We first show how many bits are required to quantize cosθ m.
Please also note that the method requires additional bits to quantize FAC signals.
As it can be seen from the two tables, the coding bits required for the quantized norms and the quantized MDCT coefficients are the least using the proposed context-based adaptive arithmetic coding.
where γ u, u ′′ = 1 − 2 − B u, u ′′ / ( N t − 1 ) with B u, u ′′ is the number of bits to quantize CDI of the serving BS and κ u, v ′′ = 2 − B v, u ′′ / ( N t − 1 ) with B v, u ′′ ; v ≠ u is the number of bits to quantize CDI of interfering BSs when the user is in the CR.
As pointed out by Isham (1994, 2002), it may well be that the extension of quantum theory to general relativity requires one to quantize, in some sense, not only the metric but also the underlying differential structure and topology.
It can be appreciated that better performance is obtained by configurations which dedicate a higher number of bits to quantize the phase, B P, in comparison to those dedicated to quantize the relation between magnitudes, B M. In fact, most of these configurations dedicate one or two bits more to quantize the phase than to quantize the magnitude.
In this subsection, we discuss the relation between the number of bits employed to quantize the different parameters in our DQ limited feedback scheme and its performance.
In fact, besides the term M×8 bits, a value of 19×2 M is required to store the 2 M Euclidean distances quantized on 19 bits each.
