Reconfigurable Antenna for Future Wireless Communication Systems

Re, E. Del; Morosi, Simone; Marabissi, Dania; Mucchi, Lorenzo; Pierucci, Laura; Ronga, Luca Simone

doi:10.1007/s11277-006-9185-8

Cited by 7 publications

(3 citation statements)

References 138 publications

(124 reference statements)

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“…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].…”

Section: Introductionmentioning

confidence: 99%

“…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.…”

Section: Introductionmentioning

confidence: 99%

“…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].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

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

Pan

2009

Wireless Pers Commun

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Multiple-input-multiple-output (MIMO) technique is often employed to increase capacity in comparing to systems with single antenna. However, the computational complexity in evaluating channel capacity or transmission rate (data rate) grows proportionally to the number of employed antennas at both ends of the wireless link. Recently, the QR decomposition (QRD) based detection schemes have emerged as a low-complexity solution. After conducting QRD on a full channel matrix that results in a triangular matrix, we claim that computational complexity can be simplified by the following ways. First, to simplify channel capacity calculation, we prove that eigenvalues of the full channel matrix multiplication equals eigenvalues of the triangular channel matrix multiplication. Second, to simplify the calculation of the optimal transmission rate constrained constellation, we propose a simplistic multiplication of the resulted simple triangular matrix and a transmitted signal vector. Then, we also propose a modified mutual information calculation (MMIC) to achieve a quite low-complexity via the divided calculation. By using computer simulation and fieldprogrammable gate array (FPGA) implementation, simulation results show that the proposed QRD-based schemes are capable of achieving conventional performance, but at a low-complexity level.

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