func GoIFFT_C(samples vlib.VectorC, N int) vlib.VectorC {
n := runtime.GOMAXPROCS(8)
if N != samples.Size() {
samples.Resize(N)
}
// fbins := vlib.NewVectorC(N)
result := vlib.NewVectorC(N)
NChannels := make([]gocomm.Complex128Channel, N)
//bigChannel := make(gocomm.Complex128Channel, N)
for i := 0; i < N; i++ {
NChannels[i] = gocomm.NewComplex128Channel()
go GoFFTPerK(NChannels[i], samples, i, N, true)
//go GoFFTPerK(bigChannel, samples, i, N, false)
}
//for i := 0; i < N; i++ {
// result[i] = (<-bigChannel).Ch
//}
for i := 0; i < N; i++ {
result[i] = (<-NChannels[i]).Ch
}
runtime.GOMAXPROCS(n)
return result
}
func IFFT_C(samples vlib.VectorC, N int) vlib.VectorC {
samples.Resize(N)
fbins := vlib.NewVectorC(N)
normalize := complex(math.Sqrt(1.0/float64(N)), 0)
result := vlib.NewVectorC(N)
for i := 0; i < N; i++ {
for n := 0; n < N; n++ {
scale := float64(i) * float64(n) / float64(N)
binf := complex(0, 2.0*math.Pi*scale)
fbins[n] = cmplx.Exp(binf)
}
// fbins = fbins.ScaleC(i)
// fmt.Print("\ni=", i, fbins)
result[i] = vlib.DotC(samples, fbins) * normalize
}
return result
}
func Complex2ComplexAFn(InObj []SComplex128Obj) (Outobjs SComplex128AObj) {
veclen := len(InObj)
samples := vlib.NewVectorC(veclen)
for i := 0; i < veclen; i++ {
samples[i] = InObj[i].Ch
}
maxexp := int(float64(InObj[0].MaxExpected) / float64(veclen))
Outobjs.Ch = samples
Outobjs.Message = InObj[0].Message
Outobjs.MaxExpected = maxexp
Outobjs.Ts = InObj[0].Ts * float64(veclen)
Outobjs.TimeStamp = InObj[0].TimeStamp
return Outobjs
}
func (m *MPChannel) updateCoeff(timestamp float64) {
/// first time
generated := false
if m.TimeStamp == -1 {
m.Coeff.Resize(m.pdp.Size())
for i := 0; i < m.pdp.Size(); i++ {
m.Coeff[i] = sources.RandNC(m.pdp[i])
}
generated = true
m.TimeStamp = 0 /// Unusuall if inbetween the MPchannel timestamp has got RESET !!
} else {
/// Existing channel-coeff is valid till m.Timestamp+m.TS,
valid := timestamp < (m.TimeStamp + m.Ts)
if !valid {
/// TRIGGER NEW COEFF
m.Coeff = vlib.NewVectorC(m.pdp.Size())
for i := 0; i < m.pdp.Size(); i++ {
m.Coeff[i] = sources.RandNC(m.pdp[i])
}
m.TimeStamp = timestamp
generated = true
}
}
/// Write new coeff to feedback channel if new was generated
if m.FeedbackCH != nil && generated {
var chdata gocomm.SComplex128AObj
chdata.Ch = m.Coeff
chdata.TimeStamp = m.TimeStamp
chdata.Ts = m.Ts
// fmt.Printf("\n CH:GENERATED @ %v with Coeff : %v, Gain : %v ", timestamp, m.Coeff[0], cmplx.Abs(m.Coeff[0])*cmplx.Abs(m.Coeff[0]))
m.FeedbackCH <- chdata
}
}
func Conv(in1, in2 vlib.VectorC) (result vlib.VectorC) {
L1 := in1.Size()
L2 := in2.Size()
N := L1 + L2 - 1
result = vlib.NewVectorC(N)
fmt.Printf("\n in1=%v", in1)
fmt.Printf("\n in2=%v", in2)
for n := 0; n < N; n++ {
for l := 0; l < L1; l++ {
indx := n - l
if indx < L2 && indx >= 0 {
result[n] += in1[l] * in2[n-l]
}
}
// result[n] = sum
}
fmt.Printf("\n result=%v", result)
return result
}
func GoFFTPerK(outputSymbol gocomm.Complex128Channel, inputsamples vlib.VectorC, k, N int, inverse bool) {
kbyN := float64(k) / float64(N)
normalize := complex(1.0/math.Sqrt(float64(N)), 0)
if !inverse {
kbyN = kbyN * -1.0
}
fbins := vlib.NewVectorC(N)
for n := 0; n < N; n++ {
scale := kbyN * float64(n)
binf := complex(0, 2.0*math.Pi*scale)
fbins[n] = cmplx.Exp(binf)
}
result := vlib.GoDotC(inputsamples, fbins, 4) * normalize
// result := vlib.DotC(inputsamples, fbins) * normalize
var data gocomm.SComplex128Obj
data.Ch = result
outputSymbol <- data
}
/// Default is a BPSK modulator
func (m *cdmaMeta) setDefaults() {
m.spreadSeq = vlib.NewVectorC(1)
m.sf = 1
}