Random Access Channel Research Articles

On the Interplay between Deadline-Constrained Traffic and the Number of Allowed Retransmissions in Random Access Networks.

In this paper, a network comprising wireless devices equipped with buffers transmitting deadline-constrained data packets over a slotted-ALOHA random-access channel is studied. Although communication protocols facilitating retransmissions increase reliability, a packet awaiting transmission from the queue experiences delays. Thus, packets with time constraints might be dropped before being successfully transmitted, while at the same time causing the queue size of the buffer to increase. To understand the trade-off between reliability and delays that might lead to packet drops due to deadline-constrained bursty traffic with retransmissions, the scenario of a wireless network utilizing a slotted-ALOHA random-access channel is investigated. The main focus is to reveal the trade-off between the number of retransmissions and the packet deadline as a function of the arrival rate. Towards this end, analysis of the system is performed by means of discrete-time Markov chains. Two scenarios are studied: (i) the collision channel model (in which a receiver can decode only when a single packet is transmitted), and (ii) the case for which receivers have multi-packet reception capabilities. A performance evaluation for a user with different transmit probabilities and number of retransmissions is conducted. We are able to determine numerically the optimal probability of transmissions and the number of retransmissions, given the packet arrival rate and the packet deadline. Furthermore, we highlight the impact of transmit probability and the number of retransmissions on the average drop rate and throughput.

Random Access and Uplink Shared Channel Resource Allocation With NOMA

Random Access and Uplink Shared Channel Resource Allocation With NOMA

A Learning-Based Energy-Efficient Device Grouping Mechanism for Massive Machine-Type Communication in the Context of Beyond 5G Networks

With the increasing demand for high data rates, low delay, and extended battery life, managing massive machine-type communication (mMTC) in the beyond 5G (B5G) context is challenging. MMTC devices, which play a role in developing the Internet of Things (IoT) and smart cities, need to transmit short amounts of data periodically within a specific time frame. Although blockchain technology is utilized for secure data storage and transfer while digital twin technology provides real-time monitoring and management of the devices, issues such as constrained time delays and network congestion persist. Without a proper data transmission strategy, most devices would fail to transmit in time, thus defying their relevance and purpose. This work investigates the problem of massive random access channel (RACH) attempts while emphasizing the energy efficiency and access latency for mMTC devices with critical missions in B5G networks. Using machine learning techniques, we propose an attention-based reinforcement learning model that orchestrates the device grouping strategy to optimize device placement. Thus, the model guarantees a higher probability of success for the devices during data transmission access, eventually leading to more efficient energy consumption. Through thorough quantitative simulations, we demonstrate that the proposed learning-based approach significantly outperforms the other baseline grouping methods.

Narrowband Internet of Things via Low Earth Orbit Satellite Networks: An Efficient Coverage Enhancement Mechanism Based on Stochastic Geometry Approach.

With the development of IoT technology and 5G massive machine-type communication, the 3GPP standardization body considered as viable the integration of Narrowband Internet of Things (NB-IoT) in low Earth orbit (LEO) satellite-based architectures. However, the presence of the LEO satellite channel comes up with new challenges for the NB-IoT random access procedures and coverage enhancement mechanism. In this paper, an Adaptive Coverage Enhancement (ACE) method is proposed to meet the requirement of random access parameter configurations for diverse applications. Based on stochastic geometry theory, an expression of random access channel (RACH) success probability is derived for LEO satellite-based NB-IoT networks. On the basis of a power consumption model of the NB-IoT terminal, a multi-objective optimization problem is formulated to trade-off RACH success probability and power consumption. To solve this multi-objective optimization problem, we employ the Non-dominated Sorting Genetic Algorithms-II (NSGA-II) method to obtain the Pareto-front solution set. According to different application requirements, we also design a random access parameter configuration method to minimize the power consumption under the constraints of RACH success probability requirements. Simulation results show that the maximum number of repetitions and back-off window size have a great influence on the system performance and their value ranges should be set within [4, 18] and [0, 2048]. The power consumption of coverage enhancement with ACE is about 58% lower than that of the 3GPP proposed model. All this research together provides good reference for the scale deployment of NB-IoT in LEO satellite networks.

Age of information for remote sensing with uncoordinated finite-horizon access

We analyze a remote sensing system in the Internet of things, where uncoordinated nodes send status updates to a common receiver to achieve information freshness, quantified through age of information. We consider a finite horizon scheduling over a random multiple access channel, where colliding messages are lost. We show that nodes must adopt a further randomization to deviate from identical schedules and escape collision deadlocks. Moreover, we discuss the impact of feedback availability if, due to, e.g., energy expenditure, it decreases the number of transmission opportunities.

Covert Communication With Gaussian Noise: From Random Access Channel to Point-to-Point Channel

Covert Communication With Gaussian Noise: From Random Access Channel to Point-to-Point Channel

Multistage Decimator Design for the Low-PHY PRACH Receiver

This paper describes the design of a multistage decimator for the Physical Random Access Channel (PRACH) receiver based on the hybrid time/frequency domain architecture. Flexible structure of the multistage decimator allows to support all combinations of PRACH subcarrier spacings and carrier bandwidths defined in the 3rd Generation Partnership Project (3GPP) Release 15 for Frequency Range (FR) 1. Impulse responses of low pass filters for each decimation stage do not depend on a selected combination allowing to facilitate hardware implementation. The multistage decimator jointly uses the Cascaded Integrator-Comb (CIC) and Nyquist filters to minimize number of required multipliers. Acceptable degradation level due to decimation in the receiver performance is estimated based on requirements defined by the Radio Access Network (RAN) working group 4. Assuming no specific detection algorithm, it is shown that the proposed design introduces negligible degradation, less than 0.1 dB in the operating Signal-to-Noise Ratio (SNR) region.

Decentralized Federated Learning Over Random Access Channel

Decentralized Federated Learning Over Random Access Channel

Performance of NR physical random access channel in the presence of carrier frequency offset in millimeter-wave bands

Performance of NR physical random access channel in the presence of carrier frequency offset in millimeter-wave bands

Radio Frequency Fingerprint Identification for 5G Mobile Devices Using DCTF and Deep Learning.

The fifth-generation (5G) mobile cellular network is vulnerable to various security threats. Radio frequency fingerprint (RFF) identification is an emerging physical layer authentication technique which can be used to detect spoofing and distributed denial of service attacks. In this paper, the performance of RFF identification is studied for 5G mobile phones. The differential constellation trace figure (DCTF) is extracted from the physical random access channel (PRACH) preamble. When the database of all 64 PRACH preambles is available at the gNodeB (gNB), an index-based DCTF identification scheme is proposed, and the classification accuracy reaches 92.78% with a signal-to-noise ratio of 25 dB. Moreover, due to the randomness in the selection of preamble sequences in the random access procedure, when only a portion of the preamble sequences can be trained, a group-based DCTF identification scheme is proposed. The preamble sequences generated from the same root value are grouped together, and the untrained sequences can be identified based on the trained sequences within the same group. The classification accuracy of the group-based scheme is 89.59%. An experimental system has been set up using six 5G mobile phones of three models. The 5G gNB is implemented on the OpenAirInterface platform.

Clustering Approach for Reliable Wireless Communication

Multiple access techniques for 5G systems are based on principles related to security, efficiency, and performance increase. Multi-user shared access (MUSA) is included in code-domain non-orthogonal multiple access (CD-NOMA) techniques with multiple benefits including multiple-access interference minimization and system capacity increase. The additional benefits of MUSA include its grant-free nature, which makes it applicable to scenarios involving random access channels, minimal latency communications, etc. Depending on the high-frequency diversity of the fading-affected channels, this technique is also used to lessen their effects. This paper illustrates the concept of code correlation used in MUSA by proposing a method to allocate MUSA codes to active users in an uplink data transmission system based on clusters. This clustering approach (grouping of 3GPP TR 38.812 spreading codewords) enables performance improvement in different system configurations by implementing various scenarios and providing reliable results. It is demonstrated that four-length spreading code selection from 3GPP family codes is a satisfactory solution, and this cluster grouping can be designed in a less overloaded multi-user system. The challenges, advantages, and limitations of the proposed method are outlined throughout the study.

FASURA: A Scheme for Quasi-Static Fading Unsourced Random Access Channels

FASURA: A Scheme for Quasi-Static Fading Unsourced Random Access Channels

The role of SIC on the design of next generation multiple access

The interplay of physical layer enhancements and classic random access protocols is the objective of this paper. Successive interference cancellation (SIC) is among the major enhancements of the physical layer. Considering the classic representatives of random access protocols, Slotted ALOHA and Channel Sensing Multiple Access (CSMA), we show that two regimes can be identified as a function of the communication link spectral efficiency. In case of high levels of spectral efficiency, multi-packet reception enabled by SIC is of limited benefit. Sum-rate performance is dominated by the effectiveness of the Medium Access Control (MAC) protocol. On the contrary, for low spectral efficiency levels, sum-rate performance is essentially dependent on physical layer SIC capability, while the MAC protocol has a marginal impact. Limitations due to transmission power dynamic range are shown to induce unfairness among nodes. However, the unfairness issue fades away when the system is driven to work around the sum-rate peak achieved for low spectral efficiency. This can also be confirmed by looking at Age of Information (AoI) metric. The major finding of this work is that SIC can boost performance, while still maintaining a fair sharing of the communication channel among nodes. In this regime, the MAC protocol appears to play a marginal role, while multi-packet reception endowed by SIC is prominent to provide high sum-rate, low energy consumption, and low AoI.

LTE Device Radio Frequency Fingerprints Blind Extraction Based on Temporal-Frequency Domain PRACH Signals

A frequency-domain cepstrum correlation and temporal transient filtered radio frequency fingerprints (RFF) blind extraction method is proposed for long term evolution uplink device authentication in this work. With the merits of the constant-modulus nature of the Zadoff-Chu (ZC) sequence and the cyclic prefix (CP) structure of the physical random access channel (PRACH) frame, the device RFF integrated in both the frequency-domain ZC sequence and the transient ramp-on/ramp-off sequences are extracted. For the frequency-domain RFF extraction, the cepstrum of the ZC sequence is calculated to enlarge the gap between the constant RFF and the random fading effects, and the correlation between two cepstrum fragments is then calculated to mitigate the random fading components. For the temporal RFF extraction, the ramp-on and ramp-off features induced by the device-specific power amplifier are extracted by exploiting the CP structure of the PRACH frame, where the CP part and the duplicate part are adaptively filtered and the final adapted weight of the least mean square filter is used as RFF. No prior PRACH parameter knowledge is required in RFF extraction and both the frequency-domain and the temporal RFF are combined as the input of the convolutional neural network to enhance the classification accuracy. With four-months sampling of PRACH signals emitted from universal software radio peripheral devices, the experimental results show that the authentication accuracy of the proposed combined RFF can reach as high as 99.9% in the line-of-sight (LOS) scenario and 99.6% in the non-LOS scenario.

A Resource Optimization for Two-Step Random Access in 5G New Radio

This paper presents a resource optimization method for the 2-step random access (RA) procedure in the 5th generation new radio (5G NR). In 2-step RA, the MsgA includes a sequence as a preamble on the physical random access channel (PRACH) and uplink payload on the physical uplink shared channel (PUSCH). The mapping between PRACH slots and PUSCH slots is specified by system configuration parameters. The network reserves the corresponding PUSCH resource fixedly, regardless of the random access occasion (RO) occupancy rate and the uplink data traffic request. It deprives the uplink scheduling resource efficiency in cases of some RO unoccupied. To achieve higher utilization efficiency, this paper studies the reusing of the PUSCH slots and occasions fixed to RACH in MsgA. By detecting the preambles in RO before the corresponding PUSCH slots, the network acquires the occupancy of the RO. Then the PUSCH occasion (PO) in reserved PUSCH can be released, which conforms to the RO detection result. The release of the previously reserved PUSCH occasions can be rescheduled and reused by the user equipment (UE) for uplink data transmission. Hence more wireless resources can be scheduled in contrast to the existing allocation of uplink share channel in 2-step type random access. It suggests that using the method improves the efficiency of resource utilization.

Simplification of DFT and IDFT in PRACH

AbstractThe respective simplifications of prime‐point discrete Fourier transform (DFT) and ultra‐long‐point inverse discrete Fourier transform (IDFT) in physical random access channel (PRACH) are proposed. The former is an equivalent substitution of DFT function by using the property of Zadoff‐Chu (ZC) sequence, and the latter is an approximation based on cubic spline interpolation, which not only reduces the IDFT points, but also is easy to construct.

Remote Tracking of Distributed Dynamic Sources Over a Random Access Channel With One-Bit Updates

In this work, we consider a network, where distributed information sources whose states evolve according to a random process transmit their time-varying states to a remote estimator over a shared wireless channel. Each source generates packets in a decentralized manner and employs a slotted random access mechanism to transmit the packets. In particular, we are interested in networks with a large number of low-complexity devices that share low-capacity random access channels. Accordingly, we investigate update strategies for remote tracking of source states that require each update to constitute as few bits as possible. To that end, we develop update strategies requiring only one-bit of information per update that employ a local cancellation strategy. We further analytically compare the performance of the cancellation-enabled update policy to the optimal policy that does not restrict the number of bits for each update, which show that an asymptotic upper bound of the optimality ratio is <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\frac{13\sqrt{2}}{12}$</tex-math></inline-formula> . Through simulations, we compare the proposed cancellation-enabled one-bit update policy with zero-wait sampling and threshold-based sampling policies that require more than one-bit of information per update. The comparisons show that the cancellation-enabled update policy at its optimal threshold level outperforms the multi-bit update policies.

An Efficient Random Access Reception Algorithm for ToA Estimation in NB-IoT

Narrowband Internet of Things (NB-IoT) aims to provide wide coverage for a massive number of low-cost devices. Therefore, an NB-IoT physical random access channel (NPRACH) preamble based on a single tone signal with frequency hopping was designed, enabling the base station to estimate the time-of-arrival (ToA) values for realizing uplink synchronization among multiple users. However, due to residual carrier frequency offset (RCFO) in the NPRACH preamble, it is crucial to keep the accuracy of the ToA estimation. Recognizing this urgency, in this paper we first judiciously investigate the effect of the hooping distance on ToA estimation. With which, we propose an efficient receiving algorithm to improve the accuracy of ToA estimation. The main aim of the algorithm is to treat two consecutive symbol groups as a whole and then carry out difference calculations on the two newly constituted symbol groups to construct a more logical frequency hopping distance. Extensive numerical results validate the superiorly of our proposed scheme compared against conventional strategies, showing that the probability of the ToA estimation obtained by this method is 99% within the acceptable error range.

A novel design of multi-user sequence set for joint vehicular radar-communication based on Oppermann family

In this paper, a novel multi-user sequence set which are to be potentially used as communication preambles for joint vehicular radar and communication using Oppermann sequences is proposed. Herein, a set of Oppermann sequences with suitable auto-ambiguity functions (AF) and cross-ambiguity functions (AF) properties have been proposed. Moreover, a channel estimation algorithm using the designed Oppermann sequences is also proposed. The designed preamble, composed of optimized Oppermann sequences is an appropriate candidate for wireless standards, where both channel estimation and multi-user vehicular radar sensing are jointly pursued. The simulation results demonstrate that the designed sequences provide a significant performance improvement for vehicular radar sensing and don't degrade the channel estimation accuracy. The proposed optimized Oppermann sequences have better auto- and cross-AF compared existing Golay complementary sequences (used in IEEE 802.11ad as preamble), Zadoff-Chu sequences (used in 5G to generate preambles for the Physical Random Access Channel (PRACH)) and the non-optimized Oppermann sequences. Specifically, compared to the preamble composed of Golay complementary sequences in IEEE 802.11ad, the proposed sequences reduce the maximum sidelobe level of the auto-AF and maximum value level of cross-AF by at least 2 and 2.85 times, respectively. The target can still be accurately detected in mutual interference scenario caused by multiple radars in the vicinity. Both the sequences, when used for channel estimation achieve the CRLB limit. Both the proposed sequences and Golay complementary sequences, when used for channel estimation achieve the Cramer-Rao Lower Bound.

Dynamic Preamble Resource Distribution for Random Access in 5G New Radio Systems

Millimeter wave (mmWave) spectrum promises unprecedented data rates in 5G New Radio (NR). However, mmWave links are susceptible to severe path and propagation losses. Implementation of directional antennas that can manifest multiple beams becomes necessary at 5G base stations (gNBs) and User Equipments (UEs). Random access procedure (RAP), which is the first stage to establish connections to gNB, in its current state would be inadequate for such systems. To support RAP, 5G NR introduced mapping of different subsets of preambles in Physical Random Access Channel (PRACH) to different beams. We explore changes in RAP due to preamble-beam mapping and present a novel online algorithm to dynamically distribute preambles amongst beams to achieve fair access opportunities. The proposed algorithm can also eliminate overload problem of the beams with large UE population especially for high arrival rates. We extend the proposed algorithm to be applicable for RAP with access class barring mechanism which enables UEs to transmit a preamble with an optimal probability and, therefore, reduce access congestion. Through extensive simulations, we validate the efficiency of our proposed algorithms in providing fair channel access opportunities, improving throughput (or stability region), and reducing access delay when the system has high rate of UE arrivals and has unbalanced UE arrivals over different beams.