DOWNLOAD FUNDAMENTALS OF DIGITAL COMMUNICATION MADHOW

Real baseband operations for Problem 2. This value is very close to the one obtained in c. Then, since X1 is exponential with mean 1. This is expected as averaged channel gain has less fluctuations and this increases the outage capacity. Solution for Problem 2. The convergence is both almost surely and in the mean square sense, but we will not worry about such technical details.

Uploader:	Mezirr
Date Added:	13 December 2010
File Size:	53.92 Mb
Operating Systems:	Windows NT/2000/XP/2003/2003/7/8/10 MacOS 10/X
Downloads:	21460
Price:	Free* [*Free Regsitration Required]

Fundamentals of digital communication

Let AT denote the transpose not conjugate transpose, even if A is complex of A. Capacity as a function of SNR for Problem 8.

The range of integration is determined as shown in Figure This can also be infered from the above equation analytically assuming small phit. This value is very close to the one obtained in c. The noise enhancement caused by the ZF equalizers is higher, but comparable.

Since the channel gains and noises are complex Gaussian, the decision statistics are complex Gaussian conditioned on H1. A good choice is 32 or 64 sub-carrier system.

Fundamentals of digital communication (eBook, ) []

We see that the turbo code obtained by the parallel concatenation of [7,5] RSC codes does better because its pmin is greater than that obtained by the parallel concatenation of [5,7] RSC codes. You may send this item to up to five recipients. Then we have 0. Hence, B[n] can be chosen from a complex constellation.

However, QAM2 has some points with 4 nearest neighbors, communicaton we definitely cannot Gray code it.

We can therefore obtain the optimal noncoherent decision rule starting from these decision statistics. Performance of the rate 13 turbo code formed by parallel concatenation of rate 1 2 [7,5] RSC code for different number of input bits We see that there is a significant gain in terms of bit error rate performance by increasing the Eb input blocklength. Also, assume we are trying to evaluate the probability that X takes the value k, i.

Part c Since, Z is complex gaussian, the components of Z are complex gaussian. To minimize computations, we differentiate in the frequency domain to get U fas shown.

Fundamentals of Digital Communication. This is about 44 dB worse than that for the AWGN channel considered in the example, so that the range fundaentals is about 22 dB smaller, i. Conditional densities and decision regions for Problem 3.

Hence X and Y cannot be independent. The conditional densities and decision regions are sketched in Problem 3. Histogram of the Q component of time-domain samples for Problem 8. We will now outline the pos- sible values the triple can take such that the communicationn message is a 1. Selected pages Title Page. Histogram of the I component of time-domain samples for Problem 8.

Factor of L on every branch Let a refer to the state 10, b refer to the state 11, c refer to the state 01 and d to the terminal 00 state.

We now verify that E[Lchannel ] that we get from simulations matches the theoretical Eb value of 2 N 0. Also, the curves lose their Gaussianity after 6 iterations or so.

Conversely, given the bit comminication rate, we can recover some information about the mean and the variance of the Gaussian. The spectra R f and C f for Problem 2. The main difference with the earlier part is that, the decision metric Hamming distance - refer to Problem 7 is to be minimized. For clip levels of 3dB and 10dB, no symbol errors were observed in symbols suggesting low SER. The output of the box should be the I and Q components of yp with respect to f2.