Wireless Networks - Science topic

Designing a mathematical model for the Ad hoc On-Demand Distance Vector (AODV) routing protocol involves formalizing the behavior, performance metrics, and operational characteristics of the protocol. Below are steps on how to approach the design of such a model:

Step 1: Define the Network Environment

Step 2: Understand AODV Operation

AODV can be understood through its key operational phases:

Step 3: Establish Key Performance Metrics

Define the metrics you are interested in analyzing, including:

Step 4: Mathematical Formulation

Trd=TRREQ+TRREPTrd​=TRREQ​+TRREP​

Te2e=∑i=1D(LR+Tpropagation+Tqueue)Te2e​=i=1∑D​(RL​+Tpropagation​+Tqueue​)

Where TpropagationTpropagation​ is the propagation delay, and TqueueTqueue​ is the queuing delay at each node.

Th=PDR⋅LTtotalTh=Ttotal​PDR⋅L​

Where TtotalTtotal​ is the total time for communication.

PDR=NdeliveredNsentPDR=Nsent​Ndelivered​​

Where NdeliveredNdelivered​ is the number of packets successfully delivered and NsentNsent​ is the total packets sent.

O=NcontrolNdataO=Ndata​Ncontrol​​

E=NRREQ⋅Etx+NRREP⋅Erx+NRERR⋅EtxE=NRREQ​⋅Etx​+NRREP​⋅Erx​+NRERR​⋅Etx​

Step 5: Simulate and Validate

Step 6: Refine the Model

Based on validation results, refine your model to improve accuracy, considering factors like dynamic changes in network topology, varying traffic patterns, or more realistic mobility models.

Best is to first try the Lite version which is available for free: https://tetcos.com/download.html

Wishing you every success, International Journal of Complexity in Applied Science and Technology

Hi Isaac Agyapong ,please see the official website of the conference, which is in English: https://ais.cn/u/BBfQBb

The geometric mean gives a higher fairness between the users, because every user must get a non-zero throughput. This is not the case for the geometric mean.

Hello Swe Zin,

I'm glad to hear that you've fixed your implementation, but I'm sorry to hear that you're still having issues with the SNR and SINR values being negative. I'm more than happy to help you here. You can share your updated implementation and any specific questions you have, and I'll do my best to help you resolve the issues.

Regarding negative SNR and SINR values, it could be due to the fact that the noise level is too high compared to the received signal. Make sure that you are using the correct units for the signal and noise levels (e.g., dBm, dBW, or linear scale). If necessary, convert between linear and logarithmic scales using the following equations:

Additionally, ensure that the signal and noise levels are calculated correctly. If the SNR and SINR values are in dB scale, ensure that you're adding and subtracting in dB scale correctly.

Lastly, when you calculate the rate, you should make sure that you're using the linear SINR and SNR values in the Shannon capacity formula:

If you still encounter issues, please share the updated implementation and any specific areas you're struggling with, and I'll do my best to help you further.

regards, Alessandro

thank you for your help

Currently, there is no widely accepted definition or framework for IIOT 5.0. However, it is generally believed that IIOT 5.0 will build on the foundations of IIOT 4.0, which is characterized by the convergence of operational technology (OT) and information technology (IT) systems, and the widespread use of advanced analytics and artificial intelligence to improve industrial processes and decision-making.

Some of the potential differences between IIOT 4.0 and IIOT 5.0 could include the increased adoption of edge computing and the use of advanced robotics and autonomous systems. IIOT 5.0 may also involve a greater emphasis on interoperability and the integration of data from a wide range of sources, including distributed ledgers and blockchain technology.

In terms of cybersecurity challenges, IIOT 4.0 and IIOT 5.0 share many of the same risks and vulnerabilities, such as the potential for cyber attacks on critical infrastructure, data breaches, and the compromise of industrial control systems. However, IIOT 5.0 may present additional challenges due to the greater use of edge computing and the deployment of more complex and autonomous systems.

Possible solutions to address these challenges include implementing robust access controls and authentication mechanisms, ensuring the secure transmission and storage of data, and incorporating cybersecurity into the design of IIOT systems from the outset. Other measures could include the use of machine learning algorithms and artificial intelligence to detect and respond to cyber threats in real-time, and the adoption of industry-wide cybersecurity standards and best practices. It will be important for organizations and stakeholders to work collaboratively to address these challenges and ensure the continued security and reliability of IIOT systems.

This is a useful reference that explains how you can utilize the log file to generate various charts https://support.tetcos.com/support/solutions/articles/14000141188-how-to-obtain-sinr-mcs-and-throughput-vs-time-for-a-5g-1gnb-1ue-scenario-with-a-time-varying-radio-

hi look here 5G coming with high data rate which give ablilty to increase damend of application and realablity with tremndous data so you can start work 5G with sensor iot different application here on file i share there's part issue and chellanges hopes it help .

Unfortunately, it is difficult to answer these questions without more context. Each situation is unique and depends on the specific conditions, processes, and technologies being used in the workplace. That being said, there are some general principles that can be applied to any workplace:

a) Employers should ensure that the workplace meets Occupational Safety and Health Administration (OSHA) and International Labour Organization (ILO) standards. This includes providing proper training, equipment, and procedures to ensure that workers are protected from potential hazards.

b) Employers should identify and evaluate any potential risks associated with the new technologies, systems, and processes being used in the workplace. This includes assessing the potential for physical, psychological, and social risks.

c) Employers should implement measures to mitigate any identified risks, including providing personal protective equipment (PPE) and training.

d) Employers should ensure that workers are aware of their rights, responsibilities, and their role in maintaining a safe and healthy workplace. e) In general, it is likely that workplaces utilizing Industry 4.0 technologies will have improved conditions for occupational health and safety than in the old manufacturing industry.

f) Employers should continually assess and review their safety systems and processes, and make sure that they are up to date with the latest technologies and best practices. They should also ensure that workers are regularly consulted and involved in safety decisions.

Even you want to develop both the transmitter and receiver in your simulation, still you only need to do your simulation in baseband to include all effects of the channel. Actually, as I know, none one is doing such simulation in RF band, because all channel effects can represented in baseband simulation, while simulation in RF band is much expensive but provides none extra value.

Let's have a quick review of some concept. In general an RF signal (also referred to as bandpass signal) is:

P(t)=I(t)*cos(w*t)+Q(t)*sin(w*t),

where w is the angular frequency of the RF carrier, I(t) and Q(t) are the in-phase and quadrature-phase components of P(t) which is a real signal. For convenience, usually a complex signal S(t) = I(t)+j*Q(t) is defined and referred to as the baseband signal of P(t). Correspondingly, the bandpass (RF) signal can be expressed as:

P(t) = Real{S(t)*exp(j*w*t)},

where Real{x} stands for the real component of x.

With these notations, when the system (including the transmitter + channel + receiver) is studied, we only need to investigate the baseband signal S(t) and its changes (due to the channel).

In short, what you can do is as follows.

(1) Generate a sequence of baseband QAM symbols (denoted by S(t)).

(2) Generate a sequence of complex Rayleigh fading coefficients, such as

h(t) = a(t)+j*b(t), where a(t) and b(t) are independent Gaussian random processes with proper power spectral density depending on how fast the channel changes.

(3) The received baseband signal is r(t) = s(t)*h(t)+n(t), where n(t) is the optional noise. Your receiver then further works on this baseband signal r(t).

If you really want to see the waveform of the received RF signal, simple take the real component of {r(t)*exp(j*w*t)}.

Hope these helpful to you. Good luck.

Hi,

Q-learning is suitable for a problem with a limited number of states and actions.

DQN, DDPG and SAC are more suitable for problems with many states and actions.

Kind regards

Dear Tariq, you mentioned 10 subchannels, shouldn't the number of subchannels be a power of 2? Like 8, 16, 32,.....128,.....etc? I might be wrong so please check it. Regarding your question, do you ask about the subchannels distribution nature? as in terms of Rayleigh or Rician, or you meant allocation?

Dear Manash Chakraborty ,

I believe this article can help you find inspiration. This is a Q1 journal about network communication and network architecture. It proposed an internet of things platform with p2p wireless communication, high speed, and security. It integrated with ION DID (based on blockchain) too. Finally, the source code is available on the GitHub link in this article.

BRs.

Hi! This is the first of the topics that we talk about in the following podcast: https://youtu.be/LyIINgdVQ8Y

The short answer is that the communication of data and the use of that data within an application is co-optimized, so that we only communicate what is needed and measure performance of the communications based on the end-user application.

Hello venkataraman,

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

Many current systems use wide bandwidths and multi-antenna techniques that jointly offer enough diversity against small-scale fading that the end performance is roughly what you would get without fading.

My point is that small-scale fading is important when designing channel estimation protocols, precoding/combining schemes, and other things that need to change at the per-channel-realization basis. But if one does those things properly, then the system performance will be roughly the same as without fading.

Hello Dr. Ali Othman Al Janaby

The question was for 5G at the time as I was just beginning to explore this field.

Thanks for your interest.

Best regards

IoT or data storing schemes for sensors

You can achieve your goal by using Gns 3 simulation and MATLAP

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 Vicky,

There exist many Research Areas Topics for Wireless Networking, such as:

2- For Communication Electronics (Physical layer) researchers:

Yes foreign adjucators are very usual for thesis examination . But I think that you should approach through your Ph.D asupervisors / guide . If the name they suggest are also present in RG very well !

Dear Salar J. Rashid ,

welcome!

The college Anatol Badach brought a figure demonstrating the definition of the software defined networks.

Software defined network is a technology of implementing the network.

It is so that the hardware physical layer devices are substituted by programmable devices such as field programmable gate arrays and digital signal processing in addition to special processors as well as general purpose processor.

The technology started with the socalled software defined radio SDR and then extended to SDWN.

This technology adopts very well to the rapid advancements in the communication networks. While the satdards can be changed and modified, the signal processing platform remains the same.

It is a change in the building methodology of the communication devices and Networks.

As pointed out by Alexandros-Apostolos A. Boulogeorgos and Emil Björnson , IRS can enhance PLS. I attended a conference recently where we discussed the same concept.

Yes, that might be possible. For example, a system might support grant-based (conventional random access followed by scheduling) and grant-free access (opportunistic data transmission without formal scheduling).

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

Dear Mabrouk Atrouche

welcome!

The multiple accessing techniques can be classified into orthogonal and nonorthogonal ones. The orthogonal techniques has theoretically zero interference if they perfectly orthogonal. In case of NOMA the signals are assigned different powers with the weak channel having the larger power.

The channel must be strictly known. Successive interference cancellation is use to determine the signal with highest power with all other signals considered as noise. So, it may be that the interference level is greater than the orthogonal methods. According to the Shannon when the noise increases keeping the signal level the same the spectral density will be smaller.

Fortunately, the matter is not the nonorthogonal versus the orthogonal but the nonorthogonal add one degree of freedom to the multiple accessing technique. Then by exploiting the NOMA one can add additional resources to the available resources. However these resources are limited by method of the detection and the accurate determination of the channel characteristics. Practically the number of power levels are limited because of such detection method. May be the practical number of levels is not greater than 2.

The most convinced platform is the matlab/simulink. You can start by a recent publication on the application of NOMA with MIMO systems as hinted by Emil Björnson

Best wishes

you can use :

It depends on the power allocation algorithm.

TOSSIM is simple and efficient simulator which is based on nesC (Network Embedded Systems

GLomoSIM

UWSIM

H matrix always includes only the complex channel coefficients between transmitter and receiver antennas. Channel models (spatial, stochastic, or deterministic) try to estimate that matrix.

CSI, on the other hand, is the set of information that the receiver calculates using that real H matrix coefficients. It measures SNR, determines the correct precoder matrix, rank, layer, etc. based on the network's algorithm, and reports to the transmitter with their corresponding indicators in a CSI reporting.

DCI's CRC will be scrambled with C-RNTI. So it is not possible for UE B to decode other UE's DCI. DCI's scrambled by all UE's reside in Common Search Space. UE Specific Search space contains DCI's belong to particular UE.

I also do not know anything about LPWAN

See my paper: Article Controller selection in software defined networks using best...

Video transmission over wireless networks is considered the most interesting application in our daily life nowadays. This kind of application needs large bandwidth, efficient routing protocols, and content delivery methods to provide smooth video playback to the receivers. I hope you will benefit from this research paper

https://www.ripublication.com/ijeer17/ijeerv9n2_06.pdf

I think hybrid system RF/FSO consider a good option.

Nice Dear C K Gomathy

Nice Contribution C K Gomathy

Could you check my papers, reply to your question Vishaka Basnayake

Hello Vishaka Basnayake , thanks. On researchgate we tend to click "recommend" on the answer of use, it helps people see what helps and what helps less.

Keep me posted on your investigation... You have an interesting question indeed

Dear Ait,

welcome!

The proposal which i hinted in my second post will enable you to measure the delay time between the master node and slave nodes. The basic idea is to use signal like the GPS one to estimate the transmission delay.

You have a specific problem and it needs investigation to concept the system and implement it within the scope of the existing systems.

Best wishes

Hello Abdulaziz M. Ghaleb

You can check my works here:

and here:

Best regards

It gets a bit messy algebraically, but I recommend that you transform your three random variables (d_1, d_2, theta) into three new variables (r, r_c, phi_1). the variable "r" is computed using the Law of Cosines, r_c is just d_2 and phi_1 is the angle formed between r and d_2. Using the Law of Sines, we have

d_1 / sin(phi_1) = d_2 / sin(phi_2).

phi_2 is the angle between r and d_1.

Realizing that phi_2 = pi - theta - phi_1, we can eliminate phi_2 from the Law of Sines and after some messy manipulation, find phi_1 as a function of d_1, d_2 and theta.

You then construct the Jacobian matrix d(r, rc, phi_1)/d(d_1, d_2, theta). The transformed PDF is given by

p(r, rc, phi_1) = p(d_1, d_2, theta) * det(J)^{-1}

where det(J) is the determinant of the Jacobian J.

The PDF for r requires you to integrate out the rc, phi_1 variables:

p(r) = int(p(r, rc, phi_1)*det(J)^{-1} d.rc d.phi_1)

Hope this helps,

Cheers!

Thank you sir

hello, dear Vishaka Basnayake,

I studied your question.

I think your problem with direct call flow between D2D initiate in a mobile cellular wireless network.

please see an attached link, maybe it will be useful for this mean.

thanks

Hello dear please see below-attached link: please click on Recommend on my reply. Thanks

Read the documents produced by ITU-T-FG-NET2030 (Networks by 2030). Several use cases refer to AI for the management of advanced network features.

Another source is ETSI-ISG-NFV (network function virtualisation) where AI might help manage complexity beyond human (control layer).

The emergency services and first respondents definitely archive their data. They are the ones to contact, in every country/location.

Dear Balaji,

As the colleagues hinted this is the performance characteristics which you have to obtain to judge the effectiveness of the channel estimation algorithm.

It would be also useful if you use other estimation algorithms for sake of comparison and getting confidence in your results.

May be an other important performance parameters is to determine the bit error rate versus the S/N ratio as this will be the ultimate goal of the estimation accuracy.

Best wishes

Enter the settings option to set again the previois data of the router or reboot the router again.

The documents are included in the release package.

https://www.gnuradio.org/news/2017-03-27-gnu-radio-release-3-7-11-and-3-7-10-2/

As said by Zahed Hossain you should not select THz frequencies for wireless communication that have high water vapor absorption. In addition to wise selection of THz frequencies and high gain antennas you can overcome high pathloss penality by beamforming with ultra-massive MIMO antennas.

If the eavesdropper is passive, it will be hard if not impossible to detect it.

When a signal is transmitted, it will arrive to many wireless receivers (e.g., mobile phones) in the surroundings. These will typically disregard the signals, but if they decide to actually decode the signal, we can't detect it.

Interference occurs whenever two rf signal with the same frequency exist at the same time in the same space. In fact the interference is an important issue in wireless communications. The major cause is that the electromagnetic waves are spreading to fill the space in which they propagate. Therefore there are strict frequency allocation and division among the different services. There are licensed bands and unlicensed bands such as the ISM bands. If your system is working in ISM band it will be more subjected to interference.

There is also activities which may produce electromagnetic switching such as power switching stations for the underground trains.

Nowadays there is the connective radio which has the capability to sense the existing active frequencies and choose a vacancy to transmit its signals.

Radio sensing is becoming an important task in wireless communication to detect the radio activities in a specific location.

Best wishes

Deadline extended to July 15...Hurry!!Papers invited for IEEE tencon 2019.Special session-Artificial Intelligence for wireless Networks.

Most of the software packages published so far covers special scenarios which make the work for research is strict. From my experience I found it is easier to propose the scenario and write the mat lab code which enables you to make the necessary changes. You can track my work through the papers attached.

Prof. S. EL-Rabaie

May be a late answer but the attached file has some code and documentation is available in the pdf file at https://tetcos.com/pdf/v11.1/Primary-User-Emulation-PUE-Attack-Cognitive-Radio-v11.1.pdf

hi Narula

Wireless Network vs Wired Network: Advantages and Disadvantages

https://turbofuture.com/computers/Wireless-Network-vs-Wired-Network-Advantages-and-Disadvantages

Hello All friends , I have qustion please i have 10 nodes in my TCL script , I want to make node neighbor for ever node 3 how made that please ,

At present strong-AI is not yet invented, in fact it may be 10-more-years before the theory is fully developed so that practical applications in technology are possible. Consequently I don't see any possible applications to improve 5G, currently, and will likely be at least 10-years in future. By that time, 5G will be obsolete, and we will have moved to more advanced systems.

Hi Aneek Ghosh ,

Both the formulas are correct. Note that

So when you write

y = sqrt(P) * h * X + sqrt(N0/2).* (randn(1,1) + 1i * randn(1,1 )),

this means that

Hence if you calculate the SNR for

y = sqrt(P) * h * X + sqrt(N0/2).* (randn(1,1) + 1i * randn(1,1 ))

you have

SNR = signal power / noise power

= power of (sqrt(P) * h * X) / power of (sqrt(N0/2).* (randn(1,1) + 1i * randn(1,1 )))

= P / N0,

because "h" is simulated in such a manner that E(|h|^2) = 1, and E(|X|^2) = 1. Note that this is the average SNR (the instantaneous SNR will be different because |h|^2 is not equal to 1).

Now in your equation

y1=sqrt(p1).*h_sr.*s1+sqrt(noise_p1).*n_sr,

I presume that "n_sr" is a zero-mean, unit-variance complex Gaussian process. So

noise_p1=p./SNR_lin = p./(p./N0) = N0

is the same as the other equation.

Hope this answers your query.

you can search the Matlab Community (File Exchange) or request from 5gnow project

Incinga (https://www.icinga.com/products/)

how can i generate PDR vs distance graph in mixim omnet++ i have scalar and vector files also Atta ur Rehman Khan Pankhuri Singh

I want also to calculate throughput and delay for 802.15.4 please any one here provide me the suggestions how to do this.

There are some errors in your formulations:

1. While calculating the TL, in the (absorption^d) expression, d should be km instead of meters.

2. Noise PDF can be approximated as 50-18*log10(f) where f in kHz.

3. Acoustic Power calculation is wrong due to the misleading usage of dB and ordinary scale.

4.PWreception depends on the modem platform that you are using. For WHOI Micromodem, PWreception is 1-3 Watts.

I suggest you to check the following two papers.

Dear Avinash Avuthu ,

I think following link will give you an idea to develop your own MAC design and implementation using NS-3. I hope surely this link will provide you an answer

Area throughput is one of the best metric describing the efficiency of overall deployment.

As such, it depends upon what you are looking for, I mean, whether you are looking for energy efficiency or spectral efficiency or in terms of implementation complexity as these are the typical trade-offs involved in designing practical wireless systems.