Modulation and demodulation model based on SDMA

Modulation and demodulation model based on SDMA

According to multi-resolution analysis theory, the modulation and demodulation of signal c (t) is the process of wavelet reconstruction and decomposition. To this end, another function φ∈L2 (R) is introduced, and φmn (t) = 2m / 2φ ( 2mt-n), so that the two spaces based on ψ and φ are mutually orthogonal, then there are two sequences {p (n)} and {q (n)} such that

g108-6.gif (671 bytes) (8a)
g108-7.gif (673 bytes) (8b)
g108-8.gif (1174 bytes) (8c)

Let fj and gj be functions on two orthogonal spaces Vj and Wj with scale j, respectively, then they have a unique series representation:

g108-9.gif (628 bytes) (9a)
g108-10.gif (626 bytes) (9b)

From equations (8) and (9), the wavelet decomposition and reconstruction algorithm can be obtained

g108-11.gif (571 bytes) (10a)
g108-12.gif (580 bytes) (10b)
g108-13.gif (946 bytes) (10c)

In the case of limited resolution (ie m < ts108.gif (98 bytes) ), Equation (4) can be rewritten as

g108-14.gif (1114 bytes) (11)

Received signal ts36-3.gif (86 bytes) (t) = c (t) + n (t), n (t) is the channel noise, according to equation (11), the best receiver model can be obtained as

g108-15.gif (1163 bytes) (12)

SDMA modulation and demodulation model can be obtained by formula (10) ~ (12), as shown in Figure 1, 2.

t108-1.gif (2555 bytes)

Figure 1 SDMA's multi-rate modulation model

t108-2.gif (2760 bytes)

Figure 2 SDMA multi-rate demodulation (best receiver) model

In actual systems, there are always g108-16.gif (350 bytes) , So the system capacity is M = ts108.gif (98 bytes) -M, ts108.gif (98 bytes) And M are the upper and lower limits of the system resolution, respectively. If multi-level PAM modulation is used on a channel of scale m, the transmission rate of the channel is Bm = 2mlog2Lm bits / second, where Lm is the number of modulation levels. When the data is in g108-17.gif (406 bytes) Transmission on the frequency band. For this modulation method, the bit error rate in the additive Gaussian fractal noise channel [2] can be obtained without coding. In fact, it is similar to the additive white Gaussian noise (AWGN) channel.

g108-18.gif (1002 bytes) (13)

Where Em is the average energy per symbol, and σ2 is the variance of AWGN. From equation (13), it can be seen that the bit error rate of each channel will be inconsistent.

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