Mmwave massive mimo: a paradigm for 5g pdf download

As IoT devices are connected to the internet, broad-scale distributed denial of service DDoS attacks could be more common. This large-scale DDoS attack will serve as an enabler in a 6G IoT system that can lead to security, privacy, and trust issues in the network. This is therefore an open research challenge for 6G networks, too.

Technology has a great impact on the lifestyle of human beings. Wireless technologies have revolutionized businesses, living standards, infrastructure, and many other aspects of human life. Mankind is in a constant struggle to find elegant solutions to various problems and is in search of new avenues to progress. This desire of mankind has evolved wireless communication from 1G to 5G. However, this development has not stopped here. The researchers around the world are working hard for the development of 6G communication network, which is expected to be rolled out by In this paper, we covered various aspects of 6G wireless networks with different perspectives.

Furthermore, a way out is discussed how these potential technologies will meet the KPI requirements for these systems. Finally, the opportunities and research challenges such as hardware complexity, variable radio resource allocation, pre-emptive scheduling, power efficiency, the coexistence of multiple RATs, and security, privacy and trust issues for these technologies on the way to the commercialization of next-generation communication networks are presented. Google Scholar. Wiley, New Jersey.

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You can also search for this author in PubMed Google Scholar. RG presented the case study, findings and discussion. MSH has carried out thorough oversight of this work. The final manuscript was read and accepted by all contributors. All authors read and approved the final manuscript. Correspondence to Haejoon Jung or M. Shamim Hossain. Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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Reprints and Permissions. Akhtar, M. The shift to 6G communications: vision and requirements. Download citation. Received : 08 September Accepted : 05 December Published : 21 December Anyone you share the following link with will be able to read this content:.

Sorry, a shareable link is not currently available for this article. Provided by the Springer Nature SharedIt content-sharing initiative. Skip to main content. Search all SpringerOpen articles Search. Download PDF. Abstract The sixth-generation 6G wireless communication network is expected to integrate the terrestrial, aerial, and maritime communications into a robust network which would be more reliable, fast, and can support a massive number of devices with ultra-low latency requirements.

Introduction Next-generation communication systems aim to achieve high spectral and energy efficiency, low latency, and massive connectivity because of extensive growth in the number of Internet-of-Things IoT devices. Vision and literature survey Currently, there is little information about the standards of 6G.

Full size image. Taxonomy of the paper. Network dimensions In this section, we give an overview of the network dimensions of 6G networks. Softwarization Main driving force behind the development of B5G and 6G networks is to provide services such as self-organization, configurability, programmability, flexibility, and heterogeneous use-cases. Virtualization Network function virtualization enables the software functions to be performed in the virtual machines and allows the access of common shared physical resources such as storage, networking, and computations.

Slicing One of the key network abilities that will allow us to build a flexible network on top of the common physical infrastructure is network slicing. A comparative analysis between 5G and 6G network architecture. Potential technologies Based on the vision of 6G and its network architecture, we now elaborate on the key enabling technologies for 6G wireless networks in this section.

Quantum communication and quantum ML Quantum technology uses the properties of quantum mechanics, such as the interaction of molecules, atoms, and even photons and electrons, to create devices and systems such as ultra-accurate clocks, medical imaging, and quantum computers. Blockchain Blockchain is bringing the revolution to some of the huge industries such as finance, supply chain management, banking, and international remittance [ 77 ].

Internal network operations Smart contracts in Ethereum, which is the second generation of blockchain technologies, have revolutionized the automation system in various applications. Blockchain-based digital services Telecommunication operators can generate new revenues by proving customers with new blockchain-based services such as mobile games, digital asset transactions, music, payments, and other services.

Digital identity verification Digital identity verification already costs the government millions of dollars every year. Ecosystem for efficient cooperation Next-generation wireless systems aim to provide a variety of new digital services. Tactile internet With the evolution of mobile Internet, sharing of data, videos are enabled on mobile devices. Communication in space and deep sea Space tourism has the immense potential for the next decade both in economic and scientific perspective [ ].

Robotics and automated vehicles for beyond industry 4. Peak data rate One of the use cases for next-generation wireless communication is eMBB, which simply implies high data rates.

Mobility More mobility robustness is also required in next-generation communication systems. Energy efficient network The next-generation wireless communication system will consist of massive self-organizing and self-healing robots. Hardware complexity and increase in chip size Next-generation mobile communication will integrate multiple communication devices ranging from sensors to HD video transmission devices or communication with high-speed trains and airplanes.

Variable radio resource allocation With variable QoS requirements, a variable radio resource has to be assigned to the user. Although this is not a new business opportunity, the growth of data demand persists with increasing uptake of multimedia contents e.

As a proven business case, enhanced mobile broadband is the priority use case in 5G deployment. Although connectivity yields low margin, it offers a stable revenue stream that will be able to bankroll the deployment of 5G to suit 5G use cases other than mobile broadband.

Furthermore, as mobile broadband is the key value proposition that is offered by the operator, excelling in enhanced mobile broadband will differentiate the early adopter from its competitors.

Therefore, although being a traditional business case, enhanced mobile broadband will be an integral part of 5G commercialisation. The early deployments will be adopting either non-standalone option 3 or standalone option 2 as the standardisation of these two options has already been completed.

Non-standalone option 3 is where the radio access network is composed of eNBs eNode Bs as the master node and gNBs gNode Bs as the secondary node see the left side of Figure 2. The NSA option 3, as it leverages existing 4G deployment, can be brought to market quickly with minor modification to the 4G network.

This option also supports legacy 4G devices and the 5G devices only need to support NR New Radio protocols so the device can also be developed quickly. On the other hand, NSA option 3 does not introduce 5GC and therefore may not be optimised for new 5G use cases beyond mobile broadband. SA option 2 has no impact on LTE radio and can fully support all 5G use cases by enabling network slicing via cloud-native service-based architecture.

On the other hand, this option requires both NR and 5GC, making time-to-market slower and deployment cost higher than that of NSA option 3. Furthermore, the devices would need to support NR and core network protocols so it would take more time to develop devices.

Availability of a suitable amount of spectrum is the most important prerequisite to launch 5G. While globally harmonised bands will be allocated formally at WRC, several countries and regions have already identified candidate bands and in some cases already allocated them.

These bands have been identified in many countries as primary bands for 5G and as Figure 3 shows, global harmonisation seems feasible in the lower part of such bands thus unlocking economies of scale in devices. Another band that has been gaining popularity for use in 5G is the so-called millimetre wave band that includes spectrum spanning from 24GHz to The very fast attenuation of the radio signal at these frequencies has cast doubts on the potential of using this spectrum to provide wide area coverage especially in the uplink direction where MIMO and beamforming may not be as effective as in the downlink, however field trials and simulations indicate that there is a key role to be played by mmWave in 5G.

The main attractiveness of mmWave, as Figure 4 shows, is the availability of very large bandwidth and the strong potential for global harmonization. Figure 3: Spectrum in the S and C bands earmarked for use in 5G in selected countries. Figure 4: Spectrum allocation in mmWave for selected countries. It should be observed that the ITU IMT requirements, especially with regards to maximum throughput are based on the assumption of using MHz channels.

From an analysis of the results of recent spectrum auctions in the 3. Hungary , United Kingdom operators will have that amount of spectrum available. The consequence is that the actual throughput that can be extracted from the 5G system will be inferior to the IMT requirement. It is important that operators are in the position to deliver 5G at a lower cost per Gbyte, therefore allocation of at least MHz is vital for such use cases.

Thanks to the possibility of utilising advanced antenna techniques such as MIMO and beamforming, simulations have shown the feasibility of matching the downlink coverage provided by LTE MHz with 5G radio base stations operating at 3. To overcome this problem it has been proposed to utilise lower band spectrum such as the MHz spectrum for the uplink data.

To optimize the coverage further, both NR uplink control and user data channels can be transmitted on the FDD-band. Both these techniques allow the uplink transmission to be switched between the FDD-band and the 3.

This provides opportunity to aggregate NR bandwidth as well as better operation of the NR uplink. This enhancement allows a device to consume radio resources provided by both 4G and 5G. There are a few variants for data bearer configuration within Option 3.

As service continuity after the loss of 5G radio coverage is more graceful in this variant, it also minimizes excessive signalling traffic between RAN and core. This traffic is huge. In the Option 3a networking mode, there is only control plane traffic in the X2 interface. So the X2 traffic is very small. From the perspective of the impact on the existing network, the Option 3x is relatively small and has become the mainstream choice for NSA networking.

By using 4G as the anchor point of the control plane, it can meet good service continuity and support rapid network construction in the initial stage of 5G deployment. To support NSA, the 4G core network needs to do a small software upgrade to add or expand several parameters. But the first generation of mmWave systems will probably be analog or some hybrid between analog and digital, since these approaches are quicker to implement.

Thanks for your great blog. Below are my questions. Closed loop spatial multiplexing uses singular value Decomposition to separate multi stream. Open loop Diversity use uncorrelated multi path while Beamforming focus energy This means correlated path.

They have same purpose but use different method. Some of these things are explained in that book. Why should the number of RF chains be greater than the number of data streams? If more than one RF chain are connected to the same antenna, you need circuitry to add the analog signals together. This leads to power losses, which is why the partially connected method only connects one RF chain per antenna.

If you want to give each data stream a unique beam, which is needed to separate the signals at the receivers, you need to have more RF chains than streams. Dear Emil, How many users can fall into a beam? Or will one user be allocated a beam? How can we explain this with respect to analog, digital and hybrid beamforming? So these 10 beams can be allocated to how many users?

With 10 RF chains, you can generate up to 10 orthogonal non-overlapping beams. Alternatively, you can create any number of partially overlapping beams. So in principle you can serve any number of users with different beams, but since the beams will be overlapping the interference will be large when you have more users than RF chains. Will the beamforming vector be different for two users if they are served by one beam? I really enjoyed this website. I have been reading about Massive MIMO for my master thesis, and I always had some shadows in my mind, that were taken for granted in many papers as being simple.

Or just totally 10 users? This question comes into my mind, since I know that many companies, have 3 or 4 RF chains in each RAU, and this would be a really low number, if it means the total number of users that might be served.

I have also another question. Having ZF means that we are doing the digital precoding? Yes, with 10 RF chains you can send 10 separate beams. With ZF, you can create as many spatial nulls zeros as you have RF chains, using digital processing. Hi nice explanation… I just want to clarify some doubts regarding precoding and digital beam forming. I know that there are differences between analog and digital beamforming but the confusion lies in digital part.

I was going through some of LTE specs and I found that precoding exists for some of the Transmission modes. Thanks in advance…. When we describe 3D beam-forming, it is often graphed as an bunch of antennas pointing different beams both horizontally and vertically to the users in a high rise building for example. When I see a graph like this, it intuitively leads me to link this to analog beamforming towards users with LOS signal.

But is 3D-beamforming more processed in the digital domain? If so, do the beams actually appear to be physical beams pointing to specific directions? Another questions, do TM7 and TM8 correspond to analog or digital beamforming? Many thanks. The illustration that you mention is correct for LOS signaling.

But keep in mind that analog beamforming can only create one beam at a time, while digital beamforming can be used to create many simultaneous beams; for example, towards users at different floors in different high rise buildings.

My thought is that transmitting signal through precoding is still omni-directional signal. Not like analog beamforming create a directional beam. Is it correct? In digital or analog beamforming, if the antenna spacing exceeds a certain spacing depending on the wavelength , grating lobes are observed.

Grating lobes represent wasted power and increased interference. When you increase the antenna spacing, the main lobe becomes narrower but grating lobes appear.

For example, it is common to design cellular antenna panels so that their grating lobes are going upwards, towards the sky, where there might not be any users and therefore no harm from the interference. Generally speaking, the best way to not waste power on interference is to have more antennas so that one can get narrow beams without grating lobes. Sections 7. Can we create multiple directional beams, with different beamwidths in order to improve coverage area in Massive MIMO fixed scenarios, i.

Is it possible to create multiple directional beams with different beamwidths to cover an area. What would change in such conditions with respect to antennae configuration? The beamwidth is generally determined by the aperture of the array, so a Massive MIMO array will have narrower beamwidths than a small array. But there are anyway methods to create wider beams for control signaling and other things that are transmitted without knowing where the receiver will be.

Prof Emil, 1. Can you guide me, in future how can I start working on hybrid pre-coding security with any new idea? Artificial noise is a Gaussian noise-like signal that the transmitter generates and sends in all directions, except the ones of the desired users. The chance is therefore high that the eavesdropper will be receive the artificial noise in addition to the desired signals.

The artificial noise reduces the SNR at the eavesdropper, making it harder for it to decode the signals. Thank you very much…please answer an additional question in connection to my previous question, how transmitter will know about desired user? There is a standard access procedure in wireless networks, where particular time-frequency resources are reserved for contacting the base station or inactive users terminals.

Then the base station schedule users on particular time-frequency resources, so it knows exactly which users are active and when. That testbed is overdesigned, in the sense that it has much higher computational capabilities than needed, but the paper describes what the main building blocks are. Dear Emil I have a question which confused me for a long time. As I know, the analog beamforming need high mutual antenna correlation.

So the antenna element spacing of antenna array should be lower than one wavelength. Normally 0. But for digital beamforming, it need low mutual antenna correlation and the antenna element spacing of antenna array should be higher than one wavelength. Analog beamforming is a special case of digital beamforming where the there are strict requirements on which beamforming coefficients that can be selected.

However, the basic physics is the same in both cases: You need an antenna spacing of 0. In a nutshell, the total aperture of the array determines the beamwidth of the beamforming while the antenna spacing determines whether or not there will be grating lobes. Section 7. I am going to prepare a paper for my MSc degree on 5G wireless communication using hybrid beamforming design.

What will you advice me to have knowledge of this title? There is a huge amount of previous work on hybrid beamforming design, thus I think it is hard to identify something new that you can work on in a Master degree. If you anyway want to do it, I recommend you to read recent survey papers on the topic and look for open problems that are mentioned in those papers. Very nice post! Yes, spatial coding might be more descriptive, but it also makes the list of terms that mean the same thing even longer….

Reading through the specs is not very clear what the differences are but I think I understood that they use Precoding when talking about multiplexing different data streams layers for the same user while Beamforming when talking about creating multiple beams each one targeting a given user.

Is this reasonable in your opinion? I think that, in most cases, beamforming is a simple method than precoding maybe even a special case. Just to add a bit of high level information as per my understanding for above query — precoding definition in ORAN and 3GPP is similar. In layman terms, considering 2 antenna transmission for SU-MIMO, if two symbols mapped to two different antennas and to be transmitted at same time T have same complex values, then the waveform generated will have similar characteristics.

Receiver will not be able to distinguish between both these waveforms. Therefore general precoding is a step to change the phase of symbols to be transmitted at time T, so that none of symbols have same complex value and waveform characteristics.

This way receiver should be able to distinguish and recover both streams. Beamforming will be special case where phase is changed in such a way that transmission from different antennas combine constructively in a specific direction.

Yes, in fact, it is the best way to achieve an array gain because you can always fully adapt the beamforming to the channel, so you get the maximum possible array gain. Great blog. What research has been done on the in building channel models i. What are the channel limits for MU in these geometries which may result in diminishing returns on spectral efficiency from the addition spatial multiplexing layers transceivers per small cell gNB?

So concise, so intense, I always learn from this blog! All students in the world should be aware of this blog! Hi Emil, 1 If we use digital beamforming for different users, we get capacity gain. Will there be any beamforming gain considering a single user and how can it be compared to analog beamforming gain with same signal to all antennas?

Digital beamforming can do everything that analog beamforming can do, but also much more. A user that stands right in front of the antenna will get exactly the same beamforming gain with digital and analog beamforming, but if the user is located at other places with many reflections and scattering , then digital beamforming give a stronger ability to tune the transmission to the channel. Analog beamforming is unable to adapt to that, while digital beamforming can fully adapt to the frequency-variations.

Hybrid beamforming lies somewhere in between. The hybrid approach is defining a number of analog beams and then allow for frequency-variations within those beams. I recommend you to consult some recent book on the NR standard.

This article gives me a feeling that digital beamforming is much more flexible than analog beamforming. It can do more tasks that analog beamforming cannot. Then what is the meaning of using analog or even hybrid beamforming?

Is it because their implementation is easier than digital at this moment? Will they all be replaced by digital beamforming in the future? Yes, your evaluation is correct. Analog and some sorts of hybrid beamforming are easier to implement at millimeter-wave frequencies. There can also be deployment situations where you need a large aperture to get a strong beamforming gain, but as much flexibility particularly not in the elevation angle since the users are confined into a limited angular interval.

I think we will reach a point where digital beamforming is used at most millimeter wave frequencies, but we might eventually hit a wall when going up in frequency: It becomes harder to implement digital beamforming and the flexibility is less needed since the coverage area is small. A nice post. To mention that wireless is the base for all of the up-to-date smart devices like Smart Bands, Smart Phones, and so on.

The voltage across a discharging capacitor is. For performance reasons, some things are implemented in native code, or use external libraries. Each program is self-contained and includes lecture sessions covering theoretical concepts followed by intensive PYTHON and R-based projects for 5G technology.

Matlab Wireless Network Projects deals with our connoisseurs provides supervision based on research project subjects and Jump to navigationJump to search. This is more flexible that you may call the polar coding routines from any working directory.

The program should not prompt for any additional information and should be self-contained. Here, we are looking at the resource grid for downlink 5G waveform with a 30 kilohertz sub-carrier spacing.

NA MATLAB is available directly from Keysight to extend the capabilities of Keysight signal analyzers and generators to make custom measurements, analyze and visualize data, create arbitrary waveforms, control instruments, and build test systems. This can present many challenges to the developer since there is little insight or understanding of the underlying code. You can use these functions as golden reference for design verification. However, low-band frequencies are useful for providing 5G access to more devices from a single tower and to areas that don't have direct line-of-sight to a 5G cell, such as rural communities.

To learn more, explore the 5G Toolbox product page. Find detailed answers to questions about coding, structures, functions, applications and libraries. This enables you to accelerate simulation, access C source code directly, or use it as a standalone executable. The code provided here originally demonstrated the main algorithms from Rasmussen and Williams: Gaussian Processes for Machine Learning.

However, regardless of numerology the length of one radio frame and the length of oneError Correction Coding in a Digital Communication System.

Create and optimize IP for 5G products.