Introduction to CDMA Wireless Communications by Mosa Ali Abu-Rgheff

By Mosa Ali Abu-Rgheff

The booklet provides an in-depth research of the rules of the unfold spectrum thoughts and their functions in cellular communications. It begins with sturdy foundations within the electronic communications which are necessary to unequivocal knowing of the CDMA expertise, and courses the reader during the basics and features of mobile CDMA communications.

Features include:

* a really transparent and thorough description of the rules and purposes of unfold spectrum innovations in multi-user cellular communications.
* Matlab-based labored examples, workouts and functional classes to obviously clarify the theoretical concepts.
* An easy-to-read clarification of the air interface criteria utilized in IS-95 A/B, cdma2000, and 3G WCDMA.
* transparent displays of the excessive pace downlink and uplink packet entry (HSDPA/HSUPA) strategies utilized in 3G WCDMA.

The ebook is a truly compatible creation to the foundations of CDMA communications for senior undergraduate and graduate scholars, besides researchers and engineers in who're trying to increase their expertise.

  • A very transparent and thorough description of the rules and functions of unfold spectrum suggestions in multi-user cellular communications.
  • Matlab-based labored examples, workouts and functional classes to obviously clarify the theoretical concepts.
  • An easy-to-read clarification of the air interface criteria utilized in IS-95 A/B, cdma2000, and 3G WCDMA.
  • Clear shows of the excessive velocity downlink and uplink packet entry (HSDPA/HSUPA) thoughts utilized in 3G WCDMA.

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Example text

In this section we consider this issue in more detail because of its importance in the system. Commonly, the receiver front-end stage comprises of a bandpass filter at the Intermediate Frequency (IF) stage to limit the noise power input to the detector stage. Let the one-sided noise power spectral density at the input to the filter be N0 W/Hz, the frequency transfer response of the filter be H(f) centred at fo , and the bandwidth (3 db cut-off frequency) of the filter be B, respectively. Since the received signal and the noise at the input of the IF filter are uncorrelated, we can analyse them separately.

18 Polar representation of the complex twiddle factor for N = 8. e. W87 = −W83 . e. up to half the sampling frequency since the other half can be obtained from the first half as stated before. The efficient algorithm for computing the DFT is known as the Fast Fourier Transform (FFT), originally developed by Cooley and Tukey in 1965. The basic idea behind the FFT is the process of continually decomposing and recombining the N-point transform into a pair of N2 -point transforms. For example, consider 1024-point transform and split it into two 512-point DFTs.

64) n=0 nk = e−j N nk is known as the twiddle factor. The inverse DFT (IDFT), f(n), is where WN given by: 2π f (n) = 1 N N−1 −nk F(k) WN k = 0, 1, . . . 18. 18 are spaced by radian frequency ω = 2π N . The periodicity property of the twiddle factor means we only need to compute − 2π nk mod 2π. 18 Polar representation of the complex twiddle factor for N = 8. e. W87 = −W83 . e. up to half the sampling frequency since the other half can be obtained from the first half as stated before. The efficient algorithm for computing the DFT is known as the Fast Fourier Transform (FFT), originally developed by Cooley and Tukey in 1965.

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