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The novel algorithm is based on minimizing the bit error rate (BER) using a fast approximation of its gradient with respect to the equalizer coefficients.
Since our approach to equalization is based on minimizing the bit error probability, first we express BER as a function of the equalizer coefficients as given in [4] (7).
Depending on the awaited quality of service, the CR can identify several criteria to optimize, such as, minimizing the bit error rate, minimizing energy consumption, maximizing spectral efficiency, etc.
Optimum detection of DST codes, in the sense of minimizing the bit error probability, can be carried out in two steps: 1. Decode the orthogonal ST code by employing Proposition 1. 2.
The MAP decoder computes soft outputs, LL R app (b(n))—the a posteriori reliability information of each coded bit in LLR form by minimizing the bit error probability (BEP [24].
The main resource allocation objectives in CR include but are also not limited to (1) minimizing the bit error rate, (2) minimizing the power consumption, (3) minimizing the interference, (4) maximizing the throughput, (5) improving the quality of service, (6) maximizing the spectrum efficiency, and (7) maximizing the user quality of experience.
Similar(51)
Thus, we formulate the problem of minimizing the bit-error performance subject to some representative parameter constraints.
If all the subcarriers can be utilized, then pilot symbol sequence can be optimally designed in terms of (i) minimizing the channel estimate mean-squared error [1, 3]; (ii) minimizing the bit-error rate (BER) when symbols are detected by the estimated channel from pilot symbols [7]; (iii) maximizing the lower bound on channel capacity with channel estimates [8, 9].
For finding their magnitudes that minimize the bit metric (14), it is the minimization problem of a quadratic function, i.e., differentiating (14) w.r.t |x2,R| and |x2,I| to find the global minima that are given as (15).
Recently, a TEQ design was proposed which directly minimizes the bit error rate (BER) of cyclic prefixed-based systems [18].
We address the design aspects of sparsening filters, including several approaches to minimize the bit error rate of MAP detectors.
More suggestions(15)
reduce the bit
minimizing the query
minimizing the processing
minimizing the level
minimizing the impact
minimizing the number
minimizing the attrition
minimizing the damage
minimizing the incidence
minimizing the embarrassment
minimizing the energy
minimizing the entropy
minimizing the threat
minimizing the risk
minimizing the sequencing
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com