Random Access Networks Research Articles

On the Performance of Uplink Rate-Splitting Multiple Access

The use of new multiple access schemes emerges as a necessity in order to efficiently cope with the massive connectivity, reliability and high throughput requirements of the next generation Internet of Things. In this letter, we study the performance of an uplink rate-splitting multiple access (RSMA) network with two sources, in terms of outage probability and throughput. Specifically, we derive closed-form expressions for the outage probability of the transmitted messages and then, we utilize them to derive the throughput of the sources in a random access network with a medium access control protocol based on slotted ALOHA and RSMA.

Extended Successive Convex Approximation for Phase Retrieval With Dictionary Learning

Phase retrieval aims at recovering unknown signals from magnitude measurements of linear mixtures. In this paper, we consider the phase retrieval with dictionary learning problem, which includes another prior information that the signal admits a sparse representation over an unknown dictionary. The task is to jointly estimate the dictionary and the sparse representation from magnitude-only measurements. To this end, we study two complementary formulations and develop efficient parallel algorithms by extending the successive convex approximation framework using a smooth majorization. The first algorithm is termed <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">compact-SCAphase</i> and is preferable in the case of moderately diverse mixture models with a low number of mixing components. It adopts a compact formulation that avoids auxiliary variables. The proposed algorithm is highly scalable and has reduced parameter tuning cost. The second algorithm, referred to as <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">SCAphase</i> , uses auxiliary variables and is favorable in the case of highly diverse mixture models. It also renders simple incorporation of additional side constraints. The performance of both methods is evaluated when applied to blind channel estimation from subband magnitude measurements in a multi-antenna random access network. Simulation results show the efficiency of the proposed techniques compared to state-of-the-art methods.

Mean-Field Limits for Large-Scale Random-Access Networks

We establish mean-field limits for large-scale random-access networks with buffer dynamics and arbitrary interference graphs. Although saturated buffer scenarios have been widely investigated and yield useful throughput estimates for persistent sessions, they fail to capture the fluctuations in buffer contents over time and provide no insight in the delay performance of flows with intermittent packet arrivals. Motivated by that issue, we explore in the present paper random-access networks with buffer dynamics, where flows with empty buffers refrain from competition for the medium. The occurrence of empty buffers thus results in a complex dynamic interaction between activity states and buffer contents, which severely complicates the performance analysis. Hence, we focus on a many-sources regime where the total number of nodes grows large, which not only offers mathematical tractability but is also highly relevant with the densification of wireless networks as the Internet of Things emerges. We exploit timescale separation properties to prove that the properly scaled buffer occupancy process converges to the solution of a deterministic initial value problem and establish the existence and uniqueness of the associated fixed point. This approach simplifies the performance analysis of networks with huge numbers of nodes to a low-dimensional fixed-point calculation. For the case of a complete interference graph, we demonstrate asymptotic stability, provide a simple closed form expression for the fixed point, and prove interchange of the mean-field and steady-state limits. This yields asymptotically exact approximations for key performance metrics, in particular the stationary buffer content and packet delay distributions.

QoS Enabled Heterogeneous BLE Mesh Networks

Bluetooth Low Energy (BLE) is a widely known short-range wireless technology used for various Internet of Things (IoT) applications. Recently, with the introduction of BLE mesh networks, this short-range barrier of BLE has been overcome. However, the added advantage of an extended range can come at the cost of a lower performance of these networks in terms of latency, throughput and reliability, as the core operation of BLE mesh is based on advertising and packet flooding. Hence, efficient management of the system is required to achieve a good performance of these networks and a smoother functioning in dense scenarios. As the number of configuration points in a standard mesh network is limited, this paper describes a novel set of standard compliant Quality of Service (QoS) extensions for BLE mesh networks. The resulting QoS features enable better traffic management in the mesh network, providing sufficient redundancy to achieve reliability whilst avoiding unnecessary packet flooding to reduce collisions, as well as the prioritization of certain traffic flows and the ability to control end-to-end latencies. The QoS-based system has been implemented and validated in a small-scale BLE mesh network and compared against a setup without any QoS support. The assessment in a small-scale test setup confirms that applying our QoS features can enhance these types of non-scheduled and random access networks in a significant way.

Maximizing Fairness for Resource Allocation in Heterogeneous 5G Networks

In this article, we first formulate the joint resource allocation, interference minimization, user-level, and cell-level fairness for maximum resource reuse in 5G heterogeneous small cell networks as an NP-hard problem. We then propose three algorithms - centralized, distributed, and randomized distributed algorithms - to efficiently solve the formulated resource allocation problem while minimizing interference, maximizing fairness, and resource reuse. Through extensive real data analysis and network simulations, we show that our proposed solutions outperform state-of-the-art schemes, namely interfering model (INT) and distributed random access (DRA), for both low and high-density 5G networks.

Throughput and resource optimization for adaptive coding‐based random access networks with correlated sources

SummaryModern wireless communication networks frequently have lower application throughput due to higher number of collisions and subsequent retransmission of data packets. Moreover, these networks are characterized by restricted computational capacity due to limited node‐battery power. These challenges can be assessed for deploying fast, reliable network design with resource‐restrained operation by means of concurrent optimization of multiple performance parameters across different layers of the conventional protocol stack. This optimization can be efficiently accomplished via cross‐layer design with the aid of network coding technique and optimal allocation of limited resources to wireless links. In this paper, we evaluate and analyze intersession coding across several source–destination pairs in random access ad hoc networks with inherent power scarcity and variable capacity links. The proposed work addresses the problem of joint optimal coding, rate control, power control, contention, and flow control schemes for multi‐hop heterogeneous networks with correlated sources. For this, we employ cross‐layer design for multiple unicast sessions in the system with network coding and bandwidth constraints. This model is elucidated for global optimal solution using CVX software through disciplined convex programming technique to find the improved throughput and power allocation. Simulation results show that the proposed model effectively incorporates throughput and link power management while satisfying flow conservation, bit error rate, data compression, power outage, and capacity constraints of the challenged wireless networks. Finally, we compare our model with three previous algorithms to demonstrate its efficacy and superiority in terms of various performance metrics such as transmission success probability, throughput, power efficiency, and delay.

Optimal Energy Sharing for Cooperative Relaying in a Random Access Network With Energy Harvesting Nodes

In this article, we consider an energy harvesting cooperative network comprised of two data sources and one relay. All nodes transmit based on a predefined slotted Aloha protocol in a random access environment. The main challenge we study is to find how the relay node must share its energy between two sources to optimize their QoS metrics, i.e., throughput and average transmission delay (ATD), separately. Thus, according to our multi-source scenario, we encounter a multi-objective optimization problem (MOOP). Since the relay does not prioritize between two sources, in order to solve the MOOP, we optimize equal-weight linear aggregation of the QoS metrics of two sources. Interestingly, we show that our problem can be modeled as an exact potential game in which the Nash equilibrium strategy is an optimal and stable solution of the related MOOP. The cooperative relaying strategy proposed in this article assures that the throughput and ATD of each source is better than the corresponding metrics without relay. Finally, we present numerical results to show how much the derived cooperative relaying strategies improve the QoS of each source.

SatOpt Partition: Dividing Throughput-Stability Region for IEEE 802.11 DCF Networks

This article investigates the throughput stability of nonsaturated 802.11 networks with distributed coordination function (DCF). We find that this throughput stability exhibits distinct characteristics in two different regions (or scopes) of parameter settings: the maximum stable throughput is higher than the saturation throughput and lasts for a long duration (say, in order of months) in one region, while the former is bounded by the latter in another region. Our core contribution is an innovative approach (called SatOpt partition) that can identify these two regions quickly and accurately, by a comparison between the saturated and optimal attempt rates. Our partition approach is suitable for a wide range of 802.11 DCF contention window settings, while our partition result is unique. Further, for 802.11 DCF standard settings, we predict the maximum stable throughput successfully, and reveal that it is often higher than the saturation throughput. We verify our approach via the widely adopted 802.11 DCF ns2 simulator (mostly with typical 802.11 DCF standard settings). We speculate that this two-region stability property should be inherent for any random-access networks. This suggests that the research on the throughput-stability problem should differentiate regions of parameter settings and failing to do so might produce inconsistent results. This study is expected to take a critical step toward solving the throughput-stability problem.

Transition time asymptotics of queue-based activation protocols in random-access networks

We consider networks where each node represents a server with a queue. An active node deactivates at unit rate. An inactive node activates at a rate that depends on its queue length, provided none of its neighbors is active.For complete bipartite networks, in the limit as the queues become large, we compute the average transition time between the two states where one half of the network is active and the other half is inactive. We show that the law of the transition time divided by its mean exhibits a trichotomy, depending on the activation rate functions.

Rate Selection for Wireless Random Access Networks Over Block Fading Channels

We study uncoordinated random access over fading channels where each user independently decides whether to send a packet or not to a common receiver at any given time slot. Specifically, we develop an information theoretic formulation to characterize the overall system throughput. We consider two scenarios: classical slotted ALOHA, where no multiuser detection (MUD) capability is available and slotted ALOHA with MUD. In each case, in order to maximize the system throughput, we provide methods to obtain the optimal rates and channel activity probabilities using the user distances to the receiver (or, equivalently, their average signal to noise ratios) assuming a Rayleigh block fading channel. The results demonstrate that the newly proposed optimal rate selection solutions offer significant increase in the expected system throughputs compared to the “same rate to all users” approach commonly used in the literature. In addition to the overall throughput optimization, we also address the issue of fairness among users and propose approaches guaranteeing a minimum amount of individual throughput to each user, and design systems with limited individual outage probabilities for increased energy efficiency and reduced delay.

Interference-Aware Opportunistic Random Access in Dense IoT Networks

It is a challenging task to design a random access protocol that achieves the optimal throughput in multi-cell random access with decentralized transmission due to the difficulty of coordination. In this paper, we present a decentralized interference-aware opportunistic random access (IA-ORA) protocol that enables us to obtain the optimal throughput scaling in an ultra-dense multi-cell random access network with one access point (AP) and a number of users. In sharp contrast to opportunistic scheduling for cellular multiple access where users are selected by base stations, under the IA-ORA protocol, each user opportunistically transmits with a predefined physical layer (PHY) data rate in a decentralized manner if not only the desired signal power to the serving AP is sufficiently large but also the generating interference leakage power to the other APs is sufficiently small (i.e., two threshold conditions are fulfilled). As a main result, it is shown that the optimal aggregate throughput scaling (i.e., the MAC throughput of e/1 in a cell and the power gain) is achieved in a high signal-to-noise ratio regime if the number of per-cell users exceeds some level. Additionally, it is numerically demonstrated via computer simulations that under practical settings, the proposed IA-ORA protocol outperforms conventional opportunistic random access protocols in terms of aggregate throughput.

Delay and Stability Analysis of Connection-Based Slotted-Aloha

In recent years, connection-based slotted-Aloha (CS-Aloha) has been proposed to improve the performance of random access networks. In this protocol, each node attempts to send a request to the access point (AP) before packet transmission. Once this attempt is successful, the node can transmit up to M packets to the AP. Previous works indicated that the CS-Aloha can achieve a higher throughput than the classical slotted Aloha (S-Aloha), if M is large enough. However, the impact of M on the delay performance and stability is still unknown. To solve this problem, we model each node of the CS-Aloha as a vacation queueing system with limited service discipline, where we consider each batch of packet transmissions as a busy period, and the attempt process between two successive busy periods as a vacation period. We derive the delay distribution, which is turned out to be a geometric distribution. From this result, we further obtain the mean delay, the delay jitter, and the bounded delay region. Our analysis shows that increasing M can accelerate the clean-up of the buffer in each node and thus decrease the attempt rate, which can reduce the average time needed by a node to make a successful attempt. As a result, a large M can decrease the mean delay and the delay jitter, and enlarge the bounded delay region. Also, we obtain the condition to achieve the minimum mean delay under different values of M .

Physical-Layer Network Coding: An Efficient Technique for Wireless Communications

As a subfield of network coding, PNC can effectively enhance the throughput of wireless networks by mapping superimposed signals at the receiver to other forms of user messages. Over the past 20 years, PNC has received significant research attention and has been widely studied in various communication scenarios, for example, TWRC, NOMA in 5G networks, random access networks, and so on. Later on, channel-coded PNC and related communication techniques were investigated to ensure network reliability, such as the design of channel code, low-complexity decoding, and cross-layer design. In this article, we briefly review the variants of channel-coded PNC-aided wireless communications with the aim of inspiring future research activities in this area. We also put forth open research problems along with a few selected research directions under PNC-aided frameworks.

Analysis of the shortest relay queue policy in a cooperative random access network with collisions

The aim of this work concerns the performance analysis of systems with interacting queues under the join the shortest queue policy. The case of two interacting queues results in a two-dimensional random walk with bounded transitions to non-neighboring states, which in turn results in complicated boundary behavior. Although this system violates the conditions of the compensation approach due to the transitions to non-neighboring states, we show how to extend the framework of the approach and how to apply it to the system at hand. Moreover, as an additional level of theoretic validation, we have compared the results obtained with the compensation approach with those obtained using the power series algorithm and we have shown that the compensation approach outperforms the power series algorithm in terms of numerical efficiency. In addition to the fundamental contribution, the results obtained are also of practical value, since our analysis constitutes a first attempt toward gaining insight into the performance of such interacting queues under the join the shortest queue policy. To fully comprehend the benefits of such a protocol, we compare its performance to the Bernoulli routing scheme as well as to that of the single relay system. Extensive numerical results show interesting insights into the system’s performance.

MSE Tail Analysis for Remote State Estimation of Linear Systems Over Multiantenna Random Access Channels

In this article, we consider the Kalman filter (KF)-based state estimation in the multisensor networked control systems. The sensors communicate plant state observations to a remote state estimator over a multiantenna random access network, resulting in random fading in measurements and rank-deficient observation updates in KF. In contrast to the conventional literature where average state estimation mean-square-error (MSE) is adopted as the estimation performance measure, we analyze the state estimation MSE tail distribution which guarantees fine-grained characterizations of the MSE sample path. We developed various sufficient conditions for the well behaved tail distribution of the MSE. Specifically, we propose the observable and unobservable cone decomposition of the transformed coordinate system induced by the singular value decomposition of the measurement matrix, which enables us to overcome the limitation of MSE analysis with rank deficient measurement matrix. In the noiseless plant case, we establish the sufficient condition such that the state estimation MSE is a supermartingale in high SNR regime. Via martingale convergence theorems, we show that the state estimation MSE is almost surely stable, which results in outlier-free MSE sample path. In the noisy plant case, we show that the state estimation MSE is uniformly upper bounded by a Markov chain in high SNR regime. We establish a sufficient condition for the existence of the steady-state distribution of the Markov chain. Via analyzing the stochastic fixed point equation associated with the stationary distribution of the Markov chain, we provide the closed-form expression for the MSE tail probability. We further established a power law that provides closed-form characterizations of the tradeoff between the communication resource and the MSE tail decay rate, where more communication resource consumption leads to faster exponential decaying MSE tail. We also recover the results in the existing literature when applying our developed theory to the scalar systems.

Random access networks with separable schemes

Consider a time slotted multiuser random access network where M users have access to a single channel and each user attempts to send packets in a particular time slot with a certain probability, according to a predetermined access scheme. This forms an interacting system of queues and in this study, the authors consider generic access schemes that satisfy a separability condition and obtain bounds for the stability region, directly using a Lyapunov-type analysis. They apply their results to the case of random access networks with partial conflicts where any particular user has collision conflicts with only a subset of the other users. Using conflict graphs to quantify the degree of such conflicts, they obtain bounds for the stability region for both deterministic and random conflict graphs that model, respectively, static and mobile networks.

Whitelisting in RFDMA Networks

Uplink transmissions, within coexisting distinct sub-GHz technologies operating in the same unlicensed band, can be exposed to detrimental impact of the interference. In such scenarios, transmission scheduling becomes important for mitigating interference or minimizing the impact of the interference. For this purpose, we aim to whitelist relatively better channels in terms of their yielded packet reception ratio using our proposed channel quality metric that is based on the received signal-to-interference-plus-noise ratio. In this paper, we investigate the trade-offs of the channel whitelisting in random frequency division multiple access (RFDMA) networks in the presence of the cumulative intra- and inter-technology interferences. Our main findings indicate that, although channel whitelisting reduces the degree of freedom, and thus the overall capacity, it empowers a certain amount of devices to be served at a much lower received signal power, whereas this is infeasible for non-whitelisting scenarios at larger received signal power, which signifies the energy conservation ability of our proposed whitelisting method. It is experimentally demonstrated, on Sigfox, a particular type of RFDMA network, that non-whitelisting scenarios are not capable of supporting any devices at a received signal power below -118 dBm. Even for lower received signal power, we are able to reduce the required number of retransmissions at the same reception probability, which indeed indicates that the overall reliability of the network is improved.

Compute-and-Forward for Random-Access: The Case of Multiple Access Points

Compute-and-forward (C&F) recently finds new applications in random-access networks focusing on the single access point (AP) scenario. In this paper, we extend the use of C&F from the single AP scenario to the multi-AP scenario. To achieve this, we identify two major challenges and propose two novel solutions. First, we introduce an AP cooperation problem and develop an efficient distributed algorithm. Second, we introduce a joint channel estimation and active user recovery problem and propose a solution based on spare recovery techniques. In addition, we provide accurate throughput and delay expressions for C&F-based carrier-sense multiple access (CSMA) protocols. These expressions, together with our trace-driven simulations, demonstrate the significant advantages of C&F-based CSMA over conventional CSMA in the multi-AP scenario.

피드백 기반 랜덤 엑세스 망에서의 순차적 간섭제거 기법

피드백 기반 랜덤 엑세스 망에서의 순차적 간섭제거 기법

Delay Performance of Two-Stage Access in Cellular Internet-of-Things Networks

In this paper, two-stage random-access-based massive Internet-of-things uplink transmission is investigated. In this scheme, aggregator nodes are additionally deployed to relay packets to deal with a massive number of arrivals. A user node determines whether to utilize aggregator nodes according to the received signal strength from base stations and aggregator nodes. If the user node selects and transmits a packet to an aggregator node, the aggregator node stores and forwards the received packet to the base station. The use of aggregator nodes can reduce the per-hop delay as well as the user energy consumption by reducing the transmission distance from user nodes. However, in the two-stage random access protocol, an increase in the number of aggregator nodes incurs collisions in the wireless medium, and hence, increases the queueing delay at the aggregator node. Thus, improved radio resource allocation and network design are required to reduce additional delay in the two-hop uplink system. We, therefore, focus on optimizing the transmission probabilities of transmitting nodes and the aggregator node density to minimize the delay in two-stage random access networks.