Get Advances in Multiuser Detection (Wiley Series in PDF

By Michael L. Honig

ISBN-10: 0471779717

ISBN-13: 9780471779711

A well timed Exploration of Multiuser Detection in instant NetworksDuring the prior decade, the layout and improvement of present and rising instant structures have prompted many vital advances in multiuser detection. This ebook fills a tremendous desire through delivering a accomplished review of an important contemporary advancements that experience happened during this energetic study zone. every one bankruptcy is contributed by way of famous specialists and is intended to function a self-contained remedy of the subject. insurance includes:Linear and selection suggestions methodsIterative multiuser detection and decodingMultiuser detection within the presence of channel impairmentsPerformance research with random signatures and channelsJoint detection tools for MIMO channelsInterference avoidance tools on the transmitterTransmitter precoding equipment for the MIMO downlinkThis booklet is a perfect access aspect for exploring ongoing study in multiuser detection and for studying in regards to the field's current unsolved difficulties and concerns. it's a helpful source for researchers, engineers, and graduate scholars who're enthusiastic about the world of electronic communications.

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Additional info for Advances in Multiuser Detection (Wiley Series in Telecommunications and Signal Processing)

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Although this method clearly must perform better than PC (with respect to MSE), it generally performs worse than the GSC for small D. 4 Comparison All of the preceding methods achieve the MMSE if the filter rank D exceeds the dimension of the signal subspace K. This can be beneficial when K ( N. Although for given D, principal components performs worse than the other eigen-space methods, the projection matrix Sk does not depend on the signature mk. , for the multiple-access channel). , due to channel impairments).

Note that this subspace is equivalent to that spanned by mk and eigen-vectors of the interference-plus-noise covariance matrix Rk ¼ R À mk myk . Consequently, the reduced-rank GSC can perform no worse than the matched filter, and is optimal in the MMSE sense when D exceeds the dimension of the interference subspace. Substantial performance gains, relative to the matched filter, can be achieved with small values of D. 3 Cross-Spectral Method [25] In this method, the columns of Sk are the eigen-vectors of R, which minimize the MSE objective: jk ¼ 1 À syk RÀ1 sk ¼ 1 À D X jsyk vi j2 li i¼1 (1:24) where v1, .

By definition, all other elements of Bk are zero. 62) over Bk gives: Bk,D ¼ (I À MyD RÀ1 MD )À1 MyD RÀ1 mk ¼ À[E E lin ]À1 E lin ]k,D D,D [E (1:64) (1:65) E lin ]D,D is the where [E E lin ]k,D is the kth column of Elin taking only rows in set D and [E matrix formed from only those rows and columns of E lin in D. , elin, m for m [ D). 65). Note that the orthogonality principle implies: E[edfd,k eÃlin,m ] ¼ 0 (1:68) where m [ D. 65) by applying the Matrix Inversion Lemma [32, Sec. 2]. 1 OVERVIEW OF MULTIUSER DETECTION Successive Decision Feedback For the S-DFD, we have for user k: D ¼ {1, .

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Advances in Multiuser Detection (Wiley Series in Telecommunications and Signal Processing) by Michael L. Honig

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