Wireless Communications - Science topic

Thank you Prof. Emil Björnson for the clarification.

i am

professor

There should be a transpose, not a conjugate transpose.

The same applies when considering uplink/downlink reciprocity: The uplink channel matrix is the transpose of the downlink channel matrix, not the conjugate transpose. The phase represents a propagation delay, and it is the same in both directions, not inverted.

Authors like to ignore this to obtain a more convenient presentation in textbooks and papers where the uplink and downlink are more mathematically symmetric (I've done that myself). But I think this isn't the right way to go if we want people to learn how to implement things in practice.

Our paper is related to Localization in underwater Visible light communications using neural networks, I believe Localization using neural networks or deep learning is a hot topic in UVLC, There are many papers on the indoor environment, but more researchers are attracted to underwater communications as the optical domain is far better than RF inside the water for different types of water (Sea or Water or Turbid water). Introducing the blockage and dynamic motion is challenge in localization and transmission in UVLC.

You welcome

I would describe it somewhat differently. In my vocabulary, channel estimation refers to the general concept of utilizing received signals to estimate the channel response. The estimation could be based on pilots, pilots+data or only data (the latter two are known as semi-blind and blind estimation).

Since the channel is changing over time, we need to estimate the channel repeatedly in a wireless system. Normally, we are only trying to estimate the current channel response, but one could also try to estimate future channel responses. This is what we call channel prediction. To succeed, you need an accurate model of the time variations. A Kalman filter is one method that can be used to predict future channels.

Interaction with a tutor is a must within a full automated process handled by the digital revolution, the following research is an answer to your question where online interaction reinforces and accelerates learning:

you can use following code to pass through the log-normal shadowing model:

s= randn(1,20); %Randomly generated signal to pass through the channel.

M=4; order of modulation (I am considering that you are using 4-QAM modulation)

s_mod= qammod(s, M); % Modulate the signal

mean= 0; %Consider mean of Log-Normal model as 0

var=1; % Consider variance of Log-Normal model as 1

h_t= lognrnd(mean, var); % Generate Log-normal model

%Befor passing through channel, add cyclic-Prefix to the modulated signal

Ncp= 5; %cyclic prefix length

s_cp= [s_mod(end-Ncp+1:end) s_mod];

% Now pass throgh Log-Normal model

r1= conv(h_t,s_cp);

%The received signal will be noisy signal, so add the noise

r= awgn(r1,10,'measured'); % Noise at SNR=5

%Now remove cyclic prefix,

y=r(Ncp+1:N+Ncp);

Hello venkataraman,

You can check the following link for free and fast publication of scopus journals.

Hello sir,

please check our paper Statistical Studies Using Goodness-of-Fit

Techniques With Dynamic Underwater Visible

Light Communication Channel Modeling,

Hopefully, it will cover your needs.

Also, If you need anything related to codes, send me an email at afikky@ucsc.edu

Wireless channels contain many propagation paths, with different amplitudes and phases. When a device moves around over distances proportional to the wavelength, the phases are changes rapidly and the paths might add constructively or destructively. If one models this statistically, you get a fading distribution.

Depending on the amplitude mix of the paths, different kinds of fading distribution appears. If all paths are equally strong, you will get Rayleigh fading. If one path is much stronger than the others, while the remaining ones are equally strong, you will get Rician fading.

If the fading doesn't match any of those categories, then the Nakagami distribution is a popular one that allows for fine-tuning a distribution to fit with measurements.

It can be of interest to evaluate the performance of communication systems in different fading scenarios, but one should avoid designing algorithms that are too reliant on a particular fading scenario because the distribution can change rapidly in practice. We talked about this in my podcast: https://ma-mimo.ellintech.se/2022/01/19/episode-25-what-models-are-useful/

You may develop a novel security protocol or privacy preserving protocol and demonstrate that it is efficient as well

Dear Anik Islam Abhi.

Look the link, maybe useful.

Regards,

Shafagat

DearAlireza Qazavi,

In order to get expertise in writing MATLAB codes for your Optimization problems, you first need to follow this manual:https://www.matlabexpo.com/content/dam/mathworks/mathworks-dot-com/images/events/matlabexpo/us/2018/master-class-solving-optimization-problems-with-matlab.pdf

Also some examples : https://www.mathworks.com/help/optim/ug/optimization-toolbox-tutorial.html

Moreover, by googeling your queries you may find bundle of techniques and examples. Practice it, and get its expert.

Good Luck

Thanks Aparna Sathya Murthy Anil Kamboj

If you found something more about MZ coding. Please inform.

Ryan Kao Based on your attachments I assume you are procuring R&S instruments. If you look at section 2.4 in both the attachments, it lists the devices and options required to conduct the tests. [This is just one example from the documents.] Typically, such capablities are licensed software options that must be purchased with the instrument (or even a later purchase of license can enable the feature!).

It will be best to go through the instrument documents, which are quite tedious to navigate through; you may save some time by reaching out to the vendor application engineer (AE) who might be interacting with your department/ institute. Understanding the test environment system is key to correct test execution and measurement.

If you need some insight into RF measurements in general, you may want to check out my book "RF & μWave Measurements: For Design, Verification and Quality Control", which is available at select amazon marketplaces. However, it does not address your 3GPP specific question.

/rgds

Dear Omar ALzoubi ,

5G telecommunications: on-body massive MIMO virtual array design.

A visible light positioning network planner.

Accurate indoor human positioning system by combining Visible Light and Radio Frequency signals.

Agricultural IoT data collection for wide crop fields.

Regards,

Shafagat

I suppose this depends on what kind of obstacles you are considering and how they are affecting the signals. If you consider an object that is scattering the signal, then the pathloss will be proportional to (d_1*d_2)^2 where d_1 is the distance from the transmitter to the obstacle and d_2 is the distance from the obstacle to receiver. For a given total propagation distance d_1+d_2, it follows that the pathloss is at its smallest when the scattering object is close to the transmitter or the receiver.

That sum rate expression is measured in bit/s/Hz. If you multiply with the bandwidth, you get it in bit/s.

Dear Zhenkang Zheng,

the future virtual 6G networks in the form of 6G slices will definitely be set up as "Software-Defined and Open Programmable 6G Slices". The idea of SRv6 Network Programming as the basic principles for the programmability of 6G slices is specified in the Internet Standard RFC 8986.

I have attached a short list of sources of information.

Best regards and good luck

Anatol Badach

European Vision for the 6G Network Ecosystem; DOI: 10.5281/zenodo.5007671

Petar D. Bojović, Teodor Malbasic, Goran Martić, Zivko Bojovic: „Toward 6G networks: Dynamic management for multi-slice QoS“

Wen Wu, Conghao Zhou, Mushu Li, Huaqing Wu, Haibo Zhou, Ning Zhang, Xuemin (Sherman) Shen, Weihua Zhuang: AI-Native Network Slicing for 6G Networks

Amin Shahraki, Mahmoud Abbasi, Md. Jalil Piran, Amir Taherkordi: „A Comprehensive Survey on 6G Networks: Applications, Core Services, Enabling Technologies, and Future Challenges“

European Vision for the 6G Network Ecosystem

Jie Dong: SRv6 based Network Slicing

Gaps, features and enablers for 5G/6G service management and orchestration

RFC 8986: Segment Routing over IPv6 (SRv6) Network Programming

SRv6 – IPv6 Segment Routing Figure 009239: Basic idea of SRv6 Network Programming

Dear Jiahui Li ,

If there is no obstacles in the path between the transmitter and the receiver and the medium is air then then the channel is for sure a line of sight.

If there is reflection from the ground to the receiver then there will be multi path effect. In this case one would model the channel by Rician model.

Both model are treated intensively in the literature. I think by skilled antenna directing to the UAV one can reduce the reception of the reflected radiation from the ground.

Best wishes

Dear Gul Lakhta ,

There is something basic which you you would like to consider. From the point view of the signals, the interference signal acts in a similar way to noise. When it is added to the symbol signal it will cause that it may be falsely detected if its value is increases such that the combined signal will be located in the neighboring decision regions of the adjacent symbols in the constellation diagram. So the interference and noise have the same effect in the symbol error.

Therefore one speaks not only from S/N ratio but also from the S/(N+I).

The noise has Gaussian amplitude distribution while the interference may not have such distribution because of the nature of the interference.

The interference signal sources are normally known and then they can be subtracted from the composite signal. If after interference cancellation there will be residual interference it will be treated as a noise concerning its effect on the symbol error. In the sense that it will set the S/I +N minimum level to achieve specific bit error rate. You see if N=0 then S/I will set this minimum.

Hope I could answer satisfactorily you question.

Best wishes

You have to explain time and space complexity of your algorithm

Aparna Sathya Murthy , thank you very much for your help ....

Anik Islam Abhi For example forecasting and game theory are both effective tools to support finance-related decision-making and reduce the impact of risk factors.

The ergodic capacity is the theoretically maximum data rate (bit/s) that one communicate at over a fading channel, where the fading processing is an ergodic process. More precisely, this is the largest rate for which the probability of decoding errors goes to zero as the length of the transmission goes to infinity.

An achievable rate is any data rate below the capacity. It is normally associated with a particular (suboptimal but practical) way of transmitting.

The sum rate is the summation of the achievable rates of multiple concurrent transmissions, for example, different users that are multiplexed.

Muhammad Hamza El-Saba Thank you very much for your answer.

The length of the cyclic prefix should be at least equal to the number of channel taps minus one, so that the linear channel filtering appears as if it is a cyclic convolution.

you can use ns3, have look at the documentation.

Old news but I found it here (http://sparselab.stanford.edu/atomizer/) if anyone finds this post while searching for it.

I've also downloaded the ZIP for posterity. Anyone feel free to get in touch if you need it. I plan on keeping it forever.

Dear Arash Darabi ,

Adding to the colleague U. Dreher , you can see the definition of the optical front-hauls in the paper at the link: https://www.3coptics.com/News/9.html

The optical from haul is the optical fiber link between the base band unit and the remote radio unit. It transmits the base band signal to the the radio unit.

grant-free Transmission" is the transmission in which the quality of service is not granted. This is the bit rate and the bit error rate.

Best wishes

Perhaps you can use generic tables to calculate that.

Zero is equal to -infinity in dB scale, since log10(0) = -infinity.

An issue with your computations is that the interference and noise power should be added together in linear scale when computing the SINR, not dB scale. So if the interference is -50 dBm and the noise is -95 dBm, the interference+noise is 10^(-5)+10^(-9.5) mW, which you can then convert to dBm as 10*log10( 10^(-5)+10^(-9.5) ).

Agree with Dr. Omid M Kandelusy

Thanks for the question. The answers also interest me

Blockchain technology can be used to safely distribute the structure and weights of trained neural networks based on tensor matrix theory in the process of mass replication in the production of Edge AI computing units. Blockchain technology can be used to coherently update multiple identical Neural Networks for adaptation to new situations or increase accuracy etc.

NetSim support a range of technologies, including the capability to interface Matlab and C++ programs. So if you want to integrate 5G in a Netsim experiment, you will need to deploy the 5G experiment in Matlab then interface it with NetSim for full deployment. I hope this answers your question.

Dear Tariq Islam ,

Yes, some smart phones have MIMO capability and so they can be used to realize your proposal.

Best wishes

Castallia, Contiki OS, OMNET ++, TinyOs are few are the options to simulate WSN. NS3 can be used but it is not designed for WSN as such.

The basic algorithms for phase configuration and channel estimation are described in our tutorial article: https://arxiv.org/pdf/2102.00742.pdf

Dear Laxmikant Minz ,

The colleagues above gave satisfactory answer. The ultimate answer of your question is to make survey test at all intended points where one one can measure directly the recieved signal strength. This means one has to determine the spatial distribution of the received signal at the coverage area.

May be the best way is to determine such distribution empirically.

But this may be very tedious.

The other solution is to use use models of large scale fading and small scale fading to obtain statistical channel models.

The last possible solution is to make an electromagnetic solution for the signals emitted from the antennas in the real propagation space with districted scatters.

Best wishes

Dear Yukinari He ,

It would be nice from you that you define the relation between the communication symbols and numerology??

This is the first time that I hear from such vocabulary in electrical communication systems.

What I know is the different symbols resulting after modulating the binary data.

There are binary symbol where every symbol contains either binary 0 or 1.

There is the the 2-bit symbol representing values from 00,10,01 and 11.

There is 3-bit symbol which has 8 states.

and so on.

This method of M-ary symbols help control the number of bit hertz.

And one can send more data in the same bandwidth by using higher order modulation.

It is known that every channel condition or S/N ratio can allow specific symbols.

If it mean symbols then yes one can control the order of modulation of the symbol.

Best wishes

Matlab UAV toolbox should be a very powerful tool.

Guidance models and navigation, trajectory and waypoint following:

UAV flight path using translations and rotations

Your question is not highly dependent and specific on wifi. It seems more important to think in terms of network traffic.

If the WiFi hub considered serves a home, you need to build scenarios:

-family members: children, parents, flat sharing people

-working hours: if working from home, how many videoconferencing sessions ,average duration, data upload and download between home location and organisation VPN

-outside of working hours: sessions of gaming, movies ("Netflix" or equivalent, movie of 120 minutes or more etc), music streaming. Browsing, YouTube, etc...

You may run a number of differently populated scenarios to explore and understand...

This may show you the limit of WiFi and take you into fine access...

As to how to picture for yourself what happens in homes during the current era of Covid19, you may benefit from browsing this study/model:

How does it work for you?

Let me know

It is generally hard find closed-form expressions. It always the same math involved:

Say that the SINR is S/(I+sigma^2), where S and I are random due to fading. Then the outage probability when communicating at the rate x is:

Pr{ log2(1+S/(I+sigma^2)) < x } = Pr{ S/(I+sigma^2) < 2^x - 1 }.

If you know the distribution of S/(I+sigma^2), then you can compute this directly.

If you only know the PDFs of S and I individually, then you need to rewrite it as

Pr{ S/(I+sigma^2) < 2^x - 1 } = Pr{ S - I (2^x - 1) < sigma^2 (2^x - 1) }.

Now "sigma^2 (2^x - 1)" is a constant, but you need to compute the PDF of "S - I (2^x - 1)", which can be done via integration. The joint PDF of the sum of random variables is obtained by convolution.

At the end of the day, the chance that you get a nice PDF of "S - I (2^x - 1)" so that you then compute the probability is closed form by integration over the PDF from 0 to sigma^2 (2^x - 1) is not so big.

try this code:

"function H=nak_m(m,Nr,Nt)

n=zeros(Nr,Nt);

for i=1:2*m

n=n+randn(Nr,Nt).^2;

end

n=n/(2*m);

phi=2*pi*rand(Nr,Nt);

H=(n^0.5).*cos(phi)+j*(n^0.5).*sin(phi);"

I hope it helps

Sure, if two users are located in the same angular direction but at different distances, the reflected beam can be partially directed to both of them. You can find an example of this on Figure 10 of https://arxiv.org/pdf/2002.04960.pdf

I think it will depend on the complexity of the algorithm and the performance of the hardware in terms of CPU.

You can create the channel directly with Matlab using the "comm.RicianChannel" then apply this filter to your signal

Muhammad Abbas Khan Thank you

There exist several pathless model, depending on the propagation environment. But you can use conventional model such as free space or Rice.

V = 0m/s

Therefore, Doppler shift = 0

Thank you Ahmed el Mahjoubi

Dear Tariq Islam ,

Assuming that the transmission coefficients of the channels from the A and B to node C are ha and hb and assume that the transmit signal of A is Sa and that of B is Sb then the received signal at node C rC= ha Sa + hb SB

The power received is rC^2.

This power can be considered an interference which is added to the white noise to determine the threshold of the useful received signal.

So the total noise at the node C= rC^2 +N

The required signal to noise ratio is then given by

C= B log2 (1 + S/( rC^2 +N))

where S is the useful recieved signal power at node C received from the intended node. Bis the bandwidth and C is the maximum bit rate.

Best wishes

similar to Laser Power Converters (LPCs) for Solar cells, are there any LED Power Converters available ?

Importance and significance of the topic.

Discuss the background and target audience.

Summarize the surveyed research area and explain why the surveyed area has been studied.

Summarize the classification scheme you used to do the survey.

Summarize the surveyed techniques with the above classification scheme.

Satheesh Monikandan Balakrishnan , For two different systems I think it is when log2(M_a)*R_a = log2(M_b)*R_b, where M is the modulation order and R is the code rate. Than you will have for both curves an equal horizontal shift between SNR and Eb/N0 of 10log10(log2(M)*R).

In case your question is about when the SNR and Eb/N0 curves will be equal then it is when log2(M)*R = 1.

I hope it help.

Dear@ Oludele,

welcome,

The colleagues gave satisfactory answer to your question but I want to explain some fundamental points:

- The noise is generated in the receiver and it is modeled by an input noise power at the input of the receiver.

- There is the free path attenuation which depends on the frequency of the signal and the path length.

- There is extra path attenuation due to rain and fog.

- This attenuation is measured and given in characteristic curves that can be be found in the link budget calculations in the books of microwave and satellite communications.

Best wishes

Good question

Dear Hareesh Ayanampudi ,

Machine learning and deep learning will be used in wireless communication to enhance the state of the art classification, prediction and detection techniques.

I saw some applications on the channel estimation and equalization in OFDM wireless communication systems.

It was found that they have detection accuracy comparable to maximum mean square errors MMSE. This work is sent to publications when it is published i will report on its publication citation!

May be the main problem is the computational loads.

Best wishes

3GPP is already supporting MU-MIMO, which is a more spectrally efficient non-orthogonal access scheme since it actually adds additional degrees-of-freedom to the transmission. Hence, I doubt that NOMA will be utilized by 3GPP to increase spectral efficiency. The 3GPP document "Study on Non-Orthogonal Multiple Access (NOMA) for NR" shows that the performance gains of NOMA are small or nonexisting under practical conditions.

I think that 3GPP is still considering to support NOMA for some short-block-length cases where one can benefit by not having to schedule users individually.

you can use :

For the implementing the patches you can use the standard materials thought for them. If you work at relatively low frequencies, then you can use the FR4 PCB material. If you work at higher frequencies you can use Roger substrates. At much higher frequencies you can use Teflon substrates.

To design multi band frequencies please refer to the paper in the link:

The typical size of the elements being used in experiments is lambda/10 to lambda/5. The reason is that you want each element to scatter the signals without a directivity, so that the combined effect of having many elements will determine the directivity of the "reflected" signal.

I also explain this at 26:00 in the following video:

You can also listen to the Episode 3 in my podcast "Wireless Future", we we discuss this. It is available on YouTube and in podcast apps.

May be the most interesting topic is the investigation and implementation of massive MIMO mobile communication systems. As the number of beam formed increases with controlled interference the spectral density increases leading to much higher bandwidth and number of users.

Goran Popovic thanks again. So, we cannot speak of a single standard LEACH-C algorithm. Rather, it is constructed by an algorithm designer. For the sake of fair comparisons, it would be better if the papers mentioned details of how they used LEACH-C.

nice project

good luck

Dear Kazi,

You ask about the physical model for distributing underwater sensors to monitor the properties of the water.

There is the see water. There is also the river water and there are lakes and pools.

Also there is also the distance of the sensor from the surface.

So, there is no specific answer for your question. I think it is very application oriented.

On the other side as the water is fluid, any concentration gradients of salt or temperature tend to decay with time because of the water molecular motion.

The best method to solve this problem is to make preliminary site surveying.

Or design your network to be able to increase the sampling time and adjust the distance between the elements of the wireless sensor arrays to achieve full observation of the intended water volume. As the wireless sensor nodes are based on microcontrollers they cab be reconfigured to Mach your needs.

These are different approaches to solve you problem.

Best wishes

Besmir

As for the spectral density of the VLC channels you can see our papers in different modulation techniques in VLC.

As the comparison

As for the comparison between the VLC and WiFi stems from the information carrier. VLC is in visible light and WiFi in UHF in radio frequencies.

The main difference is that the radio waves are able to penetrate the walls of the building. So VLC are confined in rooms.

The second main difference is the simplicity of the transmitter and the receiver.

VLC are much simpler.

As fore the specification of each system you can get them from their standards.

Best wishes

Dear Mr. Gomez,

It is the first time I have ever heard about TWDP, but it seems to me that you can use a joint unscented Kalman filtering for parameter estimation in this case. You can find the details and a novel method proposed by me in the following article:

In standard joint unscented Kalman filtering, the parameter should not necessarily be linear with respect to states. However, in modified one, it must. Furthermore, you can find the Matlab scripts considered for this article in:

I think that you can easily try it. If you have any questions, please do not hesitate to ask.

With my kind regards,

Altan

How to add application layer protocols to Omnet++