HIPAA Security Implementation, Version 1.0 by SANS Institute

By SANS Institute

Written for the IT employees in hospitals, this consultant offers step by step path on find out how to follow the necessary and addressable HIPAA defense implementation requirements right into a finished answer.

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Example text

In [ V e r d ~19861 , it was shown that the appropriately sampled outputs of filters matched to the various users' signature waveforms form a sufficient statistic for this decision problem. Given a symbol duration Tb,these matched filter outputs are given by For the conventional matched filter detector, the decision is made by quantifying these outputs directly as bk = sgn(vk), k = I , . . , K. ) denotes the algebraic sign of its argument. 9) represents the optimal decision for detection in the presence of white Gaussian noise only, under both maximum likelihood (ML) and maximum a posteriori probability (MAP).

Note that, in practical systems. the cancellation of the first user is not perfect, since it is strongly affected by the bit error rate and by amplitude and phase estimation errors. A more detailed discussion on this subject will follow in Chapter 3. Due t o the asymmetry in BER performance, equal power control represents the worst case for systems using SIC receivers. Nevertheless, SIC systems can benefit from unequal power control, such that users received with higher powers can be detected first.

In what follows, we address the following question: is multiuser detection (MUD) the right solution for future generation wireless networks? In order to answer this question, we start with several more basic questions: Why is multiuser detection superior to conventional, matched filter detection? What is the performance/complexity tradeoff for various MUD schemes? And, do we still need power control if multiuser receivers are used? 1 Performance of Matched Filter Receivers Consider a single cell synchronous DS-CDMA system with K active users.

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