Please submit your solutions in Laulima.
In this assessment, we look at a realistic channel model with its parameters determined by field measurements. Then we will implement a simplified version of this channel model in this Google Colab notebook.
One feature of the 5th-generation (5G) wireless communication systems is the usage of the millimeter-wave (mmWave) band at 60 GHz. Therefore, it is crucial to understand the mmWave channels. The Millimetre-Wave Evolution for Backhaul and Access (MiWEBA) project is one of the efforts toward this goal. If you are interested, you might want to take a look at the complete project report.
For this assessment, we will only need to refer to this paper, which summarizes the main findings in channel modeling. You can read through the first two sections to get the background of the study.
We will implement a quasi-deterministic (Q-D) channel model, as illustrated in Fig. 8 of the paper. The Q-D channel consists of a few strong deterministic rays (D-rays) and some random rays (R-rays). Each ray or multipath is a cluster of rays with similar delays. You can look at Fig. 9 of the paper for an example with two D-rays (i.e., the line-of-sight (LoS) path and the ground reflection path) and two R-rays (i.e., one path due to reflection from a car and the other due to reflection from a building).
Below are the list of tasks to do.
- (4 points) Please look at Fig. 3 and Fig. 4, and identify four major multipaths in terms of delay (in ns) and power (in dB).
- Note that a major multipath should have a relatively high power (i.e., less attenuation).
- (2 points) How would you assign each one of the four major multipaths to the LoS D-ray, the ground reflection D-ray, and two R-rays?
- (2 points) Fill in the power delay profile above in the Google Colab notebook. Then calculate the following quantities.
- Calculate the excess delays of the multipaths relative to the LoS path. For example, if the delays are 100 ns, 150 ns, 250 ns, 300ns, the excess delays should be 0 ns, (150-100 = 50) ns, (250-100 = 150) ns, (300-100 = 200) ns. Then convert the excess delays in seconds to excess delays in time slots according to the sampling rate.
- Convert the power in dB to the power in the linear scale.
- (1 point) Run the code to see the power spectral density (PSD) of the transmit signal and that of the received signal. Explain how the channel results in the difference between the two PSDs? Hint: think about the delay spread of the channel.
- Note that the PSD illustrates the spectrum of a random signal. It is defined as the Fourier transform of the autocorrelation function of the random signal. Unlike a deterministic signal, for a random signal, we compute the Fourier transform of its autocorrelation function, instead of the signal itself, because the autocorrelation function is deterministic.