Enabling Grant-Free URLLC: An Overview of Principle and Enhancements by Massive MIMO
Summary (4 min read)
A. Background
- Emerging URLLC applications include virtual/augmented reality, public safety, factory automation, and autonomous vehicles, among others [7].
- In 5G NR, a number of advances, including waveform numerology, frame structure, multiple access schemes, and scheduling policy, have been adopted for enabling URLLC [10]–[12].
- Such handshaking ensures that the device has an exclusively reserved channel for contention-free transmission, avoiding any potential collisions in data transmissions.
- Since CF mMIMO reaps all the benefits from mMIMO as well as network MIMO [36], the authors anticipate that CF mMIMO will open up new avenues and advances for GF URLLC.
- Unlike the existing articles, this survey mainly focuses on enabling GF URLLC and addressing its fundamental issues by exploiting mMIMO from the physical and data-link layers perspective.
B. Contributions
- Their three main contributions in this paper are outlined as follows:.
- 1) We develop a comprehensive review of NR specifications and techniques for URLLC, discussing underlying principles and highlighting fundamental issues of enabling URLLC with GF random access.the authors.the authors.
- 2) We review the key phenomena of mMIMO and build several deep insights into how mMIMO can be exploited to address the fundamental issues and enhance the performance of GF URLLC.the authors.the authors.
- In particular, the authors explain the benefits of exploiting preamble-collision information, coded random access, and multi-preamble detection for GF URLLC, which are only achievable via mMIMO.
II. USE CASES OF URLLC
- URLLC use cases set stringent transmission requirements, e.g., 99.999% transmission success rate within 1 ms [40].
- The authors herein focus on the three main real-life 5G business use cases: i) Industry 4.0 smart manufacturing [41], ii) Connected autonomous vehicles [42], and iii) robotic surgeries [43], all of which are now in the deployment phase.
- Since GF random access has been a part of 5G standards, it is worth noting that low delay and time-sensitive network applications (e.g., automated car driving and near real-time robotics) of the three use cases can benefit significantly with the GF URLLC [44].
- Significant trends in such applications are user-specific three-dimensional (3D) video rendering, augmented reality, remote control (e.g. remote robotics, surgery, tactile internet, etc.), wireless communication automation for efficient production facilities, vehicular traffic efficiency/safety, and mobile gaming, among others.
A. Smart Factory and Industrial Automation
- Smart factory as part of industrial automation is one of the key applications demanding URLLC.
- In addition, it is worth noting that missing a deadline can be very costly as the automation systems are always cascaded and characterized by the need to meet their inter- and intra-system deadlines [50].
- Furthermore, ultra-tight synchronization should be considered to be the third axis of URLLC when targeting such critical use cases for industrial automation [46].
- To be specific, the latency requirement for such distributed learning and connections of the ITS entities with the infrastructure backhaul should be lower than 10 ms, along with a reliability of 99.9999% [45].
- Motivated by these, GF random access has been considered and identified as a key enabler for 5G empowered ITS [44].
C. Healthcare and Public Safety
- Health care applications such as robotic telesurgery and tactile Internet spur the need for URLLC.
- They also require patients over VR headsets when taking them through their surgical plan [47].
- Likewise, public safety requires robust and reliable communications in case of natural disasters such as earthquakes, tsunamis, floods and hurricanes [60].
- And [62] reviewed emerging technologies for enabling public safety services, and mMIMO is one of them.
- Based on them, the authors then shed light on the potential of ameliorating the issues and advancing URLLC capabilities with the assistance of mMIMO technology, which can be served as guidelines for underpinning the applications of URLLC.
III. ENABLING URLLC IN NR
- To meet latency and reliability requirements of various URLLC use cases, key enabling techniques in NR physical and medium access control (PHY/MAC) layers have been adopted in 3GPP release 15 and enhanced in 3GPP releases 16 and 17 [11], [49], [64].
- The authors explain several key NR specifications and techniques for URLLC, including flexible frame structure, GF random access, and retransmission schemes.
A. Flexible Frame Structure
- In NR, one of the main specifications adopted for URLLC is a flexible frame structure, which is able to not only reduce latency but also create more retransmission opportunities within a target latency that in turn lead to enhanced reliability [45].
- Since the user-plane, latency1 is one of the dominant components in the latency of URLLC and the transmission time interval (TTI) plays an important role in contributing to the user plane latency, reducing TTI is a key to meet the lowlatency requirement.
- For this reason, NR enables TTI reduction by introducing scalable numerology (subcarrier spacing) and the concept of mini-slots [49].
- Since a larger subcarrier spacing can be employed than that of the baseline of 15 KHz, the duration of slot and orthogonal frequency division multiplexing (OFDM) symbol can be significantly reduced.
- On top of this, the number of OFDM symbols in each TTI does not necessarily equal 14.
B. GF Random Access
- To implement a radio access network for URLLC, handling random access design can be one of the most important/critical portions.
- In the second step, the BS detects the preambles transmitted by active devices and sends responses by issuing a scheduling grant.
- The 4-step random-access procedure requires two round-trip cycles between the devices and the BS, which raises the barriers to meet the stringent latency requirement of URLLC use cases [9].
- In particular, it not only increases the latency but also incurs large control-signaling overhead for small packets [11].
- The contention-free GF transmission can be employed when the number of active devices is small and their access traffic is periodic or deterministic.
C. HARQ Retransmission Schemes for GF URLLC
- The authors briefly discuss HARQ retransmission schemes for URLLC in this subsection.
- Once the device transmits a data packet, the device has to wait for feedback from a BS before any retransmission attempt.
- 2) K-Repetition HARQ Retransmission Scheme: Several research works have provided comprehensive studies on the performance of the three HARQ retransmission schemes in GF URLLC random access [73], [77], [78].
- The analysis approach in [78] does not consider the impact of CSI estimation error on the performance, which makes the analysis result too optimistic.
A. Features of mMIMO
- Thanks to the excessive degrees of freedom created by a large-size antenna array, two prominent features such as channel hardening and favorable propagation can be achieved in mMIMO [23], [86], [87].
- Channel hardening means that the effect of small-scale fading is averaged out, and devices’ channels behave a deterministic like wired channel as the number of antennas approaches infinity [86].
- It is seen that the variance of ‖h1‖ 2 M decays with M and converges towards zero, which indicates that the channel gets more hardened as M increases.
- Favorable propagation means that channels of different devices become orthogonal as M approaches infinity [87], which makes different devices distinguishable in the space domain.
B. Enhancements to GF URLLC
- By taking advantage of these two features, mMIMO is able to spatially separate signals that are simultaneously transmitted by a large number of URLLC devices over the same channel resource in GF random access, which makes it a prominent enabler for massive access [31].
- One of the most significant enhancements to GF URLLC is the high reliability and capacity ensured by mMIMO, thanks to its large array, diversity, and multiplexing gains.
- Since preamble collision in GF URLLC is dominantly detrimental to the transmission reliability, leading to increased latency and need for retransmissions, it is desirable to effectively mitigate it.
- Based on the inferred information, the BS can strategically divide the whole preamble resources into two separate sets to accommodate different groups of devices, i.e., retransmission devices and newly arrived devices.
- MMIMO can be utilized to resolve preamble collision, separate signals of devices effectively, and decode their data, which are beyond the capability of conventional systems.
V. POTENTIAL OF EMERGING CF MMIMO
- In CF mMIMO, instead of gathering all the antennas at the same location, a large number of simple and low-cost access points (APs) employing single or multiple antennas are spatially distributed to serve several devices that share the same channel resource jointly.
- Since CF mMIMO not only captures the benefits of mMIMO but also network MIMO [36], it provides more distinctive features than mMIMO [106]–[109].
- In the following, the authors present its key features and benefits compared to mMIMO.
A. Features of CF mMIMO
- CF mMIMO inherits the features of channel hardening and favorable propagation from mMIMO, although their level may be less than that in mMIMO (particularly channel hardening).
- In CF mMIMO, since APs are geographically distributed, it is highly likely that several neighbouring APs surrounds each device, also known as 1) Macro Diversity.
- To illustrates this feature, the authors present Fig. 13 with an indoor GF URLLC scenario, where URLLC devices perform GF random access to transmit data.
- To avoid boundary effects, the square area is wrapped around.
- To illustrate this feature, the authors present the ratio of channel gain obtained by the Qap APs closest to a device and that by all APs in Table II.
B. Research Directions and Challenges
- The distinctive features of CF mMIMO open up new avenues for resolving preamble collision and suppressing multiuser interference in GF random access, which thus help with the support of URLLC.
- In mMIMO, as explained in Section IV-B3, preamble-collision resolution for GF URLLC could be achieved by coded random access and its variants in the context of HARQ retransmission schemes, which rely on the use of multiple preamble transmissions over multiple transmission TTIs.
- In some URLLC use cases, the traffic pattern of devices could be deterministic and predictable [4].
- To this end, in the resource allocation for fronthaul links, the processing delay has to be taken into account to meet the latency constraints, especially for GF 14 random access.
VI. CONCLUSIONS
- The authors first outlined typical URLLC use cases and requirements and presented an overview of essential enabling techniques and principles of GF URLLC in NR.
- The authors identified and discussed key factors such as preamble collision and multi-user interference that jeopardize transmission reliability within a target latency in GF URLLC.
- Once the authors identified those factors, they then revisited the phenomena of mMIMO, i.e., channel hardening and favorable propagation, and discussed how to enhance the performance of GF URLLC by exploiting mMIMO.
- Finally, the authors shed light on the distinctive features and potential benefits of CF mMIMO over centralized mMIMO and provided a perspective on its potential research directions along with challenges towards enabling GF URLLC.
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Frequently Asked Questions (17)
Q2. What is the key to achieving the maximum mMIMO performance?
It is also important to remark that accurate acquisition of instantaneous CSI is a key to fully exploiting large spatial9 diversity and multiplexing gains of mMIMO.
Q3. How many retransmissions can be achieved in GF URLLC?
Suppose that a URLLC application aims to achieve an error probability of 10−5 and its required latency only allows a maximum K = 4 retransmissions in GF URLLC.
Q4. What are some of the applications that are emerging in the field of URLLC?
Emerging URLLC applications include virtual/augmented reality, public safety, factory automation, and autonomous vehicles, among others [7].
Q5. How can the BS estimate the CSI of preambles?
In order to further improve the spectral efficiency or shorten the latency of coded random access, a superposition of multiple orthogonal preambles [103] can be considered, which can effectively increase the number of active devices whose CSI can be estimated by the BS using SIC.
Q6. What is the main reason why retransmissions are required in random access?
In particular, in random access, retransmissions are required as packet collisions are inevitable due to the nature of uncoordinated transmissions.
Q7. What is the effect of a noisy superposition of multiple channel vectors?
Since the estimated CSI is a noisy superposition of multiple channel vectors of the collided devices, it brings two effects in mMIMO, leading to unsuccessful decoding [89], [94]–[96]: 1) it reduces the coherent array gain of the desired received signal, and 2) it introduces a coherent interference that gets stronger as M grows.
Q8. How many URLLC devices can be served simultaneously?
with target reliability of = 10−5, it is evident that only 1 URLLC device can be served in MIMO with 8 antennas, while the number of URLLC devices that can be served simultaneously increases with M and can reach 55 when M = 128.
Q9. What are the performance limitations for HARQ retransmission schemes in GF random access?
It is important to remark that the performance limitations for the HARQ retransmission schemes in GF random access are fundamentally originated from the multi-user interference as well as preamble collision when multiple devices compete for the same channel resource for uplink transmissions.
Q10. What is the main reason why multiple competing devices can transmit data over the same channel?
In GF URLLC, since multiple competing devices can transmit data over the same channel, it results in potential transmission collision, which is detrimental to the reliability.
Q11. What are the disadvantages of GF URLLC?
it incurs additional latency and undesirable signalling overheads, which hinder achieving the required level of latency constraints for URLLC.
Q12. What is the reason why LTE is not applicable to the uplink URLLC?
Earlier studies on the long-term evolution (LTE) systems to support URLLC [9] reported that LTE is not applicable to meet low-latency requirements.
Q13. What is the main reason for the lack of GF URLLC?
with limited latency budget and wireless resources, their resulting reliability levels and spectral efficiency still needs to be enhanced to meet what is required for emerging URLLC services, particularly when the URLLC access load is relatively high [6].
Q14. How can a fixed N be used to reduce the need for retransmissions?
As observed, with a fixed N , the decoding error probability can be significantly reduced as M grows, which reveals that the need for retransmissions can be dramatically reduced in GF URLLC.
Q15. How long does a TTI take to deliver a data packet?
In Fig. 3, a mini-slot based TTI of 21User-plane latency is the time it takes to successfully deliver a data packet at the radio protocol layer from the transmitter to the receiver.
Q16. What is the difference between GF and the 4-step random access procedure?
Compared to the 4-step random access, GF random access can be more efficient thanks to low signaling overhead when devices have short packets to transmit.
Q17. What is the decoding error probability of receiving q bits of data within a channel?
Based on [14], [91], [92], the decoding error probability of receiving q bits of data within d channel uses can be well approximated by(γ) ≈ E{γ}[ Q ( d log2(1 + γ)− q√V (γ)d)] , (1)where E{x}[·] is the expectation operation over variable x, V (γ) is the channel dispersion that is given by V (γ) =( 1− 1(1+γ)2 ) log22(e).