A Random Access Protocol for Massive MIMO The Adaptive ACB Based Collision Resolution XXX X XXXX XXXX X/XX/$XX 00 ©20XX IEEE A Random Access Protocol for Massive MIMO The Adaptive ACB based Collision[.]
2021 8th NAFOSTED Conference on Information and Computer Science (NICS) A Random Access Protocol for Massive MIMO: The Adaptive ACB based Collision Resolution Ha Tran Huu Wireless Communications Department VNU-UET Hanoi, Vietnam huuha.tran306@gmail.com Duong Chu Huy VNPT Hung Yen Hung Yen, Vietnam duongch.hyn@gmail.com Hung Gia Hoang Computer Engineering Department VNU-UET Hanoi, Vietnam hunghg@vnu.edu.vn Thang Xuan Vu Interdisciplinary Centre for SnT University of Luxembourg Luxembourg thang.vu85@gmail.com In the SUCRe protocol, collisions are completely resolved in a distributed manner on the UE side Specifically, each UE will estimate the ratio of its channel gain to the total channel gain of the UEs that have selected the same preamble If a UE has this ratio greater than 1/2, all other UEs’ ratios will be less than 1/2 This protocol allows only one UE with a ratio greater than 1/2 to retransmit the request while other UEs whose ratios are less than 1/2 must wait for the next turn Note that this collision avoidance policy is handled at the UEs, not at the BS, hence is fully distributed It was shown that the SUCRe protocol achieves good collision resolution when managing less than 104 UEs One drawback of this protocol, however, is that it always gives priority to UEs with large channel gain In addition, when managing a larger machine set (e.g., more than 104 UEs), the protocol’s collision resolution success rate quickly deteriorates because the average number of UEs choosing the same preamble increases significantly Abstract— mMTC (massive Machine Type Communications) is one of the key components in beyond 5G networks for smart manufacturing and the Fourth Industrial Revolution Due to the massive connectivity in mMTC, it is vital to have an efficient random access (RA) protocol In the paper, we propose a new random access technique called the Adaptive ACB (A-ACB) to minimize collisions We show that, in terms of successfully resolved probability, the proposed A-ACB always outperforms the ACBPC protocol while surpassing the SUCRe protocol when the number of collisions per preamble is large In addition, the proposed protocol achieves better fairness than the SUCRe but less than the ACBPC Finally, numerical results are provided to demonstrate the effectiveness of the proposed random access protocol Keywords— random access protocol, massive MIMO, SUCRe, ACBPC, collision resolution I INTRODUCTION The success of massive MIMO techniques [4] in the Fifth Generation (5G) communications for eMBB applications [3] has opened up a new research direction for massive machine type communications (mMTC) and ultra-reliable low-latency communications (URLLC) [5,6] A common approach in developing RA techniques for mMTC applications is to adapt from a reference LTE RA method [9] According to LTEbased protocols, an active user equipment (UE) randomly selects a preamble from a common list and then send it to the base station (BS) to request a connection When two or more UEs collide on the same preamble, the connection requests are dropped and the preamble is not used This leads to a waste of resources because LTE does not resolve but detects collisions only To improve resource utilization, several attempts have been made to address random access collision, especially for mMTC [8,10] The ACBPC protocol, first proposed in [1], aims to overcome the unfairness disadvantage of SUCRe In the first phase of this protocol, the UEs send preambles to the BS with the power inversely proportional to their channel gain Thus, the BS will receive signals with the same power from all active UEs Consequently, the BS can only detect the number of UEs which have chosen the same preamble without detecting the total channel gain The number of UE per preamble is reported back to the UEs, enabling each UE sets an appropriate ACB level to reduce the probability of collision during the retransmission phase When the number of active UEs is reasonably small, ACBPC does not perform as well as SUCRe However, ACBPC outperforms SUCRe when the number of active UEs are large In this paper, we propose a new random access protocol, advisedly referred to as the Adaptive - ACB (A-ACB), which is capable of exploiting the advantages of both ACBPC and SUCRe protocols The key idea behind A-ACB is that rather than using a uniform ACB level for all of the collided UEs, each UE in the collision list will be assigned a theoreticallydifferent individual ACB value based on its location (and thus large-scale channel fading) We show that in comparison with ACBPC, the proposed A-ACB protocol improves the successful resolution probability considerably at the expense of a reduced degree of fairness As compared with SUCRe, Massive MIMO techniques bring a number of great benefits such as bandwidth and energy savings, as well as creating good transmission conditions, namely channel hardening and favorable propagation [5] These properties also facilitate the study of collision resolution problems for mMTC random access, resulting in two prominent schemes: strongest-user collision resolution (SUCRe) [2] and access class barring with power control (ACBPC) [1] XXX-X-XXXX-XXXX-X/XX/$XX.00 ©20XX IEEE 978-1-6654-1001-4/21/$31.00 ©2021 IEEE Vu Trinh Anh* Wireless Communications Department VNU-UET Hanoi, Vietnam Corresponding author: vuta@vnu.edu.vn 45 2021 8th NAFOSTED Conference on Information and Computer Science (NICS) Fig Four phases of random access in SUCRe protocol the proposed A-ACB scheme achieves better fairness as well as higher successful resolution probability when handling a high number of active UEs MIMO uses TDD protocol with the assumption that the channel is reciprocity) The paper is organized as follows Section II provides background on SUCRe and ACBPC protocols Section III presents the proposed protocol with analytical proof Simulation results are presented in Section IV Finally, Section V concludes the paper II • In the third phase, if a UE has the ratio greater than 1/2 (which means all the remaining UEs have their ratios less than 1/2), it will be the obvious winner and retransmit over the allocated RB resources The remaining UEs must wait for the next step, so there is no collision Notice that collision has been resolved in a distributed manner and by hard decisions If only one UE chooses one preamble, its ratio is approximately 1, which makes it always be the winner If, however, no UE has a ratio greater than 1/2 then this preamble will be waste • In the fourth phase, upon receiving retransmission from the winning UE, the BS sends a signal to officially allocate RB of the connection to the UE, completing the random access protocol SUCRE AND ACBPC PROTOCOLS Fig and Fig summarize the four phases of random access in SUCRe [2] and ACBPC [1] protocols Both protocols have been built on Massive MIMO technology, in which uplink signals are processed by the maximal ratio combining (MRC) technique while downlink signals are processed by the maximal ratio transmission (MRT) method The SUCRe protocol consists of four phases as follows: • At the initial request phase (uplink): Active UEs randomly select preamble from the available set and send it to the BS The BS uses the available preamble set to correlate the received signal For each preamble used, the BS will separate the total channel gain of the UEs which have selected it • In the second phase (downlink), the sum of these channel gains is inverted by the precoding and is beamed back to the requested UEs The BS also encloses information about resource block (RB) of the connection to the future winner Due to the separation of the downlink, each UE will be able to estimate the ratio of its channel gain to the total channel gain of all UEs that have the preamble in common (Massive The main advantage of the SUCRe protocol is that it is fully distributed and can achieve a high resolution probability because the probability of two UEs choosing the same preamble is large A drawback of this technique is low degree of fairness: UEs near the BS with strong channel gain are always preferred In addition, the collision resolution of SUCRe decreases sharply when the number of UEs choosing a preamble is large In order to improve fairness, the ACBPC protocol is proposed in [1] and summarized in Fig • At the initial request phase, the UEs, after randomly selecting a preamble, will transmit to the BS with a power equal to the inverse of its channel gain (the gain is detected from phase when the BS is broadcasting) such that the BS will receive signals with the same Fig Four phases of random access in ACBPC protocol 46 2021 8th NAFOSTED Conference on Information and Computer Science (NICS) magnitude Therefore, the BS will not detect the total channel gain as it does in SUCRe protocol, but the number of UEs sharing a preamble that we designate as 𝑘 • In the second phase, the value of 𝑘 is reported back to the relevant UEs by the BS along with RB information • In the third phase, each UE will generate a random number evenly distributed from to If the random number is less than 1/𝑘 , the UE will retransmit the request; otherwise, it will not retransmit According to this protocol, there may still be unexpected situations: no UE has a random number less than 1/𝑘 or there are two or more UEs with a random number less than 1/𝑘 However, equal access is guaranteed, and the collision probability is reduced since each UE is setting up an ACB • Recall that after phase in ACBPC, each UE was notified by the BS on the downlink that there are 𝑘 UEs with the same preamble To reduce the chance of collision, the ACB are set equally to a value 𝑝 (0 < 𝑝 < 1) seeding a random number (uniformly distributed from to 1), if its value less than 𝑝, UE will retransmit the request together with ID and if the random number is larger than 𝑝, it will silent and wait the next random access The probability that there is a retransmission UE without collision when 𝑘 UEs choose the same 𝑝 value is: 𝑘 𝑃𝑝(1 UE repeat) = ( ) 𝑝(1 − 𝑝)𝑘−1 The expression represents the combination of case where only one UE retransmits and k − the remain UEs are silent Since 𝑃𝑝 is a function of 𝑝, take the first derivative respect to 𝑝 yields: 𝑑𝑃𝑝 𝑑𝑝 In the fourth phase, the collision is resolved at the BS If there is no ID collision from UEs, it means that only one UE retransmits The BS will officially allocate resources to this UE = 𝑘(1 − 𝑘𝑝) (1 − 𝑝)(𝑘−2) = (2) 1 Clearly, the solution of (2) is 𝑝 = Substituting 𝑝 = 𝑘 𝑘 into (1), we obtain the maximum collision resolution probability as: The ACBPC protocol is not as efficient as the SUCRe protocol when the average number of UE collisions per preamble is not too large (< 104 ) When the average number of UE collisions per preamble becomes larger (> 104 ), the ACBPC protocol will gradually be more efficient III (1) 1 𝑘−1 𝑘 𝑘 𝑃𝑝,max = 𝑘 (1 − ) 𝑘−1 = (1 − ) 𝑘 , (3) which is the maximum achievable collision resolution probability of the ACBPC protocol [1] For the proposed protocol (A-ACB), the ACBs of the UEs are different because the channel gain to each UE is different Suppose that the values of the ACBs are 𝑝1 , 𝑝2 , , 𝑝𝑘 , they must adhere to the constraint: ∑𝑘𝑖=1 𝑝𝑖 = PROPOSED PROTOCOL The proposed protocol is similar to SUCRe in phase and phase Therefore, after the first two phases, each UE knows the ratio of its channel gain to the total channel gain of all the UEs that share the same preamble The main difference in the proposed A-ACB protocol lies in a novel collision resolution method in phase Note in passing that the sum of ratios of the involved UEs always equals to This simple observation, nonetheless, enables the basis of the proposed method to be formed The collision resolution probability in which only UE retransmits while 𝑘 − remaining UEs are silent is given by: 𝑃𝑝𝑘 (1 UE repeat) = 𝑝1 (1 − 𝑝2 )(1 − 𝑝3 ) … (1 − 𝑝𝑘 ) + 𝑝2 (1 − 𝑝1 )(1 − 𝑝3 ) … (1 − 𝑝𝑘−1 )+ +𝑝𝑘 (1 − 𝑝1 )(1 − 𝑝2 ) … (1 − 𝑝𝑘−1 ) We are going to prove that • In the third phase: Each UE sets its ACB value equal to the ratio it has estimated The collision resolution method is similar to ACBPC, but the ACB for each UE is different in that it varies depending on the UE location (or equivalently, channel gain) rather than being a constant Subsequently, each UE generates a random number uniformly distributed from to If this random number is less than the ACB, it will retransmit Otherwise, it will wait for the next access step The proposed name for this method, adaptive ACB (A-ACB), emphasizes the innovative use of adaptive values for each UE’s ACB • In the fourth phase: BS behaves like the fourth phase of ACBPC protocol If there is no collision ID for UEs, BS will officially allocate connection resources to the winner to the constraints 𝑝1 ,𝑝2 , ,𝑝𝑘 (4) 𝑃𝑝𝑘 = 𝑃𝑝,max , subject 𝑝𝑖 > and ∑𝑘𝑖=1 𝑝𝑖 = 1, (5) where 𝑃𝑝𝑘 is assumed to be a convex function Using the Lagrange multiplier method, let Ω = 𝑃𝑝𝑘 + 𝜆(𝑝1 + 𝑝2 + +𝑝𝑘 ) (6.0) be the Lagrange objective function, the optimal solutions of the optimization problem 𝑃𝑝𝑘 subject to (5) must 𝑝1 ,𝑝2 , ,𝑝𝑘 satisfy the following conditions: Next, we will analyze the performance of the proposed AACB protocol In particular, we present a concrete analytical proof showing that A-ACB always achieves a higher resolution probability than the celebrated ACBPC protocol 𝛿Ω/𝛿𝑝1 = (1 − 𝑝2 )(1 − 𝑝3 ) … (1 − 𝑝𝑘 ) − 𝑝2 (1 − 𝑝3 ) … (1 − 𝑝𝑘 ) − − 𝑝𝑘 (1 − 𝑝2 )(1 − 𝑝3 ) … (1 − 𝑝𝑘−1 ) + 𝜆 (6.1) 𝛿Ω/𝛿𝑝2 = (1 − 𝑝1 )(1 − 𝑝3 ) … (1 − 𝑝𝑘 ) − 𝑝1 (1 − 𝑝3 ) … (1 − 𝑝𝑘 ) − − 𝑝𝑘 (1 − 𝑝1 )(1 − 𝑝3 ) … (1 − 𝑝𝑘−1 ) + 𝜆 (6.2) … 47 2021 8th NAFOSTED Conference on Information and Computer Science (NICS) 𝛿Ω/𝛿𝑝𝑘 = (1 − 𝑝1 )(1 − 𝑝3 ) … (1 − 𝑝𝑘−1 ) − 𝑝1 (1 − 𝑝2 ) … (1 − 𝑝𝑘−1 ) − − 𝑝𝑘−1 (1 − 𝑝1 )(1 − 𝑝2 ) … (1 − 𝑝𝑘−2 ) + 𝜆 compare the success collision resolution rate of the A-ACB protocol to those of the SUCRe and ACBPC for different numbers of active UEs choosing the same preamble Secondly, we investigate the average number of access attempts made by each UE through A-ACB and SUCRe protocols in a crowded network (6.k) (6.k+1) 𝑝1 + 𝑝2 + ⋯ + 𝑝𝑘 = Subtracting (6.2) from (6.1), we obtain A Success resolution probability for varying number of active UEs per preamble (𝑝1 − 𝑝2 )(1 − 𝑝3 ) … (1 − 𝑝𝑘 ) + (𝑝1 − 𝑝2 )(1 − 𝑝3 ) … (1 − 𝑝𝑘 )+ −(𝑝1 − 𝑝2 )𝑝𝑘 (1 − 𝑝3 ) … (1 − 𝑝𝑘−1 ) = ⟺ (𝑝1 − 𝑝2 )[(2(1 − 𝑝3 ) … (1 − 𝑝𝑘 ) − 𝑝3 (1 − 𝑝4 ) … (1 − 𝑝𝑘 )− −𝑝𝑘 (1 − 𝑝3 ) … (1 − 𝑝𝑘−1 )] = 0, which yields 𝑝1 = 𝑝2 Similarly, by subtracting (6.3) from (6.2), we have (𝑝2 − 𝑝3 )(1 − 𝑝1 )(1 − 𝑝4 ) … (1 − 𝑝𝑘 ) + (𝑝2 − 𝑝3 )(1 − 𝑝1 )(1 − 𝑝4 ) … (1 − 𝑝𝑘 )− −(𝑝1 − 𝑝2 )𝑝𝑘 (1 − 𝑝3 ) … (1 − 𝑝𝑘−1 ) = ⟺ (𝑝2 − 𝑝3 )[(2(1 − 𝑝1 ) … (1 − 𝑝𝑘 ) − 𝑝1 (1 − 𝑝4 ) … (1 − 𝑝𝑘 )− −𝑝𝑘 (1 − 𝑝3 ) … (1 − 𝑝𝑘−1 )] = 0, which yields 𝑝2 = 𝑝3 It is obvious that the equations (6.i) are circularly symmetric: substituting 𝑝𝑗 for 𝑝𝑖 (𝑖 ≠ 𝑗) into equation (6.i), we get the equation (6.j) Therefore, the optimal solutions obey 𝑝1 = 𝑝2 = = 𝑝𝑘 , which allows us to solve equation (6.k+1) for: 𝑝1 = 𝑝2 = = 𝑝𝑘 = (7) Fig Comparison of the probability of successful collision resolution by the number of UEs choosing the same preamble with the power loss exponent 𝑘 i= 3.2 𝑘 Substituting equation (7) into equation (4), we obtain: 1 𝑘−1 𝑘 𝑘 𝑃𝑝𝑘,min = 𝑘 (1 − ) 𝑘−1 = (1 − ) 𝑘 = 𝑃𝑝,max (8) From equation (8), it is obvious that 𝑃𝑝𝑘 ≥ 𝑃𝑝,max In the following section, we will perform numerical evaluation for the analytical results derived above IV SIMULATION RESULTS In our simulation, we adopt the numerical examples and part of the Matlab code presented in [2] to demonstrate the performance of the proposed A-ACB in cellular networks, whose parameters are summarized in Table TABLE I SIMULATION PARAMETERS Parameters Specifications Number of inactive UEs 2.104 Number of BS antenna M UEs are uniform distributions in hexagonal cells, Power loss exponent 100 R = 25 – 250m Deviation of shadow fading 10 dB Probability of active UEs 0.001 Probability in next access 0.5 Fig Comparison of the probability of successful collision resolution by the number of UEs choosing the same preamble with the power loss exponent 𝑘𝑖 = 3.8 Remarks: Fig shows that the A-ACB protocol always outperforms the ACBPC by about 12%, regardless of the number of UEs/preamble As compared to the SUCRe protocol, the success resolution rate of the A-ACB is initially lower, but levels up quickly when the number of UEs per preamble reaches 30, and becomes far more superior when the number of UEs/preamble keeps increasing above 30, where the success resolution rate of the SUCRe degrades sharply ki = 3.2; 3.8 When the power loss exponent value increases from 3.2 to 3.8 in Fig 4, it is observed that the cut-off point between the A-ACB and SUCRe performances moves to the right, from 30 (in Fig 3) to 40 This is because the gain difference The simulation is carried out on a standard personal computer using Matlab for two scenarios Firstly, we 48 2021 8th NAFOSTED Conference on Information and Computer Science (NICS) of the UEs becomes bigger when the power loss exponent increases, making the collision resolution probability of SUCRe increases When the power loss exponent changes from 3.2 to 3.8, the curve of the SUCRe shifts to the right while the curve of A-ACB barely changes (please refer to Fig 6) The cutoff point of the two curves now moves to 1.25 × 104 This represents a better resolution probability of the SUCRe as the power loss exponent increases B Average number of RA attempts in a crowded network In this scenario, at each access step there is a random number of UE activated with probability 0.001 UEs that are not accepted on the first attempt will participate in the next attempt with the probability being 0.5 Each UE can access up to 10 subsequent attempts After 10 attempts, if it is still unable to access, it will be eliminated Because the A-ACB always outperforms the ACBPC, we only compare the AACB and the SUCRe performances in this simulation, with the conventional LTE protocol serves as a reference (Baseline) V CONCLUSIONS This paper proposes a novel random access protocol that enables adaptive ACB values for massive MIMO-aided mMTC systems We demonstrated analytically that the proposed protocol outperforms the ACBPC protocol in terms of successful resolution probability as well as surpassing the SUCRe performance when the number of active users is large In terms of user fairness, although the proposed A-ACB does not perform as well as the ACBPC protocol, it achieves a higher fairness than the SUCRe Simulation results confirm the theoretical analysis while showing the dependence of collision resolution on the loss exponent of the environment Future direction for the research in this paper is to develop a method capable of combining the advantages of both SUCRe and A-ACB protocols ACKNOWLEDGMENT This work has been partly supported by VNU University of Engineering and Technology under project number CN21.05 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Physical Layer Design for Ultra-Reliable Low-Latency Communications in 3GPP Releases 15, 16, and 17, IEEE Access (Volume: 9) Page(s): 433 – 444 [7] Shiva Raj Pokhrel; Jie Diang; Jihong Park; Ok-Sun Park; Jinho Choi, Towards Enabling Critical mMTC: A Review of URLLC Within mMTC, IEEE Access (Volume: 8)Page(s): 1311796 – 131813 vol 9, no 11, pp 3590-3600, 201 [8] H Han, Y Li, and X Guo, “ A Graph-Based Random Access Protocol for Crowded Massive MIMO Systems,” IEEE Transactions on Wireless Communications, vol 16, no 11, pp 7348- 7361, Nov 2017 [9] Suyang Duan, Vahid Shah-Mansouri, Zehua Wang, and Vicent Wong, D-ACB: Adaptive Congestion Control Algorithm for Bursty M2M Traffic in LTE Networks, IEEE Transactions on Vehicular Technology 2016 [10] J C Marinello and T Abrao, “Collision Resolution Protocol via Soft Decision Retransmission Criterion,” IEEE Transactions on Vehicular Technology,vol 68, no 4, pp 4094-4097, April 2019 [11] https://github.com/emilbjornson/sucre-protocol Fig Comparison of the average number of the successful attempts between SUCRe and A-ACB with the power loss exponent 𝑘𝑖 = 3.2 Fig Comparison of the average number of the successful attempts between SUCRe and A-ACB with the power loss exponent 𝑘𝑖 = 3.8 The simulation results, presented in Fig 5, clearly show that the average number of successful RA attempts of the AACB is higher than that of the SUCRe when the number of inactive UEs ranges from to 1.20 × 104 When the number of inactive UEs increases, the average number of successful access attempts of A-ACB becomes smaller than the SUCRe’s 49 ... than the ACB, it will retransmit Otherwise, it will wait for the next access step The proposed name for this method, adaptive ACB (A- ACB) , emphasizes the innovative use of adaptive values for. .. probability of the ACBPC protocol [1] For the proposed protocol (A- ACB) , the ACBs of the UEs are different because the channel gain to each UE is different Suppose that the values of the ACBs are... still unable to access, it will be eliminated Because the A- ACB always outperforms the ACBPC, we only compare the AACB and the SUCRe performances in this simulation, with the conventional LTE protocol