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This paper studies the estimation of low-rank multiple-input multiple-output (MIMO) wideband channels in orthogonal frequency division multiplexing (OFDM) systems which are commonly considered for high-frequency wireless communications, e.g., at millimeter wave (mmWave) and Terahertz (THz) bands. To reduce the overhead for channel estimation, we propose a novel solution based on two-fold sampling of the original channel matrix. A subchannel associated with a subset of subcarriers and antennas is first selected by deterministic sampling. Low-rank matrix completion (LRMC) based on random sampling is then used to further reduce the training overhead. Utilizing the Toeplitz structure of the covariance matrices of uniform linear arrays, the angles and delays are then estimated separately at low complexities using super-resolution algorithms. Finally, the path gains are estimated and associated with the path angles and delays, followed by the extrapolation of the full-dimensional channel. As only a small number of antennas and subcarriers are required in the training, the overall training overhead and computational complexity are very low. Numerical results demonstrate that the proposed two-fold sampling-based estimator can achieve high-accuracy channel estimation. Besides, the sampling patterns and complexity of the proposed estimator are analysed, which shows that the proposed solution can be configured to provide different performance-complexity tradeoffs.

Wireless body area networks (WBANs) can provide continuous monitoring of human biological signals. Due to the limited energy of the sensors, wireless-powered system has been adopted to prolong network lifetime for implant WBANs. In this paper, we propose an energy buffer-aided wireless-powered relaying system for self-sustainable implant WBAN. The proposed system is composed of an off-body access point (AP) and many users, where an implant device is placed in body while a dual-mode wearable device with an energy buffer is attached on body for each user. In the downlink, the dual-mode wearable device simultaneously harvests energy that is stored in the energy buffer from a radio-frequency signal broadcasted by the AP and provides energy supply via wireless energy transfer to the implant device. In the uplink, the implant device uses harvested energy to transmit its collected data to the wearable device. Then the wearable device adopts the stored energy to decode and forward the data to the AP in an orthogonal multiple access way. We investigate two transmission policies for the wearable device, namely best-effort policy (BEP) and on-off policy (OOP). We derive the limiting distribution of the energy for both the BEP and OOP. Furthermore, the outage probability and average throughput of the proposed system with both the BEP and OOP are analyzed. Simulation results are presented to validate the analytical expressions and provide some useful insights.

To remotely monitor the physiological status of the human body, long range (LoRa) communication has been considered as an eminently suitable candidate for wireless body area networks (WBANs). Typically, a Rayleigh-lognormal fading channel is encountered by the LoRa links of the WBAN. In this context, we characterize the performance of the LoRa system in WBAN scenarios with an emphasis on the physical (PHY) layer and medium access control (MAC) layer in the face of Rayleigh-lognormal fading channels and the same spreading factor interference. Specifically, closed-form approximate bit error probability (BEP) expressions are derived for the LoRa system. The results show that increasing the spreading factor (SF) and reducing the interference efficiently mitigate the shadowing effects. Moreover, in the quest for the most suitable MAC protocol for LoRa based WBANs, three MAC protocols are critically appraised, namely the pure ALOHA, slotted ALOHA, and carrier-sense multiple access. The coverage probability, energy efficiency, throughput, and system delay of the three MAC protocols are analyzed in Rayleigh-lognormal fading channel. Furthermore, the performance of the equal-interval-based and equal-area-based schemes is analyzed to guide the choice of the SF. Our simulation results confirm the accuracy of the mathematical analysis, and provide some useful insights for the future design of LoRa based WBANs on how to achieve the desired performance requirements for different conditions (i.e., different network radii and average numbers of end-devices) by using different SF allocation schemes and MAC protocols.

In this paper, we consider a dual-band communication system, where a base station (BS) can communicate with a user equipment (UE) over either the sub-6GHz band or the millimeter wave (mmWave) band. We consider the joint detection of the blockage status of the BS-UE link and the optimization of the downlink rate through frequency band scheduling and beamforming design. Typically, the blockage detection requires the transmission and detection of an echo signal, and the downlink beamforming design relies on the estimation of the channel state information (CSI) of the downlink sub-6GHz and mmWave bands, the acquisition of which may result in high complexity and large overhead. To address these problems, we investigate solving the problem using only the CSI of the uplink sub-6GHz band. We decompose the problem into a blockage detection sub-problem and a beamforming design sub-problem. For the former sub-problem, we propose an efficient algorithm based on the convolutional neural network (CNN) technique. For the latter sub-problem, we propose an algorithm based on the MobileNetV2 module to achieve a high learning efficiency. Simulation results show that the proposed blockage detection algorithm can achieve over 99% detection accuracy, and the proposed beamforming design algorithm can achieve over 10% downlink rate gain, as compared to several benchmark schemes.

Abstract Purpose Based on the recycling principle, returning of tobacco crop residues into the field is a common agronomic practice. However, comprehensive knowledge about the effects of tobacco plant residue return on the rhizosphere soil microbial community is very limited. Methods After tobacco crop residue returning into the potted soil, 16S ribosomal RNA (rRNA) and internal transcribed spacer (ITS) amplicon sequencing were employed to investigate the bacterial and fungal communities, respectively, from the tobacco rhizosphere soils. Results The results showed that tobacco residue returning increased the diversity of microbial communities (bacteria and fungi) and changed the species composition. It further increased the relative abundance of beneficial microorganisms. After tobacco residue returning, the structure of the rhizosphere soil microbial community network was found more complex with strong interactions among microbial species. In addition, the keystone species of bacterial and fungal communities associated with tobacco rhizosphere soil were altered. This had exerted a driving force to the beneficial bacteria such as Sphiningomonas and Psathyrella to the keystone microorganisms which played important roles in microbial species interaction. Conclusions Tobacco residue return into soil showed significant effects on the microbial diversity, community composition, network structure, keystone microorganisms, and ecosystem functions of tobacco rhizosphere soils. This study provides a scientific basis for the improvement of tobacco field ecosystem functioning and ensuring soil health.

Upcoming beyond fifth generation (5G) communications systems aim at further enhancing key performance indicators and fully supporting brand-new use cases by embracing emerging techniques, e.g., reconfigurable intelligent surface (RIS), integrated communication, localization, and sensing, and mmWave/THz communications. The wireless intelligence empowered by state-of-the-art artificial intelligence techniques has been widely considered at the transceivers, and now the paradigm is deemed to be shifted to the smart control of radio propagation environment by virtue of RISs. In this paper, we argue that to harness the full potential of RISs, localization and communication must be tightly coupled. This is in sharp contrast to 5G and earlier generations, where localization was a minor additional service. To support this, we first introduce the fundamentals of RIS mmWave channel modeling, followed by RIS channel state information acquisition and link establishment. Then, we deal with the connection between localization and communications, from a separate and joint perspective.

The introduction of sparse code multiple access (SCMA) is driven by the high expectations for future cellular systems. In traditional SCMA receivers, the message passing algorithm (MPA) is commonly employed for received-signal decoding. However, the high computational complexity of the MPA falls short in meeting the low latency requirements of modern communications. Deep learning (DL) has been proven to be applicable in the field of signal detection with low computational complexity and low bit error rate (BER). To enhance the decoding performance of SCMA systems, we present a novel approach that replaces the complex operation of separating codewords of individual sub-users from overlapping codewords using classifying images and is suitable for efficient handling by lightweight graph neural networks. The eigenvalues of training images contain crucial information, such as the amplitude and phase of received signals, as well as channel characteristics. Simulation results show that our proposed scheme has better BER performance and lower computational complexity than other previous SCMA decoding strategies.

In this article, a graph-theoretic method (taking advantage of constraints among sets associated with the corresponding parity-check matrices) is applied for the construction of a double low-density parity-check (D-LDPC) code (also known as LDPC code pair) in a joint source-channel coding (JSCC) system. Specifically, we pre-set the girth of the parity-check matrix for the LDPC code pair when jointly designing the two LDPC codes, which are constructed by following the set constraints. The constructed parity-check matrices for channel codes comprise an identity submatrix and an additional submatrix, whose column weights can be pre-set to be any positive integer numbers. Simulation results illustrate that the constructed D-LDPC codes exhibit significant performance improvement and enhanced flexible frame length (i.e., adaptability under various channel conditions) compared with the benchmark code pair.

BackgroundThe dementia epidemic is progressing fast. As the world’s older population keeps skyrocketing, the traditional incompetent, time-consuming, and laborious interventions are becoming increasingly insufficient to address dementia patients’ health care needs. This is particularly true amid COVID-19. Instead, efficient, cost-effective, and technology-based strategies, such as sixth-generation communication solutions (6G) and artificial intelligence (AI)-empowered health solutions, might be the key to successfully managing the dementia epidemic until a cure becomes available. However, while 6G and AI technologies hold great promise, no research has examined how 6G and AI applications can effectively and efficiently address dementia patients’ health care needs and improve their quality of life. ObjectiveThis study aims to investigate ways in which 6G and AI technologies could elevate dementia care to address this study gap. MethodsA literature review was conducted in databases such as PubMed, Scopus, and PsycINFO. The search focused on three themes: dementia, 6G, and AI technologies. The initial search was conducted on April 25, 2021, complemented by relevant articles identified via a follow-up search on November 11, 2021, and Google Scholar alerts. ResultsThe findings of the study were analyzed in terms of the interplay between people with dementia’s unique health challenges and the promising capabilities of health technologies, with in-depth and comprehensive analyses of advanced technology-based solutions that could address key dementia care needs, ranging from impairments in memory (eg, Egocentric Live 4D Perception), speech (eg, Project Relate), motor (eg, Avatar Robot Café), cognitive (eg, Affectiva), to social interactions (eg, social robots). ConclusionsTo live is to grow old. Yet dementia is neither a proper way to live nor a natural aging process. By identifying advanced health solutions powered by 6G and AI opportunities, our study sheds light on the imperative of leveraging the potential of advanced technologies to elevate dementia patients’ will to live, enrich their daily activities, and help them engage in societies across shapes and forms.

Solving the satisfiability problems of Boolean polynomial equations is still an open challenge in the fields of mathematics and computer science. In this paper, our goal is to propose a non-algebraic method for solving maximal Boolean polynomial equations (Max-PoSSo problem). By leveraging channel coding theory and dynamic programming, we propose three deterministic and robust algorithms for solving the satisfiability problems of Boolean polynomial equations. Comparisons are made among the three proposed algorithms and Genetic and Gröbner algorithms. Simulation results show that the proposed algorithms exhibit better performance in terms of the largest number of Boolean polynomials equal to 0 compared to the benchmark schemes in the literature.

Distributed Luby transform (DLT) codes achieve a significant performance improvement in multi-source relay networks compared with the individual Luby transform (LT) code designed for each source. Since the DLT codes preserve the properties of the LT codes, the error floor is dominated by the low variable-node degrees in the bipartite graph, developed for iterative message passing decoding. Therefore, we analyze the error floor of the DLT codes for a multi-source, single relay, and a single destination network over additive white Gaussian noise (AWGN) channels. We modify the encoding process at the sources and propose a new relay combining scheme at the relay. The encoding process at the sources and the combining scheme at the relay are coordinated with the aim of improving the error floor performance of the proposed DLT codes. We derive a lower bound of the bit error probability of the DLT codes over AWGN channels. Furthermore, we optimize the relay degree distribution in terms of the overhead by using the framework of extrinsic information transfer chart analysis. The numerical results confirm that the proposed DLT coding scheme significantly outperforms the conventional scheme, especially in the error floor region.

We theoretically analyze outage probabilities of the lossy-forward (LF), decode-andforward (DF), and adaptive decode-and-forward (ADF) relaying techniques, with the aim of characterizing the impact of the spatial and temporal correlations of the fading variations. First, the exact outage probability expressions are analytically obtained for LF, DF, and ADF relaying assuming each link suffers from statistically independent Rayleigh fading. Then, approximated, yet accurate closed-form expressions of the outage probabilities for the relaying schemes are derived. Based on the expressions, diversity and coding gains are found. The mathematical methodology for the derivation of the explicit outage probability is further extended to the case, where the account is taken of the spatial and temporal correlations of the fading variations. The diversity gains with LF, DF, and ADF are then derived in the presence of the correlations. It is found out that the three techniques can achieve full diversity, as long as the fading variations are not fully correlated. We then investigate the optimal relay location and the optimal power allocation for the three relaying techniques. It is shown that the optimal solutions can be obtained under the framework of convex optimization. It is revealed that in correlated fading, the relay should move close to the destination or allocate more transmit power to the relay for achieving lower outage probabilities, compared with the case in independent fading.