abstract – Multiple-input multiple-output (MIMO) communication technology has proved itself as a widely used technology nowadays. MIMO can be generally referred to as a communication channel which has multiple numbers of transmitters and receivers of antenna which directly affects the communication’s performance. These days MIMO communication technologies are used in various technologies such as long-term evolution (LTE) and Wi-Fi. In this article, we discuss the different terminologies related to the MIMO communication systems such as its narrowband model characteristics, MIMO channel capacity and decomposition of the channel, various types of its diversity gain based methodologies & also its ...
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Design and Analysis of High-Capacity MIMO System in Line-of-Sight Communication
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The phase of the channel matrix elements has a significant impact on channel capacity in a mobile multiple-input multiple-output (MIMO) communication system, notably in line-of-sight (LoS) communication. In this paper, the general expression for the phase of the channel matrix at maximum channel capacity is determined. Moreover, the optimal antenna configuration of the 2 × 2 and 3 × 3 transceiver antenna array is realized for LoS communication, providing methods for n×n optimal antenna placement, which can be used in short-range LoS communication and non-scattering environment communication, such as coupling train communication and inter-satellite communication. Simulation results show that the 2 × 2 rectangular antenna array is more suitable for the communication of coupling trains, while the 3 × 3 circular arc antenna array is more suitable for virtual coupling trains according to antenna configurations. Moreover, the 2 × 2 antenna rectangular configuration proposed in this paper ...
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Performance Analysis of Mimo Technology in Mobile Wireless Systems
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Analyzing randomly placed multiple antennas for MIMO wireless communication
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We present an analytical approach for determining the signal-to-noise-ratio (SNR) of m multiple antennas in the line-of-sight case. The antennas are placed at random positions within a disc of given diameter d. We characterize the angular signal strength with three sectors: the main beam, the side beams and an area of white Gaussian noise. The SNR and the sector angles depend on d, m, and the wavelength λ. It turns out that for randomized antenna positions the analysis can be reduced to the analysis of a random geometric walk in two dimensions. The angle of the main beam is approximately λ/d with a SNR proportional to √ m. For the side beams the SNR is proportional to sinc(2αd/λ) where α denotes the angle deviating from the target. The range of the side beams is limited to an approximate angle of λ/d √ m. Beyond this angle we observe average white Gaussian noise.
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This paper reviews recently published results on multiple input multiple output (MIMO) channel modeling. Both narrowband and wideband models are considered. We distinguish between two main approaches to MIMO channel modeling, namely, physically based and non-physically based modeling. The non-physical models primarily rely on the statistical characteristics of the MIMO channels obtained from the measured data while the physical models describe the MIMO channel (or its distribution) via some physical parameters. We briefly review different MIMO channel models and discuss their relationships. Some interesting aspects will be described in more detail and we note areas where few results are available.
CRITICAL AND IMPORTANT FACTORS RELATED WITH ENHANCING WIRELESS COMMUNICATION USING MIMO TECHNOLOGY
This research propose analyze, simulate, test, and determine the optimal performance of cited three critical and important factors related with enhancing wireless communication using MIMO technology, for simulations throughout proposed work will employing Rayleigh flat and Additive White Gaussian Noise (AWGN). Orthogonal Frequency Division Multiplexing (OFDM) was the first factor simulated, to evaluate it is performance relating with the direct parameters presents the base bone of OFDM architecture such as OFDM model, channel types, FFT size, constellation and modulations. Secondly a simulation of channel capacity factor was done to assess the performance of capacity relating with SISO, SIMO, MISO, and MIMO. Finally from single antenna to multiantenna techniques was tested, to evaluate Bit Error Rate (BER) performance by using different receive and transmit diversity techniques have been simulated and tested for SIMO and MISO systems. Furthermore, different diversity techniques based on MIMO system have also been simulated and tested. All of these techniques are compared numerically and graphically with the BER performance of SISO system, in addition to their comparison with each other, by using various numbers of antennas. From proposed analysis, simulation, and testing of these three factors and their related parameters many of recommendations are obtained to set parameters of the three factors to build high performance PHY layer with wireless communication using MIMO technique. The implementation proposal was done under Matlab programming language.