Skip to main content

5G References


References

Ahmed, 2018: Ahmed, I., Khammari, H., Shahid, A., Musa, A., Kim, K.S., De Poorter, E. and Moerman, I. “A survey on hybrid beamforming techniques in 5G: Architecture and system model perspectives”. IEEE Communications Surveys & Tutorials, 20(4), pp.3060-3097, 2018.

Alkhateeb, 2014: Alkhateeb, A., El Ayach, O., Leus, G. and Heath, R.W. Channel estimation and hybrid precoding for millimeter wave cellular systems. IEEE Journal of Selected Topics in Signal Processing, 8(5), pp.831-846, 2014.

Alkhateeb, A., 2014: Alkhateeb, A., Mo, J., Gonzalez-Prelcic, N. and Heath, R.W. “MIMO precoding and combining solutions for millimeter-wave systems”. IEEE Communications Magazine, 52(12), pp.122-131, 2014.

Antonescu, 2017: Antonescu, B., Moayyed, M.T. and Basagni, S. mmWave channel propagation modeling for V2X communication systems. In 2017 IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC) (pp. 1-6). IEEE, October, 2017.

Durgin, 1998: Durgin, G., Rappaport, T.S. and Xu, H. Measurements and models for radio path loss and penetration loss in and around homes and trees at 5.85 GHz. IEEE Transactions on communications, 46(11), pp.1484-1496, , 1998.

El Ayach, 2014: El Ayach, O., Rajagopal, S., Abu-Surra, S., Pi, Z. and Heath, R.W. “Spatially sparse precoding in millimeter wave MIMO systems”. IEEE transactions on wireless communications, 13(3), pp.1499-1513, 2014.

Frenzel, 2007: Frenzel, L.E. Principles of electronic communication systems. McGraw-Hill (Boston), 2007.

Garcia, 2016: Garcia, N., Wymeersch, H., Ström, E.G. and Slock, D. Location-aided mm-wave channel estimation for vehicular communication. In 2016 IEEE 17th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC) (pp. 1-5). IEEE, July, 2016.

He, 2019: He, S. and Huang, Y. An Introduction on Millimeter Wave Communications. Wiley 5G Ref: The Essential 5G Reference Online, pp.1-23, 2019

Hosseinzadeh, 2017: Hosseinzadeh, S., Larijani, H., Curtis, K., Wixted, A. and Amini, A. Empirical propagation performance evaluation of LoRa for indoor environment. In 2017 IEEE 15th International Conference on Industrial Informatics (INDIN) (pp. 26-31). IEEE, July, 2017.

Ju, 2018: Ju, S. and Rappaport, T.S. “Simulating Motion-Incorporating Spatial Consistency into NYUSIM Channel Model”. In 2018 IEEE 88th Vehicular Technology Conference (VTC-Fall) (pp. 1-6). IEEE, 2018, August.

Ju, 2019: Ju, S., Kanhere, O., Xing, Y. and Rappaport, T.S. A millimeter-wave channel simulator NYUSIM with spatial consistency and human blockage. In 2019 IEEE Global Communications Conference (GLOBECOM) (pp. 1-6). IEEE, December, 2019.

Lin, 2019: Lin, Z., Du, X., Chen, H.H., Ai, B., Chen, Z. and Wu, D., “Millimeter-Wave Propagation Modeling and Measurements for 5G Mobile Networks”. IEEE Wireless Communications, 26(1), pp.72-77, 2019.

Martinez, 2013: Martinez-Ingles, M.T., Molina-Garcia-Pardo, J.M., Rodríguez, J.V., Pascual-García, J. and Juan-Llácer, L. Experimental comparison of UWB against mm-wave indoor radio channel characterization. In 2013 IEEE Antennas and Propagation Society International Symposium (APSURSI) (pp. 1946-1947). IEEE, July, 2013.

Meijerink, 2014: Meijerink, A. and Molisch, A.F. On the physical interpretation of the Saleh–Valenzuela model and the definition of its power delay profiles. IEEE Transactions on Antennas and Propagation, 62(9), pp.4780-4793, 2014.

Mumtaz, 2016: Mumtaz, S., Rodriguez, J. and Dai, L.  “MmWave Massive MIMO: A Paradigm for 5G”. Academic Press , 2016.

Osseiran, 2016: Osseiran, A., Monserrat, J.F. and Marsch, P. eds. “5G mobile and wireless communications technology. Cambridge University Press”, 2016.

Samimi, 2016: Samimi, M.K. and Rappaport, T.S., “3-D millimeter-wave statistical channel model for 5G wireless system design”. IEEE Transactions on Microwave Theory and Techniques, 64(7), pp.2207-2225, 2016.

Sidhu, 2012: Sidhu, S.S., Khosla, A. and Sharma, A. Implementation of 3-D ray tracing propagation model for indoor wireless communication. International Journal of Electronics Engineering, 4(1), pp.43-47, 2012

Sun, 2018: Sun, S. and T., NYUSIM User Manual, 2018, November.

Sun, 2019: Sun, S. and T., NYUSIM User Manual, 2019, September.

Sun, 2019: Sun, S. and T., NYUSIM User Manual, 2020, February.

Tiwari, 2019: Tiwari, K.K., Grass, E., Thompson, J.S. and Kraemer, R. Beam entropy of 5G cellular millimetre-wave channels. In 2019 IEEE 90th Vehicular Technology Conference (VTC2019-Fall) (pp. 1-5). IEEE, September, 2019.

Traßl, 2019: Traßl, A., Hößler, T., Scheuvens, L., Franchi, N. and Fettweis, G.P. Deriving an empirical channel model for wireless industrial indoor communications. In 2019 IEEE 30th Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC) (pp. 1-7). IEEE, September, 2019.

Tse, 2005: Tse, D. and Viswanath, P. Fundamentals of wireless communication. Cambridge university press, 2005.

Younis, 2003: Younis, I.M. and Sit, M.S.L. Advanced Radio Communication I, 2003.

People are good at skipping over material they already know!

View Related Topics to







Contact Us

Name

Email *

Message *

Popular Posts

Online Simulator for ASK, FSK, and PSK

Try our new Digital Signal Processing Simulator!   Start Simulator for binary ASK Modulation Message Bits (e.g. 1,0,1,0) Carrier Frequency (Hz) Sampling Frequency (Hz) Run Simulation Simulator for binary FSK Modulation Input Bits (e.g. 1,0,1,0) Freq for '1' (Hz) Freq for '0' (Hz) Sampling Rate (Hz) Visualize FSK Signal Simulator for BPSK Modulation ...
Read more

BER vs SNR for M-ary QAM, M-ary PSK, QPSK, BPSK, ...

📘 Overview of BER and SNR 🧮 Online Simulator for BER calculation of m-ary QAM and m-ary PSK 🧮 MATLAB Code for BER calculation of M-ary QAM, M-ary PSK, QPSK, BPSK, ... 📚 Further Reading 📂 View Other Topics on M-ary QAM, M-ary PSK, QPSK ... 🧮 Online Simulator for Constellation Diagram of m-ary QAM 🧮 Online Simulator for Constellation Diagram of m-ary PSK 🧮 MATLAB Code for BER calculation of ASK, FSK, and PSK 🧮 MATLAB Code for BER calculation of Alamouti Scheme 🧮 Different approaches to calculate BER vs SNR What is Bit Error Rate (BER)? The abbreviation BER stands for Bit Error Rate, which indicates how many corrupted bits are received (after the demodulation process) compared to the total number of bits sent in a communication process. BER = (number of bits received in error) / (total number of tran...
Read more

Q-function in BER vs SNR Calculation

Q-function in BER vs. SNR Calculation In the context of Bit Error Rate (BER) and Signal-to-Noise Ratio (SNR) calculations, the Q-function plays a significant role, especially in digital communications and signal processing . What is the Q-function? The Q-function is a mathematical function that represents the tail probability of the standard normal distribution. Specifically, it is defined as: Q(x) = (1 / sqrt(2Ï€)) ∫â‚“∞ e^(-t² / 2) dt In simpler terms, the Q-function gives the probability that a standard normal random variable exceeds a value x . This is closely related to the complementary cumulative distribution function of the normal distribution. The Role of the Q-function in BER vs. SNR The Q-function is widely used in the calculation of the Bit Error Rate (BER) in communication systems, particularly in systems like Binary Phase Shift Ke...
Read more

Channel Impulse Response (CIR)

📘 Overview & Theory 📘 How CIR Affects the Signal 🧮 Online Channel Impulse Response Simulator 🧮 MATLAB Codes 📚 Further Reading What is the Channel Impulse Response (CIR)? The Channel Impulse Response (CIR) is a concept primarily used in the field of telecommunications and signal processing. It provides information about how a communication channel responds to an impulse signal. It describes the behavior of a communication channel in response to an impulse signal. In signal processing, an impulse signal has zero amplitude at all other times and amplitude ∞ at time 0 for the signal. Using a Dirac Delta function, we can approximate this. Fig: Dirac Delta Function The result of this calculation is that all frequencies are responded to equally by δ(t) . This is crucial since we never know which frequenci...
Read more

Wireless Communication Interview Questions | Page 2

Wireless Communication Interview Questions Page 1 | Page 2| Page 3| Page 4| Page 5   Digital Communication (Modulation Techniques, etc.) Importance of digital communication in competitive exams and core industries Q. What is coherence bandwidth? A. See the answer Q. What is flat fading and slow fading? A. See the answer . Q. What is a constellation diagram? Q. One application of QAM A. 802.11 (Wi-Fi) Q. Can you draw a constellation diagram of 4QPSK, BPSK, 16 QAM, etc. A.  Click here Q. Which modulation technique will you choose when the channel is extremely noisy, BPSK or 16 QAM? A. BPSK. PSK is less sensitive to noise as compared to Amplitude Modulation. We know QAM is a combination of Amplitude Modulation and PSK. Go through the chapter on  "Modulation Techniques" . Q.  Real-life application of QPSK modulation and demodulation Q. What is  OFDM?  Why do we use it? Q. What is the Cyclic prefix in OFDM?   Q. In a c...
Read more

BER performance of QPSK with BPSK, 4-QAM, 16-QAM, 64-QAM, 256-QAM, etc

📘 Overview 📚 QPSK vs BPSK and QAM: A Comparison of Modulation Schemes in Wireless Communication 📚 Real-World Example 🧮 MATLAB Code 📚 Further Reading   QPSK provides twice the data rate compared to BPSK. However, the bit error rate (BER) is approximately the same as BPSK at low SNR values when gray coding is used. On the other hand, QPSK exhibits similar spectral efficiency to 4-QAM and 16-QAM under low SNR conditions. In very noisy channels, QPSK can sometimes achieve better spectral efficiency than 4-QAM or 16-QAM. In practical wireless communication scenarios, QPSK is commonly used along with QAM techniques, especially where adaptive modulation is applied. Modulation Bits/Symbol Points in Constellation Usage Notes BPSK 1 2 Very robust, used in weak signals QPSK 2 4 Balanced speed & reliability 4-QAM ...
Read more

What is - 3dB Frequency Response? Applications ...

📘 Overview & Theory 📘 Application of -3dB Frequency Response 🧮 MATLAB Codes 🧮 Online Digital Filter Simulator 📚 Further Reading Filters What is -3dB Frequency Response?   Remember, for most passband filters, the magnitude response typically remains close to the peak value within the passband, varying by no more than 3 dB. This is a standard characteristic in filter design. The term '-3dB frequency response' indicates that power has decreased to 50% of its maximum or that signal voltage has reduced to 0.707 of its peak value. Specifically, The -3dB comes from either 10 Log (0.5) {in the case of power} or 20 Log (0.707) {in the case of amplitude} . Viewing the signal in the frequency domain is helpful. In electronic amplifiers, the -3 dB limit is commonly used to define the passband. It shows whether the signal remains approximately flat across the passband. For example, in pulse shapi...
Read more

Coherence Bandwidth and Coherence Time

🧮 Coherence Bandwidth 🧮 Coherence Time 🧮 MATLAB Code s 📚 Further Reading For Doppler Delay or Multi-path Delay Coherence time T coh ∝ 1 / v max (For slow fading, coherence time T coh is greater than the signaling interval.) Coherence bandwidth W coh ∝ 1 / Ï„ max (For frequency-flat fading, coherence bandwidth W coh is greater than the signaling bandwidth.) Where: T coh = coherence time W coh = coherence bandwidth v max = maximum Doppler frequency (or maximum Doppler shift) Ï„ max = maximum excess delay (maximum time delay spread) Notes: The notation v max −1 and Ï„ max −1 indicate inverse proportionality. Doppler spread refers to the range of frequency shifts caused by relative motion, determining T coh . Delay spread (or multipath delay spread) determines W coh . Frequency-flat fading occurs when W coh is greater than the signaling bandwidth. Coherence Bandwidth Coherence bandwidth is...
Read more