Minimizing Age of Collection for Multiple Access in Wireless Industrial Internet of Things

This paper investigates the information freshness of Industrial Internet of Things (IIoT) systems, where each IoT device makes a partial observation of a common target and transmits the information update to a central receiver to recover the complete observation. We consider the age of collection (AoC) performance as a measure of information freshness. Unlike the conventional age of information (AoI) metric, the instantaneous AoC decreases only when all cooperative packets for a common observation are successfully received. Hence, effectively allocating wireless time-frequency resources among IoT devices to achieve a low average AoC at the central receiver is paramount. Three multiple access schemes are considered in this paper: time-division multiple access (TDMA) without retransmission, TDMA with retransmission, and frequency-division multiple access (FDMA). First, our theoretical analysis indicates that TDMA with retransmission outperforms the other two schemes in terms of average AoC. Subsequently, we implement information update systems based on the three schemes on software-defined radios. Experimental results demonstrate that considering the medium access control (MAC) overhead in practice, FDMA achieves a lower average AoC than TDMA with or without retransmission in the high signal-to-noise ratio (SNR) regime. In contrast, TDMA with retransmission provides a stable and relatively low average AoC over a wide SNR range, which is favorable for IIoT applications. Overall, we present a theoretical-plus-experimental investigation of AoC in IIoT information update systems

Low-Power Random Access for Timely Status Update: Packet-based or Connection-based?

This paper investigates low-power random access protocols for timely status update systems with age of information (AoI) requirements. AoI characterizes information freshness, formally defined as the time elapsed since the generation of the last successfully received update. Considering an extensive network, a fundamental problem is how to schedule massive transmitters to access the wireless channel to achieve low network-wide AoI and high energy efficiency. In conventional packet-based random access protocols, transmitters contend for the channel by sending the whole data packet. When the packet duration is long, the time and transmit power wasted due to packet collisions is considerable. In contrast, connection-based random access protocols first establish connections with the receiver before the data packet is transmitted. Intuitively, from an information freshness perspective, there should be conditions favoring either side. This paper presents a comparative study of the average AoI of packet-based and connection-based random access protocols, given an average transmit power budget. Specifically, we consider slotted Aloha (SA) and frame slotted Aloha (FSA) as representatives of packet-based random access and design a request-then-access (RTA) protocol to study the AoI of connection-based random access. We derive closed-form average AoI and average transmit power consumption formulas for different protocols. Our analyses indicate that the use of packet-based or connection-based protocols depends mainly on the payload size of update packets and the transmit power budget. In particular, RTA saves power and reduces AoI significantly, especially when the payload size is large. Overall, our investigation provides insights into the practical design of random access protocols for low-power timely status update systems

Semantic Communication-Empowered Physical-layer Network Coding

In a two-way relay channel (TWRC), physical-layer network coding (PNC) doubles the system throughput by turning superimposed signals transmitted simultaneously by different end nodes into useful network-coded information (known as PNC decoding). Prior works indicated that the PNC decoding performance is affected by the relative phase offset between the received signals from different nodes. In particular, some "bad" relative phase offsets could lead to huge performance degradation. Previous solutions to mitigate the relative phase offset effect were limited to the conventional bit-oriented communication paradigm, aiming at delivering a given information stream as quickly and reliably as possible. In contrast, this paper puts forth the first semantic communication-empowered PNC-enabled TWRC to address the relative phase offset issue, referred to as SC-PNC. Despite the bad relative phase offsets, SC-PNC directly extracts the semantic meaning of transmitted messages rather than ensuring accurate bit stream transmission. We jointly design deep neural network (DNN)-based transceivers at the end nodes and propose a semantic PNC decoder at the relay. Taking image delivery as an example, experimental results show that the SC-PNC TWRC achieves high and stable reconstruction quality for images under different channel conditions and relative phase offsets, compared with the conventional bit-oriented counterparts

Channel Cycle Time: A New Measure of Short-term Fairness

This paper puts forth a new metric, dubbed channel cycle time (CCT), to measure the short-term fairness of communication networks. CCT characterizes the average duration between two consecutive successful transmissions of a user, during which all other users successfully accessed the channel at least once. In contrast to existing short-term fairness measures, CCT provides more comprehensive insight into the transient dynamics of communication networks, with a particular focus on users' delays and jitter. To validate the efficacy of our approach, we analytically characterize the CCTs for two classical communication protocols: slotted Aloha and CSMA/CA. The analysis demonstrates that CSMA/CA exhibits superior short-term fairness over slotted Aloha. Beyond its role as a measurement metric, CCT has broader implications as a guiding principle for the design of future communication networks by emphasizing factors like fairness, delay, and jitter in short-term behaviors

Device Activity Detection in mMTC with Low-Resolution ADC: A New Protocol

This paper investigates the effect of low-resolution analog-to-digital converters (ADCs) on device activity detection in massive machine-type communications (mMTC). The low-resolution ADCs induce two challenges on the device activity detection compared with the traditional setup with assumption of infinite ADC resolution. First, the codebook design for signal quantization by the low-resolution ADCs is particularly important since a good codebook design can lead to small quantization error on the received signal, which in turn has significant influence on the activity detector performance. To this end, prior information about the received signal power is needed, which depends on the number of active devices $K$. This is sharply different from the activity detection problem in traditional setups, in which the knowledge of $K$ is not required by the BS as a prerequisite. Second, the covariance-based approach achieves good activity detection performance in traditional setups while it is not clear if it can still achieve good performance in this paper. To solve the above challenges, we propose a communication protocol that consists of an estimator for $K$ and a detector for active device identities: 1) For the estimator, the technical difficulty is that the design of the ADC quantizer and the estimation of $K$ are closely intertwined and doing one needs the information/execution from the other. We propose a progressive estimator which iteratively performs the estimation of $K$ and the design of the ADC quantizer; 2) For the activity detector, we propose a custom-designed stochastic gradient descent algorithm to estimate the active device identities. Numerical results demonstrate the effectiveness of the communication protocol.Comment: Submitted to IEEE for possible publicatio

An Ultra-fast Quantum Random Number Generation Scheme Based on Laser Phase Noise

Based on the intrinsic random property of quantum mechanics, quantum random number generators allow for access of truly unpredictable random sequence and are now heading towards high performance and small miniaturization, among which a popular scheme is based on the laser phase noise. However, this scheme is generally limited in speed and implementation complexity, especially for chip integration. In this work, a general physical model based on wiener process for such schemes is introduced, which provides an approach to clearly explain the limitation on the generation rate and comprehensively optimize the system performance. We present an insight to exploit the potential bandwidth of the quantum entropy source that contains plentiful quantum randomness with a simple spectral filtering method and experimentally boost the bandwidth of the corresponding quantum entropy source to 20 GHz, based on which an ultra-fast generation rate of 218 Gbps is demonstrated, setting a new record for laser phase noise based schemes by one order of magnitude. Our proposal significantly enhances the ceiling speed of such schemes without requiring extra complex hardware, thus effectively benefits the corresponding chip integration with high performance and low implementation cost, which paves the way for its large-scale applications.Comment: 25 pages, 7 figure