A Symbolic Encapsulation Point as Tool for 5G Wideband Channel Cross-Layer Modeling
Abstract
:1. Introduction
2. Related Work
3. Methods Applied
3.1. Propagation Deterministic Mechanism
- ${\phi}_{i}\left(t\right)$, introduced by the scatterer reflection coefficient and here, omitted due to complexity;
- $\mathsf{\Delta}{\varphi}_{i}$, originating from phase rotation along the electrical distance of a wave.$$\mathsf{\Delta}{\varphi}_{i}=\frac{2\pi}{{\lambda}_{0}}{d}_{i}$$
- ${c}_{i}\left(t\right)$, which represent ith scatterer contribution to overall magnitude of received signal;
- ${x}_{CE}\left(t-\raisebox{1ex}{${d}_{i}$}\!\left/ \!\raisebox{-1ex}{$c$}\right.\right)$, term that follows changes of transmitted signal.
3.2. Level Crossing Rate and Average Fade Duration
3.3. Finite State Markov Chain Constitution
3.3.1. State Classification Model
3.3.2. Channel Matrix Derivation
4. Symbolic Encapsulation Roadmap
5. Numerical and Simulation Results
5.1. HST Scenario
5.2. V2V Scenario
5.3. V2Vcrossroad Scenario
6. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Step | Pseudocode |
---|---|
1 | Input N_{samples}, N_{SC}, Δf, t_{s}, P_{t} |
2 | B= (N_{samples}−1)/2; |
3 | Generate distance matrix D=$\left|\text{}d\left[-B\right]\dots d\left[0\right]\dots d\left[B\right]\right|$ |
4 | Calculate c_{i} according to (6) for every of N_{SC} scatterers |
5 | Calculate P_{r} using (8) |
6 | Calculate scatterers magnitude vectoraaccording to (7) |
8 | f_{axis} = (start: Δf: end) |
9 | W =zeros (N_{samples}, length(f_{axis})) |
10 | LCR, AFD = zeros (length(f_{axis}), N_{samples}) |
11 | Forn=1 toN_{samples} |
12 | For b=1 to length(f_{axis}) |
13 | For s=1 to N_{SC} |
14 | Λ =c/f_{axis}(b) |
15 | W(n,b)= W(n,b) + a(s)×exp(-j×2π/λ)× D(s,n) |
16 | end |
17 | end |
18 | end |
19 | For b=1 to length(f_{axis}) |
20 | r = transpose(column(W,b)) |
21 | Calculate root mean square RMS of r |
22 | Normalize as abs(r)/RMS |
23 | Calculate level crossing rate LCR and average fade duration AFD across r |
24 | Update matrices LCR(p,1:length(LCR)) and AFD(p,1:length(AFD)) |
25 | end |
Numerology | Case A | Case B | Case C |
---|---|---|---|
SCS (kHz) | 15 | 30 | 60 |
Bandwidth (MHz) | 3.6 | 7.2 | 14.4 |
Resolution (kHz) | 180 | 360 | 720 |
Symbol duration (μs) | 66.7 | 33.3 | 16.7 |
Simulation time (4 symbols) | 200 | 100 | 50 |
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Stefanovic, N.; Blagojevic, M.; Pokrajac, I.; Greconici, M.; Cen, Y.; Mladenovic, V. A Symbolic Encapsulation Point as Tool for 5G Wideband Channel Cross-Layer Modeling. Entropy 2020, 22, 1151. https://doi.org/10.3390/e22101151
Stefanovic N, Blagojevic M, Pokrajac I, Greconici M, Cen Y, Mladenovic V. A Symbolic Encapsulation Point as Tool for 5G Wideband Channel Cross-Layer Modeling. Entropy. 2020; 22(10):1151. https://doi.org/10.3390/e22101151
Chicago/Turabian StyleStefanovic, Nenad, Marija Blagojevic, Ivan Pokrajac, Marian Greconici, Yigang Cen, and Vladimir Mladenovic. 2020. "A Symbolic Encapsulation Point as Tool for 5G Wideband Channel Cross-Layer Modeling" Entropy 22, no. 10: 1151. https://doi.org/10.3390/e22101151