In-Vehicle WLAN Radio-Frequency Communication Characterization

Intra-vehicle digital communications: characterization and simulation of the electromagnetic environment

“…The curve in black was obtained with 4 cottonclothed passengers in the vehicle; the curve in grey was obtained with these same 4 passengers, who had donned a metallic vest in aluminum. A stirring ratio of 15 to 18 dB was obtained for frequencies between 1 and 6 GHz; we noted no impact due to the addition of the metallic vest [11]. The measurements also show that, in a frequency bandwidth between 2.4 and 6 GHz and with several passengers, the quality factor Q varied from 100 to 500, depending on, for example, the position and radiation pattern of the antennas or the type of car [11,12].…”

Path-loss measurement system for design of in-vehicle short range communication

“…The propagation mechanism was investigated in the passenger compartment [2,3]. The channel measurements were carried out for a Zigbee-based sensor network and ultra wide band system [4,5].…”

Complexity Reduction by Using QR-Based Scheme in Computing Capacity for Optimal Transmission

“…Multiple-input-multiple-output (MIMO) technique [1][2][3] is often employed to increase capacity in comparing to systems with single antenna [4,5]. In wirless MIMO communications, the design of an optimal transmission is essential in order to meet demands from a large number of simultaneous data transmissions [1][2][3].…”

“…In wirless MIMO communications, the design of an optimal transmission is essential in order to meet demands from a large number of simultaneous data transmissions [1][2][3]. Bertrand et al [6] shows the mutual information constrained constellation to achieve the maxim achievable rate at various signal-to-noise ratio (SNR) conditions in MIMO system.…”

“…However, with full MIMO channel matrix (H) [6][7][8][9][10], the computational complexity in calculating channel capacity or transmission rate (data rate) increases proportionally when the number of antennas and/or modulation orders are higher [6][7][8][9][10]. More specifically, the full MIMO channel matrix multiplication [6] leads to complicated very-large-scale integration (VLSI) [11], field-programmable gate array (FPGA) implementation [12] and real-time design [1][2][3]. To simplify the computational complexity, the QR-decomposition (QRD) scheme [13][14][15] with restraining complexity has been devised to reduce the MIMO channel matrix multiplication due to involving a lot of zeros in a triangular matrix [13][14][15].…”