1. A method of activating a de-activated cell in a cellular radio system, the method comprising:
collecting measurements from a number of user equipment connected to the cellular radio system;
constructing a model for mapping a first cell generating a least power increase in the cellular radio system to be activated based on the collected measurements;
determining to activate the cell mapped as the first cell to be activated when traffic demand of the cellular radio system cannot be served using already activated cells, wherein activation of the cell mapped as the first cell decreases the overall energy consumption of the cellular radio system; and
collecting and storing measured power consumptions of base stations at given loads;
wherein the measured power consumptions of the base stations at the given loads are used as input data when determining to activate the cell mapped as the first cell to be activated.
2. The method of claim 1 wherein the collected measurements comprise one or more received signal powers or one or more timing advances.
3. The method of claim 1 wherein the collected measurements comprise one or more inter radio access technology measurements or one or more positioning measurements.
4. The method of claim 1 wherein constructing the model comprises automatically constructing the model for mapping the first cell to be activated based on the collected measurements using machine learning.
5. The method of claim 1 further comprising ordering additional measurements to be performed by one or many user equipment.
6. A network device for activating a de-activated cell in a cellular radio system, the network device comprising a processor configured to:
collect measurements from a number of user equipment connected to the cellular radio system;
construct a model for mapping a first cell generating a least power increase in the cellular radio system to be activated based on the collected measurements;
determine to activate the cell mapped as the first cell to be activated when traffic demand of the cellular radio system cannot be served using already activated cells, wherein activation of the cell mapped as the first cell decreases the overall energy consumption of the cellular radio system; and
collect and store measured power consumptions of base stations at given loads;
wherein the measured power consumptions of base stations at given loads are used as input data when determining to activate the cell that is mapped as the first cell to be activated.
7. The device of claim 6 wherein the measurements comprise one or more received signal powers or one or more timing advances.
8. The device of claim 6 wherein the measurements comprise one or more inter radio access technology measurements or one or more positioning measurements.
9. The device of claim 6 wherein the processor is further configured to automatically perform the construction of the model for mapping the first cell to be activated based on the collected measurements using machine learning.
10. The device of claim 6 wherein the processor is further configured to order additional measurements to be performed by one or many user equipment.
The claims below are in addition to those above.
All refrences to claim(s) which appear below refer to the numbering after this setence.
1. A semiconductor device having a semiconductor multi-layer structure which includes at least one active layer including at least one luminescent layer of InxAlyGa1\u2212x\u2212yN (0<x<1, 0\u2266y\u22660.2), and at least a part of said at least one luminescent layer acting as a quantum well,
wherein said semiconductor device satisfies at least one of:
a first condition that a threshold mode gain of said quantum well is more than 12 cm\u22121, and
a second condition that said semiconductor device has an internal loss \u201c\u03b1i\u201d (cm\u22121) which satisfies \u03b1i>12xn \u2212\u03b1m (cm\u22121), where \u201c\u03b1m\u201d is a mirror loss, and \u201cn\u201d is a number of said quantum well; and
a third condition that said semiconductor device has a slope efficiency \u201cS\u201d (WA) which satisfies: S<3\xd7{\u03b1m(12\xd7n)}\xd7{(1\u2212R1)\u221a(R2)}{(1\u2212\u221a(R1R2))\xd7(\u221a(R1)+\u221a(R2))}, where \u201cR1\u201d is a first reflectance of a first cavity facet, from which a light is emitted, \u201cR2\u201d is a second reflectance of a second cavity facet opposite to said first cavity facet, \u201c\u03b1m\u201d is a mirror loss, and \u201cn\u201d is a number of said quantum well, and
wherein a differential gain \u201cdgdn\u201d of said at least one active layer satisfies dgdn\u22671.0\xd710\u221220(m2)1 and
standard deviations of microscopic and macroscopic fluctuations in a band gap energy of said at least luminescent layer are not more than 40 meV; and
wherein said microscopic fluctuation is measured based on temperature dependence of a photoluminescence lifetime and wherein said microscopic fluctuation is controlled by heat treatment of said semiconductor device at a temperature between 850\xb0 C. and 1200\xb0 C.
2. The semiconductor device as claimed in claim 1, wherein said semiconductor device has a cavity length \u201cL\u201d of not less than 1000 micrometers, and said first reflectance \u201cR1\u201d is not more than 20%, said second reflectance \u201cR2\u201d is not less than 80% and less than 100%, and said slope efficiency \u201cS\u201d satisfies S<2.1n (WA).
3. The semiconductor device as claimed in claim 1, wherein said semiconductor multi-layer structure comprises a gallium-nitride-based multi-layer structure.
4. The semiconductor device as claimed in claim 3, wherein said gallium-nitride-based multi-layer structure extends over a gallium-nitride-based substrate.
5. The semiconductor device as claimed in claim 3, wherein said gallium-nitride-based multi-layer structure extends over a sapphire substrate.
6. The semiconductor device as claimed in claim 3, wherein said gallium-nitride-based multi-layer structure extends over a substrate having a surface dislocation density of less than 1\xd7108cm2.
7. The semiconductor device as claimed in claim 1, wherein a standard deviation \u201c\u0394x\u201d in the \u201cmicroscopic fluctuation\u201d of the indium composition is not more than 0.067.
8. The semiconductor device as claimed in claim 7,
wherein said semiconductor device has a slope efficiency \u201cS\u201d (WA) which satisfies:
S<3\xd7{\u03b1m(12\xd7n)}\xd7{(1\u2212R1)\u221a(R2)}{(1\u2212\u221a(R1R2))\xd7(\u221a(R1)+\u221a(R2))},
where \u201cR1\u201d is a first reflectance of a first cavity facet, from which a light is emitted, \u201cR2\u201d is a second reflectance of a second cavity facet opposite to said first cavity facet, \u201c\u03b1m\u201d is a mirror loss, and \u201cn\u201d is a number of said quantum well.
9. The semiconductor device as claimed in claim 8, wherein said semiconductor device has a cavity length \u201cL\u201d of not less than 1000 micrometers, and said first reflectance \u201cR1\u201d is not more than 20%, said second reflectance \u201cR2\u201d is not less than 80% and less than 100%, and said slope efficiency \u201cS\u201d satisfies S<2.1n (WA).
10. The semiconductor device as claimed in claim 7, wherein said semiconductor device has an internal loss \u201c\u03b1i\u201d (cm\u22121) which satisfies \u03b1i>12\xd7n\u2212\u03b1m (cm\u22121), where \u201c\u03b1m\u201d is a mirror loss, and \u201cn\u201d is a number of said quantum well.
11. The semiconductor device as claimed in claim 7, wherein said semiconductor device has a photo-luminescence peak wavelength distribution of not more than 40 meV in said active layer.
12. The semiconductor device as claimed in claim 1, wherein the microscopic fluctuations are not more than 20 meV.
13. The semiconductor device as claimed in claim 1, wherein a dispersion degree of a thermal carrier in said active layer is estimated by varying a temperature measurement, so as to determine said microscopic fluctuation.