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The 802.11n MIMO-OFDM Standard 191 in .NET Generate Denso QR Bar Code in .NET The 802.11n MIMO-OFDM Standard 191




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The 802.11n MIMO-OFDM Standard 191 generate, create qr code jis x 0510 none for .net projects Codeabar Figure 8.12: Cumulative distribution of measured throughput. Figure 8.13: TCP throughput measured at various distances. 192 The 802.11n MIMO-OFDM Standard 8.11 Conclusions The performa .NET QR Code JIS X 0510 nce of wireless LAN in terms of range and throughput is increased significantly by the use of MIMO-OFDM, which is the basis of the new IEEE 802.11n standard.

Performance results show that net user throughputs over 100 Mbps are achievable with just 2 spatial streams, which is about four times larger than the maximum achievable throughput using IEEE 802.11a/g. For the same throughput, MIMO-OFDM achieves a range increase of about a factor of 3 compared to conventional wireless LAN.

This performance boost makes MIMO-OFDM the ideal successor to the current OFDM-only wireless LAN. Also, it enables new throughput-demanding applications such as wireless video distribution. Seeing the effectiveness and superior capability of MIMO-OFDM in enhancing data rate and extending range, other standards organizations have realized that it can do wonders for other technologies, both fixed, mobile and cellular.

Standard bodies like 3GPP, WiBro, WiMax and the 4G Mobile Forum have started exploring the use of MIMO-OFDM in their respective technology areas, making it the technology of choice for future wireless networks.. 8.12 References [1] R. van N qr bidimensional barcode for .NET ee, G.

Awater, M. Morikura, H. Takanashi, M.

Webster, and K. Halford, New High Rate Wireless LAN Standards, IEEE Communications Magazine, Vol. 37, No.

12, pp. 82-88, Dec. 1999.

[2] G. G. Raleigh and J.

M. Cioffi, Spatio-Temporal Coding for Wireless Communications, Proc. 1996 Global Telecommunications Conf.

, Nov. 1996, pp. 1809-1814.

[3] G. G. Raleigh and V.

K. Jones, Multivariate Modulation and Coding for Wireless Communication, IEEE Journal on Selected Areas in Communications, Vol. 17, No.

5, May 1999, pp. 851-866. [4] R.

van Nee, A. van Zelst, and G. Awater, Maximum Likelihood Decoding in a Space Division Multiplexing System, IEEE VTC 2000, Tokyo, Japan, May 2000.

[5] IEEE 802.11 Working Group, IEEE P802.11n/D2.

0 Draft Amendment to Standard for Information Technology-Telecommunications and information exchange between systems-Local and Metropolitan networks-Specific requirements-Part 11: Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) specifications: Enhancements for Higher Throughput, January 2007. [6] A. Stephens, 802.

11n Functional Requirements, IEEE document 802.11-02/813r12, March 2004. [7] R.

van Nee and R. Prasad, OFDM for Mobile Multimedia Communications, Boston: Artech House, Dec. 1999.

[8] V. Erceg, et al., TGn Channel Models, IEEE document 802.

11-03/940r4, May 2004. [9] J. Chen, et al.

, Reduced-Complexity Decoding of LDPC Codes , IEEE Transactions on Communications, Vol.53, No.8, August 2005, pp.

1288-1299.. 9 MIMO Spatial Processing for 802.11n WLAN Bj rn Bjerke, Irina Medvedev, Visual Studio .NET QR Code JIS X 0510 John Ketchum, Rod Walton, Steven Howard, Mark Wallace and Sanjiv Nandaa 9.1 Introduction.

Tremendous consumer interest in multimedia applications is driving the need for successively higher data rates in wireless networks. The IEEE 802.11n standard for high throughput Wireless Local Area Networks (WLANs) improves significantly upon the data rates experienced by end users of current WLAN systems, e.

g., 802.11a, b, and g.

The soon-to-be ratified 802.11n standard specifies a high data rate multiple-input, multiple-output (MIMO) based physical layer which employs orthogonal frequency division multiplexing (OFDM) and up to four spatial streams [1]. Both high data rate and long-range coverage are achieved by employing spatial signal processing techniques such as spatial spreading and transmit beamforming [2], among others.

802.11n introduces a range of MAC-layer enhancements also, but these are beyond the scope of this chapter. In this chapter, we give an overview of two spatial processing alternatives available to implementers of 802.

11n. We examine spatial spreading and transmit beamforming schemes, as well as possible receiver structures. Comparisons in terms of performance and complexity are also given.

The chapter is organized as follows. Section 9.2 gives a brief overview of MIMO OFDM, as well as the relevant system aspects of the 802.

11n physical layer (PHY). Section 9.3 describes spatial spreading.

Section 9.4 describes eigenvector-based transmit beamforming and schemes for channel sounding and calibration. Section 9.

5 describes receiver structure alternatives for use with the above mentioned techniques. A comparison of the schemes, including simulation results illustrating the performance of the various receivers, is provided in Section 9.6, and a complexity analysis is given in Section 9.

7. Conclusions are drawn in Section 9.8.

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