1. A 3D device adapted to produce an image comprising an opacity estimate predictor adapted to predict opacity of at least one primitive using at least one first equation derived from at least one second equation used to compute opacity.
2. The 3D device of claim 1, wherein said first equation comprises MIN value={(A==0b00)|(B==0b00) & (SubCD)|(C==0b00)|(D==0b00) & (SubE)|(E==0b00)}|{SubCD & (C==0b11) & (D==0b11) & (SubE)|(E==0b00)|(A==0b00) & (B==0b00)}|{SubE & (E==0b11) & (SubCD)|(C==0b00) & (D==0b00)|(A==0b00) & (B==0b00)} and MAX value={(A==0b11) & (B==0b11) & (\u02dcSubCD)|(C==0b00)|(D==0b00) & (\u02dcSubE)|(E==0b00)}|{(A==0b11) & (B==0b11) & (\u02dcSubCD) & (C==0b11) & (D==0b11)}|{(A==0b11) & (B==0b11) & (\u02dcSubE) & (E==0 b11)}|{(\u02dcSubCD) & (C==0b11) & (D==0b11) & (\u02dcSubE)|(E==0b00)}|{(\u02dcSubCD) & (C==0b11) & (D==0b11) & (\u02dcSubE) & (E==0b11)}|{(\u02dcSubE) & (E==0b11) & (\u02dcSubCD)|(C==0b00)|(D=0b00)}.
3. The 3D device of claim 1, wherein said second equation comprises (A*B\xb1C*D\xb1E)<<S.
4. The 3D device of claim 3, wherein said first equation is based on at least axioms 1.0*1.0=1.0, 0.0*x=0.0, 1.0+x=1.0 when clamped, 0.0\u2212x=0.0 when clamped, x\u22121.0=0.0 when clamped, 0.0<<n=0.0 and 1.0<<n=1.0 when clamped.
5. The 3D device of claim 1 wherein the opacity estimate predictor is further adapted to reject said primitive if said predicted opacity is less than or equal to a minimum value, and further comprising a texture module adapted to compute opacity of at least one non-rejected primitive.
6. The 3D device of claim 5, wherein said texture module is further adapted to compute said opacity according to the at least one second equation.
7. The 3D device of claim 6, wherein said second equation comprises (A*B\xb1C*D\xb1E)<<S.
8. The 3D device of claim 7, wherein said second equation is based on said first equation.
9. The 3D device of claim 5, wherein said texture module is further adapted to blend non-rejected primitives.
10. The 3D device of claim 1, further comprising a register communicating with at least said predictor and adapted to store a primitive list.
11. The 3D device of claim 10, further comprising an X-loop and Y-loop communicating with at least said register and adapted to determine at least one relevant scan line.
12. The 3D device of claim 11, further comprising a Z-order device communicating with at least the X-loop and Y-loop and adapted to order the primitives.
13. A 3D core for producing an image using at least two primitives comprising:
an opacity estimate predictor adapted to predict opacity of the primitives using at least one first formula and reject at least one of the primitives if said predicted opacity is equal to a minimum value;
a register adapted to store a list of said non-rejected primitives; and
a texture device adapted to compute the opacity of the non-rejected primitives using at least one second formula.
14. The 3D core of claim 13 wherein said first formula is derived using said second formula.
15. The 3D core of claim 13 further adapted to parse said list of non-rejected primitives.
16. The 3D core of claim 15 further adapted to reject any non-rejected primitives that are behind any non-rejected primitives having a predicted maximum opacity value.
17. The 3D core of claim 13, further comprising an X-loop and Y-loop communicating with at least said register and adapted to determine at least one relevant scan line.
18. The 3D core of claim 17, further comprising a Z-order device communicating with at least the X-loop and Y-loop and adapted to order the primitives.
19. A method for producing an image, the method comprising:
predicting opacity of primitives represented by data used to produce the image, using at least one first equation;
rejecting select data based at least in part on said predicted opacity, forming a group of non-rejected data; and
computing opacity for said group using at least one second equation; and
blending said group, forming the image.
20. The method of claim 19, wherein forming said group comprises rejecting at least one of said data having a minimum predicted opacity value.
21. The method of claim 19, wherein forming said group comprises rejecting at least one of said data behind data having a maximum predicted opacity value.
22. The method of claim 19, further comprising ordering said group from a back to a front of the image.
23. The method of claim 19, further comprising generating a data list.
24. The method of claim 19, further comprising identifying data for at least one display line of the image.
25. The method of claim 19, wherein said second equation is based on said first equation.
26. The method of claim 19, wherein said first equation comprises a plurality of equations.
27. The method of claim 19, wherein said second equation comprises a plurality of equations.
28. A method of computing opacity of a plurality of primitives used to produce an image, the method comprising:
predicting an opacity value of the primitives using at least one first equation;
rejecting at least one of the primitives based at least in part on said predicted opacity value;
generating a primitive list of first non-rejected primitives;
identifying at least one of the primitives from said list for at least one display line of the image;
ordering said first non-rejected primitives;
rejecting at least one of said first non-rejected primitives based at least partially on said predicted opacity value forming second non-rejected primitives;
computing opacity for said second non-rejected primitives using at least one second equation; and
blending all said second non-rejected primitives, producing the image.
29. The 3D core of claim 28 wherein said first formula is derived using said second formula.
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 method of switching between transmission modes in an IEEE802.11n wireless communication system, comprising steps of:
determining, by a receiver, a decision metric as a function of post-detection constellation-coding SNR, said determining including:
estimating communication channel information based on long preamble;
computing a squared min-distance of constellation for different MCS (modulation coding scheme) with the same transmission rates; and
selecting between transmission modes based on the decision metric.
2. The method of claim 1, wherein selecting between transmission modes further includes selecting between spatial multiplexing, delay diversity and space-time coding transmission modes based on the decision metric.
3. The method of claim 2 further including comparing MCS of different transmission modes using the decision metric.
4. The method of claim 3 wherein selecting between transmission modes further includes selecting between transmission modes based on the decision metric to achieve the best system performance.
5. The method of claim 1, wherein determining a decision metric further includes determining a decision metric as a function of a constellation distance and coding rate.
6. The method of claim 5 wherein determining a decision metric further includes:
computing a post-detection SNR (\u03c1MIMO) for different transmission modes;
computing a coding loss of higher coding rate (\u03c1coding); and
computing a decision metric D for each transmission mode, such that each transmission mode has a corresponding decision metric.
7. The method of claim 6 wherein selecting the transmission modes further includes switching between the transmission modes based on the decision metric of each transmission mode.
8. The method of claim 6 wherein selecting the transmission modes further includes selecting the transmission mode with the largest decision metric.
9. The method of claim 8 wherein the communication system comprises a transmitter and a receiver, the method further comprising feeding back the selection information to the transmitter for switching between transmission modes accordingly.
10. The method of claim 6 wherein computing a decision metric D for each transmission mode further includes for each transmission mode computing:
D=\u03c1MIMOd2min-constellation\u2212\u03c1coding,
where (d2min-constellation) is the squared min-distance of constellation for different MCS with the same transmission rates.
11. The method of claim 10, wherein eigen-value computation for transmission mode selection is not performed.
12. The method of claim 10, wherein the communication system comprises a MIMO system.
13. A controller for switching between transmission modes in an IEEE802.11n wireless communication system, comprising:
a decision metric calculator configured for determining a decision metric as a function of post-detection constellation-coding SNR by:
estimating communication channel information based on long preamble;
computing a squared min-distance of constellation for different MCS (modulation coding scheme) with the same transmission rates; and
a selector that selects between transmission modes based on the decision metric.
14. The controller of claim 13, wherein the selector selects between transmission modes further by selecting between spatial multiplexing, delay diversity and space-time coding transmission modes based on the decision metric.
15. The controller of claim 14 further including means for comparing MCS of different transmission modes using the decision metric.
16. The controller of claim 15 wherein the selector selects between transmission modes further by selecting between transmission modes based on the decision metric to achieve the best system performance.
17. The controller of claim 16, wherein the decision metric calculator determines the decision metric further by determining a decision metric as a function of post detection SNR, a constellation distance and coding rate.
18. The controller of claim 17 wherein the decision metric calculator determines the decision metric further by:
computing a post-detection SNR (\u03c1MIMO) for different transmission modes;
computing a coding loss of higher coding rate (\u03c1coding); and
computing a decision metric D for each transmission mode, such that each transmission mode has a corresponding decision metric.
19. The controller of claim 18 wherein the selector selects the transmission modes further by switching between the transmission modes based on the decision metric of each transmission mode.
20. The controller of claim 18 wherein the selector selects the transmission modes further by selecting the transmission mode with the largest decision metric.
21. The controller of claim 20 wherein the communication system comprises a transmitter and a receiver, such that the controller further feeds back the selection information to the transmitter for switching between transmission modes accordingly.
22. The controller of claim 18 wherein decision metric calculator computes the decision metric D for each transmission mode further by, for each transmission mode, computing:
D=\u03c1MIMO+d2min-constellation\u2212\u03c1coding,
where (d2min-constellation) is the squared min-distance of constellation for different MCS with the same transmission rates.
23. The controller of claim 22, wherein eigen-value computation for transmission mode selection is not performed.
24. The controller of claim 22, wherein the communication system comprises a MIMO system.
25. The controller of claim 18, wherein post-detection SNR (\u03c1MIMO) for direct mapping mode is determined as min(1diag{R\u2020R\u2020H}), where R\u2020 is the MIMO equalizer coefficients computed using MMSE (Minimum Mean Squared Error) criterion or ZF (Zero Forcing) criterion.
26. The controller of claim 18, wherein post-detection SNR (\u03c1MIMO) for spatial spreading mode with number of spatial streams NSS=1 is determined as \u2225Hq\u2225F where \u2225H\u2225F is the Frobenius norm of the H matrix, defined as \u03a3j,k|hj,k|2,and q is the spatial spreading antenna map vector.
27. The controller of claim 18, wherein post-detection SNR (\u03c1MIMO) for spatial spreading mode with number of spatial streams Nss>1 is determined as min(1diag{R\u2020R\u2020H}) where R\u2020 is the MIMO equalizer coefficients based on the equivalent channel coefficient HQ, using the MMSE (Minimum Mean Squared Error) criterion or the ZF criterion, and Q is the spatial spreading matrix.
28. The controller of claim 27 wherein the \u03c1coding values are further optimized based on detailed implementation codes.
29. The controller of claim 18, wherein post-detection SNR (\u03c1MIMO) for STBC (Space-Time Block Coding) mode with number of spatial streams Nss=1 is determined as \u2225H\u2225F where \u2225H\u2225F is the Frobenius norm of the H matrix, defined as \u03a3j,k|hj,k|2.
30. The controller of claim 18, wherein post-detection SNR (\u03c1MIMO) for STBC (Space-Time Block Coding) mode with number of spatial streams Nss=2 is determined as min (\u2225H1\u2225F, \u2225H2\u03bcF) where H1 is first of two rows of channel matrix H, corresponding to the channel of the first data stream, and H2 are the third and fourth rows of the channel matrix H, corresponding to the second data stream.
31. The controller of claim 18, wherein post-detection SNR (\u03c1MIMO) for basic beamforming mode with power loading is determined as \u03c1MIMO=min(1diag{R\u2020R\u2020H}+diag(P1,P2, . . . ,PNss)), where R\u2020 is the MIMO equalizer coefficients based on the equivalent channel coefficient HQ, using the MMSE (Minimum Mean Squared Error) criterion or the ZF (Zero Forcing) criterion, Q is the eigen-steering matrix.
32. The controller of claim 18, wherein coding loss of higher coding rate (\u03c1coding) is determined as:
\u03c1coding (dB)
Rate 12 codes
0
Rate 23 codes
2
Rate 34 codes
3
Rate 56 codes
\u20094.
33. The controller of claim 18, wherein a squared mm-distance of constellation (d2min-constellation) for different MCS with the same transmission rates is determined as:
d2min-constellation
d2min-constellation (dB)
BPSK
4
6.02
QPSK
(2\u221a{square root over (2)})2
3.01
16QAM
(2\u221a{square root over (10)})2
\u22123.98
64QAM
(2\u221a{square root over (42)})2
\u221210.2.
34. A method of switching between transmission modes in an IEEE802.11n wireless communication system, comprising steps of:
Determining, by a receiver, a decision metric as a function of post-detection constellation-coding SNR including:
determining a decision metric as a function of a constellation distance and coding rate;
estimating communication channel information based on long preamble;
computing a post-detection SNR (PMIMO) for different transmission modes;
computing a coding loss of higher coding rate (P coding);
computing a squared min-distance of constellation (d^2 min_constellation) for different MCS (modulation coding scheme) with the same transmission rates; and
computing a decision metric D for each transmission mode, such that each transmission mode has a corresponding decision metric; and
selecting between transmission modes based on the decision metric.
35. A controller for switching between transmission modes in an IEEE802.11n wireless communication system, comprising:
a decision metric calculator configured for determining a decision metric as a function of post-detection constellation-coding SNR, a constellation distance and coding rate, the decision metric calculator further configured for:
estimating communication channel information based on long preamble;
computing a post-detection SNR (\u03c1MIMO) for different transmission modes;
computing a coding loss of higher coding rate (\u03c1coding);
computing a squared min-distance of constellation (d2min-constellation) for different MCS (modulation coding scheme) with the same transmission rates; and
computing a decision metric D for each transmission mode, such that each transmission mode has a corresponding decision metric; and
a selector that selects between transmission modes based on the decision metric.