Very nice video. Thank you. Do you have any point of view about the resource allocation problem in mmWave mMIMO small base stations (5G)? I get your book about this theme, and I'll read that.
There are many types of resource allocation problems to consider, including scheduling, multiuser beamforming selection, power allocation. You can find some possible solutions in the academic literature. These things are not standardized so we cannot know what kind of solutions the companies are using. My books can give you a sense of some of the theory for how to approach these problems. I’m sure there tutorial papers on specific topics as well.
thank professor for your brief explanation in optimization transmit power. i would like to ask which constant variable optimized in cell free massive MIMO other than mentioned in this video?
I haven't seen any other "new" variables being optimized in the cell-free Massive MIMO area. Apart from what is said in this video, one can optimize which subsets of access points that are serving which users. This is not a truly new variable but is still important. Here is a paper about it: arxiv.org/pdf/2002.01504
No, NOMA is essentially an outdated technology that we don't believe in. Episode 11 of our podcast is discussing that: ma-mimo.ellintech.se/2021/03/10/episode-11-non-orthogonal-multiple-access/ You can also read the following blog post: ma-mimo.ellintech.se/2021/04/15/is-there-a-future-for-noma/
sir,my research area is energy harvesing by RIS .now i found two problem are maximise harvested power and SNR at recevier.optimize the harvested power means which factor is i considered for getting high value. transmission power or rectifier output
There are many possible ways to formulate optimization problems, and multiple possible metrics. The point that we want to make with this video is that we always need to make a conscious choice of what problem we want to solve and have a (subjective) motivation for it. If you choose between maximizing two different metrics, think about what would be the benefit of the two different problems and then make up your mind about which option you prefer!
thank you sir. nice explanation. what are the factors are considered for optimization of power consumption model for energy harvesting. send your video link sir
We don’t have a video on that topic. The important thing is to build a model that depends on the variables that you will consider and then validate it theoretically or experimentally.
Yes, this is a real-world problem when dimensioning cellular network deployments. In this case, we are finding the desirable base station equipment (antennas per site) and figure out how many users should be served simultaneously to achieve maximum energy efficiency.
You can also compare the cost for one Site with a high numbers of Antennas and the cost for a Site with less Antennas. On one place an Massive MiMo can be more cost efficent than an small Cell aproch. In an other place it van be different.
Eduard Walz Yea, that is essentially what we are doing by letting both the number of antennas and the base stations per area unit be optimization variables.
At what minute was that said? I would guess it means the following: If we need a certain SNR at the receiver, then it is proportional to "channel gain * transmit power". If we can improve the channel gain, then we cut back on transmit power.
Hello Professor, Kindly give some idea about transmit power minimization using Multi-antenna on UAV ? What factors to consider why deploying beamforming in UAV enabled commmunication
When formulating an optimization problem, you need to figure out what function to optimize, what variables to consider, and what the constraints are. I understand that you want to minimize the function “total transmit power” and that your variables are “the individual transmit power values”. The remaining question is what your constraints are, because you need something related to the communication performance, otherwise the optimal solution will be to use zero power. Since you mention UAV-enabled communication, you need to determine what difference the UAVs make in the system compared to a conventional network without UAVs. Is it only the channel model that differs or something else?
@UCb9xzjXWJYW-MOU4Q6TZbVg Right, but many beamforming algorithms can be applied to any set of channel vectors. For example the algorithms described in my book “optimal resource allocation…” are applicable for arbitrary vectors, but the communication performance (rate) will depend on what the channel conditions to use. There are also concepts such as beam tracking and angle-of-arrival based channel estimation in the mmWave literature that only works if the channels have the right properties.
Thanks, Prof. Emil for your great explanation!
You are an awesome person, great and wonderful work
A very nice video. Thank you very much.
thanks for a great lecture
Very nice video. Thank you. Do you have any point of view about the resource allocation problem in mmWave mMIMO small base stations (5G)? I get your book about this theme, and I'll read that.
There are many types of resource allocation problems to consider, including scheduling, multiuser beamforming selection, power allocation. You can find some possible solutions in the academic literature. These things are not standardized so we cannot know what kind of solutions the companies are using.
My books can give you a sense of some of the theory for how to approach these problems. I’m sure there tutorial papers on specific topics as well.
@@WirelessFuture
can you send the book for resouce allocation and power allocation. I am doing research in this area
thank professor for your brief explanation in optimization transmit power. i would like to ask which constant variable optimized in cell free massive MIMO other than mentioned in this video?
I haven't seen any other "new" variables being optimized in the cell-free Massive MIMO area. Apart from what is said in this video, one can optimize which subsets of access points that are serving which users. This is not a truly new variable but is still important. Here is a paper about it: arxiv.org/pdf/2002.01504
This video is a Gem of a kind.
Thank you professor
Thank you sir for a nice explaination. Do you have other video about spectrum efficiency of NOMA?
No, NOMA is essentially an outdated technology that we don't believe in. Episode 11 of our podcast is discussing that: ma-mimo.ellintech.se/2021/03/10/episode-11-non-orthogonal-multiple-access/
You can also read the following blog post: ma-mimo.ellintech.se/2021/04/15/is-there-a-future-for-noma/
@@WirelessFuture Ok I will read that, thank you
sir,my research area is energy harvesing by RIS .now i found two problem are maximise harvested power and SNR at recevier.optimize the harvested power means which factor is i considered for getting high value. transmission power or rectifier output
There are many possible ways to formulate optimization problems, and multiple possible metrics. The point that we want to make with this video is that we always need to make a conscious choice of what problem we want to solve and have a (subjective) motivation for it. If you choose between maximizing two different metrics, think about what would be the benefit of the two different problems and then make up your mind about which option you prefer!
thank you sir. nice explanation. what are the factors are considered for optimization of power consumption model for energy harvesting. send your video link sir
We don’t have a video on that topic. The important thing is to build a model that depends on the variables that you will consider and then validate it theoretically or experimentally.
Thank you for sharing. However, I have no idea why we need to optimize the number of users and antennas in a cell. Is it a real-world problem?
Yes, this is a real-world problem when dimensioning cellular network deployments. In this case, we are finding the desirable base station equipment (antennas per site) and figure out how many users should be served simultaneously to achieve maximum energy efficiency.
You can also compare the cost for one Site with a high numbers of Antennas and the cost for a Site with less Antennas. On one place an Massive MiMo can be more cost efficent than an small Cell aproch. In an other place it van be different.
Eduard Walz Yea, that is essentially what we are doing by letting both the number of antennas and the base stations per area unit be optimization variables.
What do we mean by maximizing the channel gain in order to minimize the transmitter power PT?
At what minute was that said? I would guess it means the following: If we need a certain SNR at the receiver, then it is proportional to "channel gain * transmit power". If we can improve the channel gain, then we cut back on transmit power.
My sincere apologies
Thanks a lot for answering a question about the topic which was not discussed in this video. This will not be happening again.
Hello Professor, Kindly give some idea about transmit power minimization using Multi-antenna on UAV ? What factors to consider why deploying beamforming in UAV enabled commmunication
When formulating an optimization problem, you need to figure out what function to optimize, what variables to consider, and what the constraints are. I understand that you want to minimize the function “total transmit power” and that your variables are “the individual transmit power values”. The remaining question is what your constraints are, because you need something related to the communication performance, otherwise the optimal solution will be to use zero power.
Since you mention UAV-enabled communication, you need to determine what difference the UAVs make in the system compared to a conventional network without UAVs. Is it only the channel model that differs or something else?
@@WirelessFuture can you please share the link of Book's code for simulation
Thank you. your book is student friendly and easy to read and understand.
@@abidafridi6570 I guess you refer to github.com/emilbjornson/book-resource-allocation All my other code is available under the same profile.
@@WirelessFuture Thank you so much Professor
@UCb9xzjXWJYW-MOU4Q6TZbVg Right, but many beamforming algorithms can be applied to any set of channel vectors. For example the algorithms described in my book “optimal resource allocation…” are applicable for arbitrary vectors, but the communication performance (rate) will depend on what the channel conditions to use. There are also concepts such as beam tracking and angle-of-arrival based channel estimation in the mmWave literature that only works if the channels have the right properties.