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towards co-channel users This is done by allocating the dominant DoA to the desired user and assuming other DoAs correspond to co-channel users (the loss of diversity gain induced by only using the primary DoA is discussed in the final section of this chapter) The user's downlink spatial covariance matrix is then computed using equation (524) (524) where b m o d is the user's modified power azimuth spectrum, a d is the downlink steering vector and H is the Hermitian transpose of a vector The co-channel user downlink spatial covariance matrix, R d , is also estimated in the same way The optimum downlink weights are then computed Results in [118] show a 10 dB performance degradation when the spatial covariance matrix has no temporal averaging applied to it.

(5.70)

A second transformation technique expressing the uplink covariance matrix, R,, as a Fourier series expansion has been proposed by Goldberg and Fonollosa in [ 1201 Fourier coefficients of the spatial covariance matrix are estimated at the uplink frequency by means of least squares estimation The coefficients are then used to compute the spatial covariance matrix at the downlink frequency, Rd Simulations show an average signal-to-noise-plus-interference ratio improvement of 20 dB above a single element for both low and high angular spread environments Performance is, however, based upon the assumption that the signal phase is constant over the FDD spacing which is an idealistic assumption since it was shown earlier in this chapter that signal amplitude (and therefore phase) is heavily dependent on frequency A rotation matrix based transformation is proposed by Rayleigh, Diggavi, Jones and Paulraj in [121].

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So many customer service programs emphasize end-user customers, to a fault. If a department is concerned only

Here, the phases of the uplink spatial covariance matrix are rotated corresponding to a dominant DoA This is accomplished by applying a linear transformation (a) to the uplink steering vector (a,) as shown in equation (525)..

h Q ( t )= F-'{ffQ(.f)} * h I ( t ) * g+(t) d(t) = v(t) = c*(t) * hl(t) * g - ( t ) .

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To be anisochronous, (1) groups may not be related by symmetry, taking into consideration internal motions which are rapid on the NMR time scale, and (2) there must be su cient eld gradient so that the di erence is observable. For homotopic groups, chemical shifts are indistinguishable in chiral or achiral solvents, that is, the groups are isochronous. Enantiotopic groups are isochronous in achiral solvents and distinguishable (anisochronous) in chiral solvents. In principle, the enantiotopic protons of bromochloromethane will be anisochronous in a chiral solvent. However, it requires a fair degree of association to make the chemical shift di erence visible. This requirement may be satis ed in hydrogen-bonding solvents:

To illustrate the calculation of the compaction factor, let us suppose that the bending is provided by sector magnets. A sector magnet is one in which the ideal orbit enters and exits at right angles to the magnet ends. The procedure for calculating the difference in path between a particle of the central momentum and an off-momentum particle is sketched in Figure 3.16. The circumference change, AC, is given by

Figure B14.2. Orbital correlation diagram for electrocyclic opening of cyclopropyl cation: S, A and solid lines indicate disrotatory opening; S, A and dotted lines indicate conrotatory opening.

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