This paper presents a comprehensive study on random access (RA) design for multi-channel Ambient IoT (A-IoT) networks enabled by uplink frequency division multiple access (FDMA). We introduce and unify the three-step RA procedure (RAP) specified in ongoing 3GPP standardization, which serves as a useful reference for future research. To fully exploit the multi-channel capability, we propose enhanced frame structures, including a novel multi-round Msg1 collection (MRMC) scheme, in which Msg1 carries a randomly generated ID from each device and is transmitted in the first step of the three-step RAP. We also develop new analytical models that capture the unique characteristics of multi-channel A-IoT, providing closed-form expressions for RA efficiency that serve as a foundation for network optimization. Furthermore, we design online control algorithms that estimate the device population in real time and dynamically adjust frame configurations for optimal operation under device uncertainty. The proposed Boosted Estimation with Early Frame Termination (BE2FT) algorithm effectively handles bursty traffic conditions and improves resource utilization. Extensive simulations validate the accuracy of our analytical models and demonstrate significant gains in RA efficiency and service time. The proposed scheme achieves performance close to the ideal performance, where the number of devices is assumed perfectly known and the frame length is optimally configured.

The freshness of information is crucial for IoT applications, such as remote sensing systems and real-time status updates. The overabundance of stale information at the destination can potentially compromise the accuracy and reliability of system decision-making processes. To address this concern, a new metric termed the Age of Information (AoI) has been proposed to capture the freshness of status updates. In this article, we present an analytical framework to establish a dual-action guideline for minimizing the average AoI in random access networks. We then utilize this guideline to propose two online activation control protocols: 1) the age-dependent activation control (ADAC) algorithm and 2) the threshold-based ADAC (T-ADAC) algorithm. The former prioritizes the activation of devices with higher instantaneous AoI, while the latter enables a device to be active with a dynamic probability only when its instantaneous AoI is beyond a predetermined threshold. Extensive simulations demonstrate the effectiveness of the proposed ADAC and T-ADAC, showing that our proposed algorithms outperform the state-of-the-art approaches in random access networks. Specifically, the proposed methods can achieve maximum throughput and minimum average AoI, showcasing their superior performance in real-world scenarios.

The rapid expansion of Internet of Things (IoT) applications has led to significant access challenges for radio access networks, potentially causing bottlenecks and degrading service quality. This paper proposes Dual-Core, a novel dual collision resolution mechanism for the four-step random access (RA) procedure of 5G communication systems. Dual-Core integrates slotted ALOHA protocol for random access preamble (RAP) transmission and a custom splitting algorithm for bandwidth request message (Msg 3) transmissions, resolving collisions in both PRACH and PUSCH. Additionally, we introduce an online controlled access class barring (ACB) to maximize the throughput of Dual-Core, with the optimal ACB rate determined by our proposed analytical model. Numerical results demonstrate that the proposed Dual-Core significantly reduces service time compared to the conventional RA procedure operating at its optimal performance, while utilizing the same amount of PUSCH resources. Furthermore, when additional PUSCH resources are available, Dual-Core efficiently utilizes them to serve more devices, a capability that conventional systems lack.

Due to flexibility, ad-hoc networking is an attractive structure for future emerging networks, such as Internet of Things (IoT), wireless sensor networks and vehicular networks. However, due to infrastructure-less, optimizing transmission control to avoid collision in ad-hoc networks is challenging. In this paper, we proposed an adaptive slotted-contention-based media access control (A-SCMAC) protocol which can adapt to network dynamics so that it can reduce collision and improve throughput. With A-SCMAC, each time slot consists of two periods: reservation period (RP) and transmission period (TP). By observing the channel outcomes in the RP the nodes learn the network status such as the number of nodes who have packets to transmit and control the transmission optimally for reserving the TP. Simulation results show that the proposed A-SCMAC can achieve the maximum throughput even the network traffic load changes.

Internet of Things (IoT) represents one of the most significant paradigm shifts recently, with several heterogeneous services and applications to the ultimate realization of connected living. In many status-sensitive IoT services, information usually has a higher value when it is fresher. A new metric, termed the age of information (AoI), was proposed to capture the freshness of status updates. In this paper, we propose a novel online control weight-based age-dependent activation control (W-ADAC) algorithm that prioritizes the activation of the devices that are divided into different classes possibly according to different AoI requirements. With the proposed W-ADAC, we introduce the concept of weighted AoI which is applied to control the activation probability of each device. In particular, higher weights are given to the devices that manifest higher priority requirements. As it is hard to obtain the system weighted AoI due to a lack of information on the distributed devices, we further introduce the capability of estimating the system weighted AoI into the proposed W-ADAC. Extensive simulations show the effectiveness of the proposed W-ADAC over multiple priorities and confirm that the proposed algorithm not only improves the overall system throughput but also provides the near-minimum AoI.

In recent years, homomorphisms have been exploited to compare the structures and properties of two generalized information systems. Some of these homomorphisms are based on consistent functions, which are a class of special mappings between universal sets. The purpose of this paper is to unify and extend the consistent functions in the literature into the framework of neighborhood systems. After introducing the notion of consistent functions with respect to neighborhood systems, we explore some important properties of the extended consistent functions such as preserving the inverse images and the intersections of neighborhoods. Our results provide a sound basis for further investigating neighborhood systems via homomorphisms.