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Moreover, the EE can be further improved by using the optimal bit allocation.
From the field experiments, the optimal bit stick-out is determined to be 147.4 mm, and the range of reasonable bit stick-out is 96.6 198.2 mm.
The key factors influencing the optimal bit stick-out, such as hydraulic parameters, formation strength, and the ratio of bit-to-conductor dimensions, are also considered.
A distortion model is created to integrate both subjective and objective factors and an R-D criterion is used to obtain the optimal bit allocation.
The total MSE of the optimal bit allocation is given by sigma_{epsilon}^{2}(rho, theta_{o})={hG}_{m}2^{-2R(rho,theta_{o})}, (17).
Therefore, the optimal bit overhead for tag acquisition reads (cf. (2)) beta_{text{CS}}^{text{(A)}} = M = leftlceil c K log frac{N}{K} rightrceil.
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Besides, once the MS reaches to its optimal bit-rate, the extra probing packets should be reduced, so the MS can stay using the optimal bit-rate most of the time.
Since (27) and (1) are the same within a constant factor of πe/ 6 (which is identical for all transform coefficients), it is easy to verify that the optimal bit-allocation solution under SWC-HRSQ model is also given by (2).
The psychovisual threshold can be utilized to find the optimal bits-budget for image signals.
Similarly, at time slot t, the optimal number of bit rate allocated to SU k is obtained: ∑ m = 1 M R k, m, t * L k, m, t * = m ( t ) p k p k a Δf log 2 h k * β k, m, t Δf ln ( 2 ) + p k b R max (58).
Notice that the optimal number of bits decreases as the feedback power increases.
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