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As the focus is on optimizing spectral efficiency, each BS schedules the user with the highest SNR.
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Specifically, to optimize spectral efficiency (SE) for single-relay cooperative communication in UWB-based weANseeke seek the relay with the optimal location together with the corresponding optimal power allocation.
Moreover, all these AS schemes we study here are merely to optimize the spectral efficiency, not other metrics.
To optimize the spectral efficiency in cellular networks, the overhead of such training has to be as low as possible to reduce the corresponding redundancy as long as the quality of service requirements are achieved.
Instead of optimizing to improve spectral efficiency of access networks, in [41], energy efficiency of some well-known principal scheduling schemes is introduced.
Thus, a pattern-based cognitive communication system (PBCCS) was introduced to optimize the overall spectral efficiency with respect to SNR [9, 10].
However, this is a known problem for MIMO broadcast channels designed to optimize the system spectral efficiency under total transmit power constraints, rather than per BS antenna power constraints [16].
We formalize the problem of maximizing network spectral efficiency optimizing (a) QAM size, (b) power allocation, (c) time allocation, and (d) relays transmitting and receiving at each phase.
Simulated annealing is used in Section 4.5 to optimize the BER and spectral efficiency when under interference.
The network spectral efficiency is then computed optimizing the choice of S, yielding R ( DF ) = max S ⊆ { 1, 2, 3 } R ( DF ) ( S ) = max S ⊆ { 1, 2, 3 } C min i ∈ S { H i } C ∑ i ∈ S G i 2 C min i ∈ S { H i } + C ∑ i ∈ S G i 2. (9).
The emerging wireless communication systems are carefully designed to simultaneously optimize the delivered user capacity, the average spectral efficiency and the cell coverage.
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