We study irregular repetition slotted ALOHA (IRSA) with multi-antenna reception over Rayleigh block fading channels. An exact closed-form expression for the average decoding error probability ¯ϵm,L is derived for collision sizes m = 1 and m = 2 by applying the inclusion–exclusion principle, which generalizes known single-antenna results and remains valid for any finite number of antennas. Using this result, we develop a density-evolution-based analysis of multi-antenna IR-SA systems and characterize belief-propagation (BP) thresholds. Numerical results for the corresponding maximum a posteriori (MAP) decoding thresholds and converse bounds are also presented, demonstrating threshold saturation with spatial coupling.

This paper explores the optimization of transmission probability and code rate in multi-device slotted ALOHA systems employing successive interference cancellation (SIC) and feedback over Nakagami- m fading channels. Although previous research has derived the optimal probability and the code rate to maximize the sum rate in a two-device scenario analytically using Markov process, its extension to configurations with more than two devices remains challenging. The complexity of Markov modeling arises from two main challenges: 1) an increase in the number of devices greatly expands the state space, precluding the analytical determination of system throughput; 2) deriving transition probabilities in the Nakagami- m channel model is difficult. In this study, we use computer simulations to evaluate the sum rate and to search for the optimal transmission probability and code rate to maximize the sum rate of the systems. Our simulation findings reveal that at an average SNR the optimal code rate is independent of the number of devices and transmission probability. In a 30-device slotted ALOHA system with an SNR of 15 dB, the maximum sum rate of 2.9235 is almost achieved at a transmission probability of 0.0665 and an optimal code rate of approximately 4.02, regardless of the number of devices.

We examine a neural network-based system designed to identify$K$devices, each with device-specific I/Q imbalances in the RF modulator, as they transmit signals to an access point using time-division multiple access. Traditional methods begin training with randomly chosen initial parameters and need numerous pilot symbols, which can be impractical in scenarios such as when a unmanned aerial vehicle (UAV) serves as the access point, collecting data from massive device sensor networks. In this work, we focus on adaptive learning with minimal pilot symbols to train the neural network to classify devices by their I/Q imbalances. Reptile is an efficient meta-learning algorithm designed to help models rapidly adjust to new tasks with minimal training data. By employing Reptile, we pre-train neural network model parameters offline, facilitating rapid online adaptation and fine-tuning for effective identification of new devices. Simulations indicate that Reptile surpasses conventional methods in device identification with fewer pilot symbols.

In wireless communication systems, the presence of inter-symbol interference (ISI), resulting from multipath propagation and channel memory, poses a significant challenge to reliable symbol detection and message recovery. A blind estimation of the ISI channel with a memory length-$L$is proposed. In the receiver, the iterative$K$-means clustering algorithm is used for this blind channel estimation process and a cyclic redundancy check (CRC) is employed to ultimately validate the recovered message. The algorithm produces$K^{L}$potential sets of channel taps as a consequence of channel phase uncertainties caused by phase rotation. Subsequently, these are reduced to$K$sets using the squared error comparison between the received and the reconstructed symbols. The transmitted message is subsequently obtained using these$K$candidate channel tap sets through Viterbi demodulation, channel decoding, and verification of CRC. The simulation results show that for the ISI channel with a dominant line-of-sight component, the block error rate of the proposed approach is close to that of a perfectly known channel, yet it nearly aligns with the performance of the conventional MMSE estimator utilizing a few pilot symbols.

Throughput analysis for successive interference cancellation-based two-device slotted ALOHA with feedback is studied over Nakagami-m fading channels. Explicit expressions for the state transition probabilities are derived for a Markov process, thus facilitating the computation of the throughput. Through optimization of the transmission probability, it is shown that the maximum throughput is achieved for a given code rate.

In wireless power transfer (WPT) systems, multiple-input single-output (MISO) signal processing enhances the power transfer efficiency by optimizing array antenna weight vectors according to channel coefficients between the transmitter and receivers. In a MISO-based WPT system, a time division multiplexing (TDM) scheduling should be jointly optimized; transmitter periodically switches weight vectors for receivers by assigning a time slot to each weight vector. This paper proposes a receiver grouping strategy for TDM scheduling to improve the fairness and efficiency of the WPT system. Receivers with correlated channel conditions are classified into a group because the transferred energy with a beamforming weight directed to a certain receiver is supplied to other receivers, which is called beneficial interference. Beamforming weight vectors are derived to maximize the harvested energy of each group. The time slots duration assigned to weight vectors is then optimized to maximize the minimum harvested energy among receivers. The simulation experiments in an indoor multipath environment reveal that the proposed method improves the minimum and average harvested energy.

Immediately after the occurrence of a natural disaster, communication infrastructures used in daily life become temporarily unavailable. Under such a situation, intermittently connected mobile ad hoc networks (MANETs) play an important role in providing post-disaster networking. While previous studies on such networks have mainly focused on one-to-one messaging applications, the importance of monitoring applications has become increasingly important in recent years. For monitoring applications, the key performance measure is given by the freshness of the information, rather than the traditional delay characteristics. In this paper, we present a mathematical analysis of the age of information (AoI) for intermittently connected MANETs, which captures the information freshness of monitoring applications. We further investigate basic principles in the network design based on the analytical results obtained. In particular, we discuss the AoI-energy tradeoff from different perspectives of source and relay nodes.

Optical wireless communication is a promising technology for underwater broadband access networks, which are particularly important for high-resolution environmental monitoring applications. This paper focuses on a deep-sea monitoring system, where an underwater optical wireless network is deployed on the seafloor. We model such an optical wireless network as a general queueing network and formulate an optimal relay placement problem, whose objective is to maximize the stability region of the whole system, i.e., the supremum of the traffic volume that the network is capable of accommodating. The formulated optimization problem is further shown to be non-convex, so that its global optimization is non-trivial. In this paper, we develop a global optimization method for this problem and we provide an efficient algorithm to compute an optimal solution. Through numerical evaluations, we show that a significant performance gain can be obtained by using the derived optimal solution.

The performance of the quasi-cyclic low-density parity-check (QC-LDPC) coded partial-access interleave division multiple access (IDMA) systems is evaluated with the SNR (signal-to-noise ratio) evolution algorithm. The partial access IDMA system is the IDMA system in which the 0s, i.e., non-energy transmission, are inserted into the chip sequence. The SNR evolution algorithm is developed and employed to evaluate the systems. Numerical and simulation results show that the partial access has better BER (bit error rate) performance than that of the conventional full access in a range of low Eb/N0, and the proposed IDMA system with the 3GPP NR QC-LDPC codes has a good error-floor performance.

A partial-access scheme is proposed for coded-IDMA (interleave-division multiple-access) systems. Similar to conventional IDMA systems, the transmitter of each user consists of a concatenation of channel encode, spreading, and user-specific interleaving. The only difference is that after spreading, some 0s are inserted into the chip sequence. Among the transmitted symbols of -1, 0, 1, symbol 0, however, implies a non-energy transmission or non-access to the channel. In the IDMA receiver, we use a customary joint iterative decoding based on a single factor graph. In our proposed IDMA systems, partial access not only greatly decreases the complexity of the joint decoding; it also decreases the number of short loops in the factor graph. Our extrinsic information transfer (EXIT) analysis and bit-error-rate (BER) simulations show that the proposed partial-access scheme outperforms conventional full-access-IDMA systems in a low SNR range.

In this paper, we consider a detection method against fake messages in sparse mobile ad-hoc networks, where nodes are temporally isolated. In these networks, messages are delivered to their destination nodes using store-carry-forward routing, where they are relayed by some nodes. Therefore, when a node has messages in its buffer, it can easily rewrite them. When there exist malicious nodes in the network, they can alter messages to fake message and launch fake message attacks, spreading the fake messages over the network. In this paper, we first model system dynamics as a continuous-time absorbing Markov chain, and clarify how fake message attacks affect the system performance using Markov analysis. We then propose a detection method that uses the hash value of messages. Whenever a node that has a message and its hash value encounters another node, it forwards only one of them to that node. By doing so, the message and its hash value are delivered to the destination node via different paths. Through simulation experiments, we show the effectiveness of our proposed method.

In sparsely populated mobile ad-hoc networks, store-carry-forward routing is one of the most important techniques. In order to avoid buffer overflows, any store-carry-forward routing must be incorporated with a buffer management scheme when the buffer size is limited. The goal of efficient buffer management policies minimizes the number of messages undelivered to destination nodes. For achieving this goal, we propose a novel buffer management policy based on message rarity. Giving high priority to rare message, i.e., the number of the original message and its copies being only one, the proposed scheme can avoid the extinction of messages in the network as long as possible. Through simulation experiments with a real trace data, we show the performance evaluation of a store-carry-forward routing with the proposed buffer management policy and the effectiveness of the proposed scheme.

We have proposed a new visible light Orthogonal Frequency Division Multiplex (OFDM) system using the Constant Amplitude Zero Auto-Correlation (CAZAC) equalization. In visible light systems, LEDs or LDs in transmitters have small dynamic range of input signal magnitude for linear operation and the bias current must be carefully set to consider the maximum allowable forward current of LEDs or LDs, to reduce magnitude distortion and to control signal clipping. The OFDM enables the limited frequency bandwidth of LEDs or LDs to be fully-used and the CAZAC equalization drastically reduces magnitude fluctuation of OFDM time-domain signal. We found that one CAZAC sequence in cooperation with IFFT process converts the PAPR of the M-Quadrature Amplitude Modulation (QAM) OFDM signal into the PAPR of an M-QAM single-carrier signal. This fact is our new discovery. Moreover, since the CAZAC equalization has potential capacities of frequency diversity effect, the system has an advantage in improvement of the BER performance under frequency selective fading environments, which also includes the frequency-dependent attenuation due to the frequency response of LEDs and LDs. Furthermore, we verified for 16QAM-OFDM and 16PSK-OFDM, and confirmed that the communication distance is much extended by the CAZAC.

We propose a probabilistic store-carry-forward message delivery scheme based on node density estimation. In our scheme, when a node with a message copy encounters another node, the former forwards its copy to the latter with a certain probability. The forwarding probability is determined depending on a node density at the contact location where two nodes encounter. More specifically, when the node density is high, the forwarding probability is set to be low. This policy is designed to avoid excess message copy transmissions in a high node-density area. In general, nodes frequently encounter each other in high node-density areas and message copies rapidly spread over the nodes. In order to determine whether the node density is high or not, each node estimates the node density distribution over the whole network based on the contact location information. The information is collected by each node and exchanged among nodes. With simulation experiments, we evaluate the performance of our scheme in terms of the mean delivery delay and the number of forwarded message copies.