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Objective Thoracolumbar fractures are one of the most common fractures in clinical practice. Surgical intervention is recommended to restore spinal alignment or decompress the nerves when there are unstable fractures or neurological injuries. However, after excessive forward thrust force restoration, facet joint dislocation often occurs between the upper vertebra and the fractured vertebra, which usually leads to unsatisfactory reduction outcomes. Herein, we propose a novel spinal facet joint toothed plate to assist in fracture reduction. The purpose of this study is to evaluate the effectiveness of the new spinal facet joint toothed plate in preventing facet joint dislocation, and its advantages compared to traditional pedicle screw‐rod decompression. Methods A total of 26 patients in the toothed plate group and 93 patients in the traditional group who experienced thoracolumbar fracture with reduction were retrospectively included. Relevant patients' information and clinical parameters were collected. Furthermore, visual analogue scores (VAS) scores and Oswestry disability index (ODI) scores were also collected. Moreover, imaging parameters were calculated based on radiographs. Correlated data were analyzed by χ2 test and t test. Results All patients in this study had no postoperative complications. Postoperative VAS scores and ODI scores (p

BackgroundHigher thyroid-stimulating hormone (TSH) amidst normal thyroid hormone (TH) levels may contribute to a negative impact on cardiovascular health (CVH). We sought to probe the associations between Life’s Essential 8 (LE8), a newly revised CVH evaluation, and low thyroid function among US adults.MethodsThe datasets from the 2007-2012 National Health and Nutrition Examination Survey (NHANES) were applied to the study. Low-normal thyroid function and subclinical hypothyroidism (SCH) were both regarded to be low thyroid function. Multivariable logistic regressions were utilized to inquire about the relationship between LE8 and low thyroid function.ResultsAmong the 6,315 participants (age ≥20 years), 1,375 (21.77%) were ascertained to be low thyroid function. After adjusting possible confounders, a higher LE8 score was linked to a lower probability of experiencing low thyroid function (Odds ratio [OR] for each 10-point increase: 0.923 [95% CI, 0.884-0.964]). A similar correlation was found between the health factors score and low thyroid function (OR for each 10-point increase: 0.905 [95% CI, 0.876-0.935]). Also, scoring better on physical activity (PA), body mass index (BMI), blood lipid, blood glucose (BG), and blood pressure (BP) may be conducive to reducing the rates of low thyroid function. Furthermore, subgroup and sensitivity analyses indicated that the negative correlations were generally robust.ConclusionsThe LE8 score and health factors score were nonlinearly and negatively related to the prevalence concerning low thyroid function. Promoting the regulation of optimum CVH levels could work on mitigating the load of low thyroid function and cardiovascular diseases (CVDs).

This paper investigates a backscatter communication (BackCom) non-orthogonal multiple access (NOMA) system with numerous base stations (BSs) and backscatter devices (BDs). The objective is to maximize sum uplink rate by adjusting reflection coefficients of BDs and establishing association policies between BSs and BDs. To achieve this, matching theory is utilized to address the association problem, and a quadratic transform iterative algorithm is employed to calculate optimal reflection coefficients under a given association policy. Meanwhile, hybrid successive interference cancellation (SIC) is applied to reduce the outage probability of the proposed system while optimizing the uplink sum data rate, where a low-complexity solution is developed. Simulation results validate the superiority of the proposed optimization scheme in enhancing uplink sum data rate. The comparison between BackCom NOMA and BackCom orthogonal multiple access (OMA) reveals superior performance of the former, which becomes increasingly evident as the number of BSs and BDs increases. The proposed iterative algorithm significantly enhances the system’s sum uplink data rate. The usage of hybrid SIC also notably declines the outage probability of the system.

Abstract Background Many patients during manual therapy after anterior ligament reconstruction will experience severe pain, which has a negative impact on their rehabilitation. However, there is rarely an analgesic method for these patients during rehabilitation. Nitrous oxide with rapid analgesic and sedative effects is often used to relieve pain in minor procedures. The purpose of this study is to determine whether or not nitrous oxide analgesia decreases pain compared to oxygen during manual therapy after anterior ligament reconstruction. Methods/design This single-center, randomized, double-blind and controlled trial will recruit 120 patients. Patients ≥ 18 years old undergoing manual therapy after anterior ligament reconstruction (1 month post-operative) with acute pain (VAS ≥ 4) are included. The main exclusion criteria included the following: pulmonary embolism, intestinal obstruction, pneumothorax. Patients will be randomly allocated to the intervention group (A) and the control group (B) in a ratio of 1:1. Doctors, therapists, patients, and data collectors are all blind to the study. The manual therapy will be performed by therapists. Nurses who implemented the intervention handed the doctors envelopes containing the patients’ codes and allocation of A or B. Group A will receive a pre-prepared nitrous oxide/oxygen mixture plus conventional treatment (no analgesic) given as 30-min treatment sessions, once daily, and group B will receive oxygen plus conventional treatment (no analgesic) under the same conditions. Assessments will be taken 2 min before the intervention (T0), 5 min after the beginning of the intervention (T1), and 5 min after the intervention finished (T2). The primary outcome is pain score. Secondary outcomes include vital signs, side effects, joint range of motion, adjuvant analgesia need, therapist and patient satisfaction, and whether willing to receive the same gas again. Expected outcomes We expect nitrous oxide inhalation to have a beneficial effect on the pain of patients who receive manual therapy after anterior ligament reconstruction. Discussion If this treatment appears beneficial, it could improve patients’ satisfaction and quality of life potentially and even be implemented widely in hospital and rehabilitation settings. Trial registration ClinicalTrials.gov identifier, ChiCTR2200061175 (Version 2.0 June 15, 2022), https://www.chictr.org.cn .

Previous studies have validated a close association between inflammatory factors and multiple sclerosis (MS), but their causal relationship is not fully profiled yet. This study used Mendelian randomization (MR) to investigate the causal effect of circulating inflammatory proteins on MS. Data from a large-scale genome-wide association study (GWAS) were analyzed using a two-sample MR method to explore the relationship between 91 circulating inflammatory proteins and MS. The inverse-variance-weighted (IVW) analysis was employed as the main method for evaluating exposures and outcomes. Furthermore, series of the methods of MR Egger, weighted median, simple mode, and weighted mode were used to fortify the final results. The results of the IVW method were corrected with Bonferroni (bon) and false discovery rate (fdr) for validating the robustness of results and ensuring the absence of heterogeneity and horizontal pleiotropy. The sensitivity analysis was also performed. The results of the forward MR analysis showed that higher levels of CCL25 were found to be associated with an increased risk of MS according to IVW results, OR: 1.085, 95% CI (1.011, 1.165), p = 2.42 × 10−2, adjusted p_adj_bon = 1, p_adj_fdr = 0.307. Similarly, higher levels of CXCL10 were found to be associated with an increased risk of MS, OR: 1.231, 95% CI (1.057, 1.433), p = 7.49 × 10−3, adjusted p_adj_bon = 0.682, p_adj_fdr = 0.227. In contrast, elevated levels of neurturin (NRTN) were associated with a decreased risk of MS, OR: 0.815, 95% CI (0.689, 0.964), p = 1.68 × 10−2, adjusted p_adj_bon = 1, p_adj_fdr = 0.307. Reverse MR analysis showed no causal relationship between MS and the identified circulating inflammatory cytokines. The effects of heterogeneity and level pleiotropy were further excluded by sensitivity analysis. This study provides new insights into the relationship between circulating inflammatory proteins and MS and brings up a new possibility of using these cytokines as potential biomarkers and therapeutic targets. The data in this study show that there are only weak associations between inflammatory molecules and MS risk, which did not survive bon and fdr correction, and the obtained p-values are quite low. Therefore, further studies on larger samples are needed.

ObjectiveCancer seriously endangers human health and represents a global public health issue. Cancer-related fatigue (CRF) is a distressing and persistent sense of exhaustion caused by cancer or cancer treatment, widely prevalent among cancer patients. This study aims to summarize emerging trends and provide directions for future research of CRF through bibliometric and visualization analyses.MethodsA systematic search in the Web of Science Core Collection database from 2001-01-01 to 2023-05-18 were conducted. Only reviews and articles written in English were considered. CiteSpace and the R were used for bibliometric and visualization analyses.ResultsThe analysis revealed that 2,566 studies on CRF have been published by 1,041 institutions in 70 countries so far. The number of articles published and cited annually have been steadily increasing. Eduardo Bruera published the most articles, and Julienne E Bower is the most co-cited author. The University of Texas System is the leading institution in cancer-related fatigue research. The United States and China have the largest number of publications. Supportive Care in Cancer published the most articles, and Journal of Clinical Oncology is the most co-cited journal. “Comparison of Pharmaceutical, Psychological, and Exercise Treatments for Cancer-Related Fatigue: A Meta-analysis”, authored by Mustian KM et al. and published in JAMA Oncology was the most co-cited document. Keyword analysis indicated that research focus had shifted from “epoetin alpha” and “anemia” to “risk factors”, “systematic review”, “acupuncture”, “anxiety”, “traditional Chinese medicine” and “guidelines”.ConclusionIn conclusion, this analysis provides comprehensive research trends and knowledge network maps of CRF. Clinical physicians should concurrently focus on the anemia, insomnia, anxiety, and depression status of patients when assessing or managing CRF. Improvements in related risk factors also contribute to alleviating fatigue. Furthermore, it is essential to pay attention to authoritative CRF guidelines. Acupuncture and traditional Chinese medicine also have therapeutic potential, which merits further investigation. Researchers should draw attention to the crucial roles of inflammation, hypoxia, and mitochondrial dysfunction, which could be the frontiers.

Unmanned Aerial Vehicle (UAV) communication is a promising technology that provides swift and flexible on-demand wireless connectivity for devices without infrastructure support. With recent developments in UAVs, spectrum and energy efficient green UAV communication has become crucial. To deal with this issue, Spectrum Sharing Policy (SSP) is introduced to support green UAV communication. Spectrum sensing in SSP must be carefully formulated to control interference to the primary users and ground communications. In this paper, we propose spectrum sensing for opportunistic spectrum access in green UAV communication to improve the spectrum utilization efficiency. Different from most existing works, we focus on the problem of spectrum sensing of randomly arriving primary signals in the presence of non-Gaussian noise/interference. We propose a novel and improved p-norm-based spectrum sensing scheme to improve the spectrum utilization efficiency in green UAV communication. Firstly, we construct the p-norm decision statistic based on the assumption that the random arrivals of signals follow a Poisson process. Then, we analyze and derive the approximate analytical expressions of the false-alarm and detection probabilities by utilizing the central limit theorem. Simulation results illustrate the validity and superiority of the proposed scheme when the primary signals are corrupted by additive non-Gaussian noise and arrive randomly during spectrum sensing in the green UAV communication.

Hashimoto’s thyroiditis (HT) is not only the most frequent autoimmune thyroid disease (AITD), but it also has a significant impact on patients’ health-related quality of life (HRQoL), and it has been variably associated with differentiated thyroid carcinoma. Even though its pathogenesis is still incompletely understood, oxidative stress is believed to play an important role. Hypothyroidism related to later stages of HT can be treated with levothyroxine substitution therapy; various approaches such as selenium supplementation and iodine-restricted diets have been proposed as disease-modifying treatments for earlier stages, and even thyroidectomy has been suggested for refractory cases of painful HT. Nevertheless, many patients still report suboptimal HRQoL, highlighting an unmet medical need in this area. The concepts and approaches of traditional Chinese medicine (TCM) in treating HT are not broadly known in the West. Here, we provide an overview of TCM for HT, including combinations of TCM with selenium. We encompass evidence from clinical trials and other studies related to complex TCM prescriptions, single herbs used in TCM, and phytochemicals; wherever possible, we delineate the probable underlying molecular mechanisms. The findings show that the main active components of TCM for HT have commonly known or presumed antioxidant and anti-inflammatory activities, which may account for their potential utility in HT. Further exploring the practices of TCM for HT and combining them with evidence- and mechanism-based approaches according to Western standards may help to identify new strategies to alter the clinical course of the disease and/or to treat patients’ symptoms better and improve their HRQoL.

This paper investigates a backscatter communication (BackCom) based non-orthogonal multiple access (NOMA) system in a multiple-input and single-output (MISO) scenario, where two decoding methods are deployed, including the sum-capacity approach and QR decomposition. The goal is to maximize energy efficiency (EE) through the optimization of the beamforming matrix and the reflection coefficient of the BackCom devices. Two algorithms, Dinkelbach based on penalty semidefinite relaxation (SDR) and successive convex approximation (SCA), are proposed as high-performance and low-complexity solutions, respectively. Simulation results indicate that the combination of the sum-capacity approach and Dinkelbach yields the best performance, though at the highest complexity, while the amalgamation of QR decomposition and SCA offers the lowest performance but with minimal complexity.

BackgroundPrevious studies have shown that there is a correlation between diseases of the thyroid gland and mental illnesses; however, any causal relationship between them remains unclear. This study aimed to evaluate the causal relationship between borderline personality disorder and four thyroid diseases.MethodsThe causal relationship was inferred using double-sample Mendelian randomization analysis of appropriate instrumental variables from genome-wide association studies. We calculated the estimated value of the effect using various statistical methods.ResultsBorderline personality disorder was a risk factor for non-toxic single thyroid nodules with each increase in standard deviation increasing the risk of a non-toxic single thyroid nodule by 1.13 times (odds ratio = 1.131; 95% confidence interval, 1.006-1.270; P=0.039). There was no evidence of a correlation between borderline personality disorder and hyperthyroidism/thyrotoxicosis, hypothyroidism, and autoimmune thyroiditis.ConclusionThis study showed that there is a positive causal correlation between borderline personality disorder and non-toxic single thyroid nodules but not with other thyroid diseases. This means that thyroid status should be monitored in patients with borderline personality disorder. However, the possibility of a causal relationship between other mental illnesses and thyroid diseases requires further research.

Non-orthogonal multiple access (NOMA) continues to receive enormous attention as a potential technique for improving the spectral efficiency (SE) of wireless networks. Although for several years most research efforts on the performance of NOMA systems focused on the ergodic sum-rate and outage probability, recent works have shifted towards error rate analysis of various NOMA configurations and designs. While the influx of publications on this topic is rich in lessons and innovations, the sheer volume of it makes it easy to get caught up in the details, so much so that one often loses sight of the overall picture. This paper serves as a survey on NOMA error rate analysis, painted in the large with bold and immediately recognizable strokes of insights to facilitate for the reader to understand and follow the up-to-date progress in this area. In addition to summarizing the principles of NOMA error rate analysis, this work aims to minimize redundancy and overlaps, identify research gaps, and outline future research directions.

Intelligent reflecting surface (IRS) has been recently integrated with emerging communication technologies to meet the demanding requirements of communication systems. This paper investigates the deployment of multi-IRS units in a hybrid time-domain multiple access (TDMA) and non-orthogonal multiple access (NOMA) system, referred to as a multi-IRS-aided hybrid TDMA-NOMA system. In particular, a self-sustainable scenario is proposed, in which the IRS units can harvest energy from the radio frequency signal to feed them-self with the required energy. With this self-sustainable IRS-aided hybrid TDMA-NOMA system, the available time is fragmented into a set of time slots, in which an IRS unit is assigned to serve a cluster of users during each time slot. Meanwhile, the remaining unassigned (i.e., idle) IRS units harvest energy to feed themselves with the required energy, which addresses the energy limitation challenge related to conventional communication systems. Specifically, we propose an efficient algorithm to group the users in clusters and, thus, assign an appropriate IRS unit for each cluster. To examine the capabilities of the proposed self-sustainable multi-IRS-aided hybrid TDMA-NOMA system, a resource allocation framework is formulated aiming to minimize the transmit power at the base station under a set of quality-of-service (QoS) constraints. Such QoS constraints include the minimum required rate for each user and the minimum harvested energy at each IRS. However, since the considered optimization problem is not convex, and the coupled nature of the design parameters (i.e., the per-user power allocation and per-IRS reflection phase matrix), solving such a problem is challenging. Thus, we develop an efficient iterative algorithm, based on the sequential convex approximation, to solve the original optimization problem. Simulation results reveal that the proposed self-sustainable IRS-aided TDMA-NOMA system with the proposed clustering approach and IRS assignment consumes less power while achieving the sustainability of IRS units compared to benchmark approaches.

Abstract While Doppler resilient complementary waveforms (DRCWs) have previously been considered to suppress range sidelobes within a Doppler interval of interest in radar systems, their ability to provide Doppler resilience can be further improved. A new singular value decomposition (SVD)‐based DRCW construction is proposed, in which both transmit pulse trains (made up of complementary pairs) and receive pulse weights are jointly considered. Besides, using the proposed SVD‐based method, a theoretical bound is derived for the range sidelobes within the Doppler interval of interest. Moreover, based on the SVD solutions, a challenging non‐convex optimization problem is formulated and solved to maximise the signal‐to‐noise ratio (SNR) with the constraint of low range sidelobes. It is shown that, compared with existing DRCWs, the proposed SVD‐based DRCW has better Doppler resilience. Further, the new optimised SVD‐based DRCW has a higher SNR while maintaining the same Doppler resilience.

BackgroundNitrous oxide (N2O) with rapid analgesic effect is often used to relieve pain induced by diagnostic procedures. This review was conducted to evaluate the efficacy and safety of N2O in patients undergoing puncture biopsy.MethodsWe systematically searched PubMed, Embase, the Cochrane Library, Web of Science, Scopus and the ClinicalTrials.gov up to March, 2022. Randomized controlled trials (RCTs) were included if they investigated the effect of N2O in adults undergoing puncture biopsy. The primary outcome was pain score. Secondary outcomes included anxiety score, patient satisfaction and side effects.ResultsTwelve RCTs with 1070 patients were included in the qualitative review, of which eleven RCTs were included in the meta-analysis. Pooled analysis suggested that compared with the controls (placebo, lidocaine and midazolam), N2O had better analgesic effect (MD -1.12, 95% CI -2.12 to -0.13, P = 0.03; I2 = 94%). In addition, N2O significantly alleviated patient anxiety (MD = -1.79, 95% CI -2.41 to -1.18, PConclusionThe present review suggested that N2O might be effective for pain management in patients undergoing puncture biopsy.

ObjectiveHashimoto’s thyroiditis (HT) is the most common type of thyroid disease and can cause many different manifestations. The local symptoms of HT are an under-studied area of research. Therefore, the purpose of this study was to investigate the local symptoms of HT and their prevalence.MethodsA systematic review was performed to find articles in PubMed that discuss the local symptoms of HT. Relevant vocabulary terms and key terms included: autoimmune thyroid disease (AITD), hyperthyroidism, hypothyroidism, neck, throat, pharynx, airway, esophagus, breathe, swallow, globus, sleep apnea, symptoms, and quality of life. Two investigators independently screened the eligible studies.ResultsA total of 54 articles fulfilled the inclusion criteria. Of these, 25 were clinical studies, 24 were case reports, and five were reviews. These clinical studies and case reports included a total of 2660 HT patients. There were eight local symptoms related to HT: neck pain (0.02%~16%), voice changes (7%~30%), throat discomfort (20%~43.7%), shortness of breath (28%~50%), dysphagia (29%), goiter-related symptoms (69.44%), sleep apnea, and generally defined compressive symptoms. Due to the use of different outcome measures among all the studies, a meta-analysis of the data could not be performed.ConclusionGoiter symptoms, which are an item on the ThyPRO scales, are the most frequent local symptoms in HT patients, and include neck pain, voice changes, throat discomfort, and dysphagia. These local symptoms should be identified in the clinic and included in the early diagnosis and management of HT, as well as evaluated further to understand their relevance in the pathogenesis of HT.

This study investigates the application of deep deterministic policy gradient (DDPG) to reconfigurable intelligent surface (RIS)-based unmanned aerial vehicles (UAV)-assisted non-orthogonal multiple access (NOMA) downlink networks. The deployment of UAV equipped with a RIS is important, as the UAV increases the flexibility of the RIS significantly, especially for the case of users who have no line-of-sight (LoS) path to the base station (BS). Therefore, the aim of this study is to maximize the sum-rate by jointly optimizing the power allocation of the BS, the phase shifting of the RIS, and the horizontal position of the UAV. The formulated problem is non-convex, the DDPG algorithm is utilized to solve it. The computer simulation results are provided to show the superior performance of the proposed DDPG-based algorithm.

Objective In order to realize the intelligent navigation and autonomous collision avoidance of unmanned ships in coastal areas, an intelligent collision avoidance decision-making method based on driving practice is proposed. Method First, the real-time rationality and uniqueness of the unmanned ship intelligent collision avoidance decision-making process is analyzed. The ontology conceptual model of the navigation situation is then designed and combined with the international regulations for preventing collisions at sea (COLREGS) and good seamanship practices, and the ship encounter scenarios are quantitatively divided into 12 types. An improved composite collision risk index assessment model is then proposed from the perspective of piloting practice to reflect collision risk more accurately. Finally, an intelligent collision avoidance decision-making model based on operator's perspective (BOP) is established, and the optimal collision avoidance strategy is solved by taking the shortest total collision avoidance path as the objective function under the constraints of ship maneuverability and rudder angle amplitude limit. Simulation experiments are then conducted in different obstacle environments. Results The simulation results show that this method can accurately determine the piloting situation, provide a reasonable steering strategy and achieve effective collision avoidance in different obstacle environments. Conclusion This study provides a theoretical basis and method for realizing the intelligent collision avoidance decision-making and dynamic local collision avoidance path planning of ships.

Voting is one of the most prominent components of democracy. The one-vote veto, which requires the voting result to be only “yes” or “no”, is a particularly noteworthy type of voting with widespread application. When obtaining a “no” result, no useful information about the number of “no” votes and who votes “no” is disclosed. In this paper, we introduce a protocol for anonymous one-vote veto utilizing qubits and local Pauli operations $\mathbb {Z}$ and $\mathbb {X}$ , building simple processes for easy implementation under the current technology. For better elaboration, we give two examples: all voters cast “yes” votes and only one voter casts a “no.” Then, the corresponding experiment tests are conducted on the simulated IBM quantum computer to verify their feasibility. We also show that the proposed protocol has the desirable properties of privacy, fairness, verifiability and robustness. Furthermore, we analyze the proposed protocol’s security against cheating from eavesdroppers, a semi-honest server and malicious voters. This work is the first attempt to illustrate how qubits can be useful for building a secure anonymous one-vote veto strategy.

In this paper, we propose a joint beamforming and power-splitter optimization technique for simultaneous wireless power and information transfer in the downlink transmission of a multiple-input single-output (MISO) non-orthogonal multiple access (NOMA) system. Accordingly, each user employs a power splitter to decompose the received signal into two parts, namely, the information decoding and energy harvesting. The former part is used to decode the corresponding transmitted information, whereas the latter part is utilized for harvesting energy. For this system model, we solve an energy harvesting problem with a set of design constraints at the transmitter and the receiver ends. In particular, the beamforming vector and the power splitting ratio for each user are jointly designed such that the overall harvested power is maximized subject to minimum per-user rate requirements and the available power budget constraints at the base station. As the formulated problem turns out to be non-convex in terms of the design parameters, we propose a sequential convex approximation technique and demonstrate a superior performance compared to a baseline scheme.

Multi-access Edge Computing (MEC) is an essential technology for expanding computing power of mobile devices, which can combine the Non-Orthogonal Multiple Access (NOMA) in the power domain to multiplex signals to improve spectral efficiency. We study the integration of the MEC with the NOMA to improve the computation service for the Beyond Fifth-Generation (B5G) and the Sixth-Generation (6G) wireless networks. This paper aims to minimize the energy consumption of a hybrid NOMA-assisted MEC system. In a hybrid NOMA system, a user can offload its task during a time slot shared with another user by the NOMA, and then upload the remaining data during an exclusive time duration served by Orthogonal Multiple Access (OMA). The original energy minimization problem is non-convex. To efficiently solve it, we first assume that the user grouping is given, and focuses on the one group case. Then, a multilevel programming method is proposed to solve the non-convex problem by decomposing it into three subproblems, i.e., power allocation, time slot scheduling, and offloading task assignment, which are solved optimally by carefully studying their convexity and monotonicity. The derived solution is optimal to the original problem by substituting the closed expressions obtained from those decomposed subproblems. Furthermore, we investigate the multi-user case, in which a close-to-optimal algorithm with low-complexity is proposed to form users into different groups with unique time slots. The simulation results verify the superior performance of the proposed scheme compared with some benchmarks, such as OMA and pure NOMA.

This paper considers the design of beamforming for orthogonal time frequency space modulation assisted non-orthogonal multiple access (OTFS-NOMA) networks, in which a high-mobility user is sharing the spectrum with multiple low-mobility NOMA users. In particular, the beamforming design is formulated as an optimization problem whose objective is to maximize the low-mobility NOMA users' data rates while guaranteeing that the high-mobility user's targeted data rate can be met. Both the cases with and without channel state information errors are considered, where low-complexity solutions are developed by applying successive convex approximation and semidefinite relaxation. Simulation results are also provided to show that the use of the proposed beamforming schemes can yield a significant performance gain over random beamforming.

The Proliferation of connected and embedded devices has played a critical role in the development of next generation Internet of Things (IoT), and consequently, the diffusion of low power networks. The sustainability of such networks entails energy aware devices that are capable of self-sustainable operations by harvesting and recycling energy from various sources. Accordingly, integration of wireless-powered networks (WPN) with ambient backscatter communications (AmBC), in which a backscatter transmitter conveys data to a destination by backscattering ambient signals, has recently emerged as a promising key technology for low power wireless networks. However, these technologies are not optimized and/or designed for large-scale networks and a massive number of IoT devices.

Driven by the emergence of new compute-intensive applications and the vision of the Internet of Things (IoT), it is foreseen that the emerging 5G network will face an unprecedented increase in traffic volume and computation demands. However, end users mostly have limited storage capacities and finite processing capabilities, thus how to run compute-intensive applications on resource-constrained users has recently become a natural concern. Mobile edge computing (MEC), a key technology in the emerging fifth generation (5G) network, can optimize mobile resources by hosting compute-intensive applications, process large data before sending to the cloud, provide the cloud-computing capabilities within the radio access network (RAN) in close proximity to mobile users, and offer context-aware services with the help of RAN information. Therefore, MEC enables a wide variety of applications, where the real-time response is strictly required, e.g., driverless vehicles, augmented reality, robotics, and immerse media. Indeed, the paradigm shift from 4G to 5G could become a reality with the advent of new technological concepts. The successful realization of MEC in the 5G network is still in its infancy and demands for constant efforts from both academic and industry communities. In this survey, we first provide a holistic overview of MEC technology and its potential use cases and applications. Then, we outline up-to-date researches on the integration of MEC with the new technologies that will be deployed in 5G and beyond. We also summarize testbeds and experimental evaluations, and open source activities, for edge computing. We further summarize lessons learned from state-of-the-art research works as well as discuss challenges and potential future directions for MEC research.

Unmanned aerial vehicles (UAVs) with the potential of providing reliable high-rate connectivity, are becoming a promising component of future wireless networks. A UAV collects data from a set of randomly distributed sensors, where both the locations of these sensors and their data volume to be transmitted are unknown to the UAV. In order to assist the UAV in finding the optimal motion trajectory in the face of the uncertainty without the above knowledge whilst aiming for maximizing the cumulative collected data, we formulate a reinforcement learning problem by modelling the motion-trajectory as a Markov decision process with the UAV acting as the learning agent. Then, we propose a pair of novel trajectory optimization algorithms based on stochastic modelling and reinforcement learning, which allows the UAV to optimize its flight trajectory without the need for system identification. More specifically, by dividing the considered region into small tiles, we conceive state-action-reward-state-action (Sarsa) and Q-learning based UAV-trajectory optimization algorithms (i.e., SUTOA and QUTOA) aiming to maximize the cumulative data collected during the finite flight-time. Our simulation results demonstrate that both of the proposed approaches are capable of finding an optimal trajectory under the flight-time constraint. The preference for QUTOA vs. SUTOA depends on the relative position of the start and the end points of the UAVs.

Orthogonal multiple access (OMA) technologies have prevailed from the first-generation (1G) to the fourth-generation (4G) of modern mobile communications, primarily because of their low complexity. The key idea of OMA is to ensure that the communication resources allocated to different users are orthogonal in at least one radio resource dimension. As a result, the number of active users allowed to access the OMA system is strictly limited by the number of available orthogonal resources, which becomes less effective for supporting massive connectivity and achieving user fairness. In contrast to OMA, non-orthogonal multiple access (NOMA) simultaneously accommodates a multitude of users using the same radio resource block via superposition signaling and employs various transmit or receive signal processing techniques to mitigate the resulting interference. However, the success of NOMA technologies relies heavily on the implementation of advanced signal processing techniques for transceivers, which may introduce large processing delays and increase computational complexity. Thanks to recent progress in hardware and theory in signal processing and machine learning, high signal processing complexity has become more affordable and processing latency can be significantly reduced, which enables the development of NOMA. Thus, sophisticated signal processing algorithms for multi-user detection, scheduling, and interference management are indispensable for the successful implementation of NOMA in the next-generation wireless systems.

To satisfy the explosively increasing demands for high-speed data applications and massive access requirements of various Internet-of-thing (IoT) devices, a whole package of performance requirements has been proposed for the fifth-generation (5G) mobile communication system. Motivated by the necessity of network architecture enhancement, a paradigm of fog radio access networks (F-RANs) has emerged as a promising evolution path for 5G network architecture. In F-RANs, a fog-computing layer is formed at the edge of networks, and parts of service requirements can be responded to locally without interacting with the cloud computing center via the fronthaul links. Therefore, by taking full advantage of distributed caching and centralized processing, F-RANs provide great flexibility to satisfy quality-of-service (QoS) requirements of various 5G scenarios. F-RAN has become a research hotspot and draws a lot of attention from both academia and industry. As it integrates with artificial intelligence and other new emerging technologies, 5G is facing new challenges, and the study of F-RANs is entering a new era as well.

In this paper, we investigate the secure transmission in multigroup multicasting cell-free massive MIMO system in the presence of pilot spoofing attack. With the imperfect uplink and downlink channel estimation, a distributed conjugate beamforming processing with normalized power constraint policy is exploited at access points (APs) for downlink multicasting data transmission. Closed-form expressions for the per-user achievable rate are derived with and without downlink training, respectively. Also, the analytical results of the upper bound on the information leakage to eavesdropper are carried out. Moreover, a mechanism based on the minimum description length (MDL) is presented to detect pilot spoofing attack. Consequently, the achievable ergodic secrecy rate is obtained to evaluate the system's secrecy performance. The numerical results are presented to quantitatively analyze the impacts of eavesdropper's spoofing pilot power and the number of groups on the secrecy performance of the considered systems.

We investigate the physical-layer security of an uplink wireless time-division multiple-access channel with energy-harvesting source nodes. We consider a set of source nodes equipped with rechargeable batteries and information buffers communicating confidentially with a base station, Bob, in the presence of a passive eavesdropper, Eve. An energy-harvesting rechargeable-battery cooperative jammer is assumed to assist the source nodes to confidentially send their information messages. We propose a two-level optimization formulation to improve the system's security performance. At the first optimization level, we propose a jamming scheme under energy constraints at different nodes to reduce the secrecy outage probabilities without relying on the eavesdropper's instantaneous channel state information. At the second optimization level, we optimize the number of energy packets used at the source nodes and the cooperative jammer as well as the time-slot allocation probabilities to maximize the secure throughput under the network's queues stability constraints and an application-specific secure throughput for each legitimate source node. The numerical results show the significant performance gains of our proposed optimization relative to two important benchmarks. We verify our theoretical findings through simulations and quantify the impact of key system design parameters on the security performance.

Harvesting energy from the surrounding environment is an important and practical solution to prolong the life of the energy-constrained Internet-of-Things (IoT) devices, e.g., wireless sensors. Visible light communications (VLC) has been proved able to provide high-speed data links while meeting the illumination requirement. Thereby, the energy of VLC signals may be harvested by the energy-constrained IoT terminals, such as indoor sensors and portable/wearable devices. This paper presents the concept of simultaneous lightwave information and power transfer (SLIPT) with a particular focus on the design of the receiver and the practical methods to realize SLIPT in the domains of time, signal components, and photoelectric converters. Furthermore, this paper also introduces the applications of SLIPT to various network topologies and communication technologies, e.g., multiple input multiple output, hybrid VLC-radio frequency, and secure communications. Finally, a detailed discussion of future research directions and challenges for the design of SLIPT systems is also presented.

Satellite communication networks are expected to be indispensable as part of an integrated complement for the upcoming 5G networks since they can provide the most comprehensive coverage and reliable connection for areas where are economically unviable and/or difficult to deploy terrestrial infrastructures. Meanwhile, the power-domain non-orthogonal multiple access (NOMA), which can serve multiple users simultaneously within the same time/frequency block, has been viewed as another promising strategy used in the 5G network to provide high spectral efficiency and resource utilization. In this paper, we introduce a general overview of the application of the NOMA to various satellite architectures for the benefits of meeting the availability, coverage, and efficiency requirements targeted by the 5G. The fundamental and ubiquitous features of satellite link budget are first reviewed. Then, the advantage and benefit of introducing the NOMA scheme in various satellite architectures, such as conventional downlink/uplink satellite networks, cognitive satellite terrestrial networks, and cooperative satellite networks with satellite/terrestrial relays, are provided, along with the motivation and research methodology for each scenario. Finally, this paper reviews the potential directions for future research.

The millimeter wave (mmWave) frequency band will become a key enabler for future wireless systems currently facing the explosive growth of data traffic and the sparsity of the traditional ultra-high frequency (UHF) band. Nevertheless, the challenges for mmWave communications lie in high propagation loss, sensitivity to blockage, high cost for equipping directional antennas, and so on. Furthermore, the traditional design for the UHF networks cannot be directly used for future mmWave networks, which needs to be reshaped from the perspectives of fundamental objectives, various constraints, and different degrees of freedom. This paper addresses the key functions and discusses the challenges for PHY layer and MAC layer design in mmWave small-cell networks, including mmWave antenna design, beamforming, initial access, radio resource allocation, power allocation, and so on. The novel resource management approach for the joint PHY-MAC layer design is proposed to find the trade-off among hardware cost of the mmWave antenna, beamforming overhead, and efficiency of the new resource block (RB) allocation in beam-frequency-time (B-T-F)-dimension.

In this paper, we investigate different secrecy energy efficiency (SEE) optimization problems in a multiple-input single-output underlay cognitive radio (CR) network in the presence of an energy harvesting receiver. In particular, these energy efficient designs are developed with different assumptions of channels state information (CSI) at the transmitter, namely perfect CSI, statistical CSI and imperfect CSI with bounded channel uncertainties. In particular, the overarching objective here is to design a beamforming technique maximizing the SEE while satisfying all relevant constraints linked to interference and harvested energy between transmitters and receivers. We show that the original problems are non-convex and their solutions are intractable. By using a number of techniques, such as non-linear fractional programming and difference of concave (DC) functions, we reformulate the original problems so as to render them tractable. We then combine these techniques with the Dinkelbach's algorithm to derive iterative algorithms to determine relevant beamforming vectors which lead to the SEE maximization. In doing this, we investigate the robust design with ellipsoidal bounded channel uncertainties, by mapping the original problem into a sequence of semidefinite programs by employing the semidefinite relaxation, non-linear fractional programming and S-procedure. Furthermore, we show that the maximum SEE can be achieved through a search algorithm in the single dimensional space. Numerical results, when compared with those obtained with existing techniques in the literature, show the effectiveness of the proposed designs for SEE maximization.

This paper investigates the application of non-orthogonal multiple access (NOMA) and device-to-device (D2D) into the scenario of massive Machine Type Communications (mMTC). Specifically, we first propose a new NOMA-and-D2D integrated network, where NOMA is utilized to deal with the cross-tier and co-tier interference at the base station side. To fully exploit the advantages of the network, we formulate a joint channel allocation and power control problem with the objective to maximize the performance of the D2D communications under the constraints of the rate requirements of the cellular users. For solving the formulated problem efficiently, we first adopt the sequential convex approximation method to solve the channel allocation subproblem, and then transform the power control subproblem into a convex optimization problem. To further reduce the computational complexity, we employ the convolutional neural network (CNN) to devise a resource management framework, where the relation between the system states and the control policies is established by multiple neurons. Finally, simulation results indicate that the convex approximation based algorithm outperforms the other algorithms in terms of utility, sum-rate, and user satisfaction, and the CNN based algorithm achieves orders of magnitude speedup in computational time with only slight loss of performance.

This paper investigates a cooperative uplink system where two users wish to send messages to a base station with the help of a buffer-aided relay. Transmission modes in terms of both non-orthogonal multiple access (NOMA) and orthogonal multiple access (OMA) are considered. For the considered system, the probability for the user-to-relay channels to successfully perform NOMA is first theoretically derived in two scenarios of dynamic and fixed power controls (PCs) at users. Then, an efficient buffer-aided hybrid NOMA/OMA based mode selection (MS) scheme is proposed, which adaptively switches between the NOMA and OMA transmission modes according to the instantaneous strength of wireless channels and the buffer state. The state transmission matrix probabilities of the corresponding Markov chain is also derived, and the performance of the proposed hybrid NOMA/OMA scheme is analyzed with closed-form expressions, in terms of sum throughput, outage probability, diversity gain, and average packet delay. For both the dynamic and fixed PCs, the proposed scheme is proved to achieve a diversity gain of two when the buffer size is not smaller than three, which means that fixed PC will not lead to a loss of diversity gain.

This paper proposes a novel location-based multi-group multicast framework, which is termed non-orthogonal multiple access (NOMA)-assisted multi-region geocast. This novel spectrum sharing framework exploits the NOMA technology to realize the simultaneous delivery of different messages to different user groups characterized by different geographical locations. The essence of the proposed framework is that the geographical information of user groups unites NOMA and multi-group multicast to enhance the spectral efficiency (SE) and the energy efficiency (EE) of wireless transmissions. Specifically, we investigate the downlink beamforming design of the proposed framework in multiple-input single-output settings. The decoding strategy for NOMA is designed and guaranteed by users' geographical information and required quality of service. The majorization and minimization algorithm is exploited to solve the non-convex and intractable problems therein. Comprehensive numerical experiments are further provided to show that NOMA holds tremendous promise but also limitations in terms of SE and EE, compared with spatial division multiple access and orthogonal multiple access.

We consider a two-user multi-relay cooperative non-orthogonal multiple access (NOMA) network with distributed space-time coding. Two dual-relay selection strategies are proposed for cooperative NOMA, namely, two-stage dual relay selection with fixed power allocation (DRS-FPA) and two-stage dual relay selection with dynamic power allocation (DRS-DPA). Furthermore, lower and upper bounds on the outage probability for the DRS-FPA scheme and the exact outage probability for the DRS-DPA scheme are obtained in closed-form, respectively. Numerical results show that the proposed two-stage DRS schemes not only yield better outage performance than the existing single relay selection schemes without sacrificing spectral efficiency, but can also achieve full diversity gain.

Non-orthogonal multiple access (NOMA) has been recently recognized as a promising multiple access technique to significantly improve the spectral efficiency of mobile communication networks. The key idea of NOMA is to encourage spectrum sharing, which is similar to the concept of cognitive radio networks. Take power domain NOMA as an example, where the power domain is used for multiple access. This is fundamentally different from the previous generations of mobile networks which have been relying on the time/frequency/code domain. It is worth mentioning that NOMA has been demonstrated to be compatible with many 5G techniques. Thus, the purpose of this Special Section in IEEE Access was to provide a forum for the latest research and innovations in NOMA technologies as well as their applications, and to bridge the gap between theory and practice in the design of 5G multiple access. We received a total of 29 submissions, and after a rigorous review process, 13 articles have been selected for publication, which are briefly discussed next.

With technological advancements, future wireless communications networks are expected to incorporate densely deployed base stations serving tens of billions of low-power wireless devices, in order to enable emerging Internet-of-Things (IoT) applications. However, this leads to a dramatic increase in energy cost at the wireless network, and makes it a difficult task to efficiently power massive wireless devices. Therefore, how to reduce the energy cost at the network side and also provide sustainable energy supply at the wireless device side become two increasingly important issues for the success of IoT. Recently, energy harvesting (EH) from ambient sources (e.g., solar and wind) and dedicated wireless power transfer (WPT) via radio frequency (RF) signals have emerged as appealing solutions to power base stations and low-power wireless devices. Such techniques have several promising advantages over the traditional grid/battery-powered systems, such as improved energy efficiency, reduced energy and maintenance costs, prolonged lifetime, and even perpetual and uninterrupted operations. Hence, EH wireless communications and wireless powered communications have attracted signifficant interests recently from both academia and industry.

Multi-access edge computing (MEC) and non-orthogonal multiple access (NOMA) are regarded as promising technologies to improve the computation capability and offloading efficiency of mobile devices in the sixth-generation (6G) mobile system. This paper mainly focused on the hybrid NOMA-MEC system, where multiple users were first grouped into pairs, and users in each pair offloaded their tasks simultaneously by NOMA, then a dedicated time duration was scheduled to the more delay-tolerant user for uploading the remaining data by orthogonal multiple access (OMA). For the conventional NOMA uplink transmission, successive interference cancellation (SIC) was applied to decode the superposed signals successively according to the channel state information (CSI) or the quality of service (QoS) requirement. In this work, we integrated the hybrid SIC scheme, which dynamically adapts the SIC decoding order among all NOMA groups. To solve the user grouping problem, a deep reinforcement learning (DRL)-based algorithm was proposed to obtain a close-to-optimal user grouping policy. Moreover, we optimally minimized the offloading energy consumption by obtaining the closed-form solution to the resource allocation problem. Simulation results showed that the proposed algorithm converged fast, and the NOMA-MEC scheme outperformed the existing orthogonal multiple access (OMA) scheme.

Physical layer security has been recently recognized as a promising new design paradigm to provide security in wireless networks. In addition to the existing conventional cryptographic methods, physical layer security exploits the dynamics of fading channels to enhance secured wireless links. In this approach, jamming plays a key role by generating noise signals to confuse the potential eavesdroppers, and significantly improves quality and reliability of secure communications between legitimate terminals. This article presents theoretical limits and practical designs of jamming approaches for physical layer security. In particular, the theoretical limits explore the achievable secrecy rates of user cooperation-based jamming whilst the centralized and game theoretic-based precoding techniques are reviewed for practical implementations. In addition, the emerging wireless energy harvesting techniques are exploited to harvest the required energy to transmit jamming signals. Future directions of these approaches and the associated research challenges are also briefly outlined.

The multi-tier heterogeneous network (HetNet) architecture can potentially address the massive connectivity and high throughput demands of the emerging fifth generation (5G) of wireless networks. However, the inter-tier interference in HetNets is considered to be a major performance bottleneck. This paper proposes a geometry-based three-dimensional (3-D) stochastic channel model for the spatial characterization of the sum interference in a two-tier HetNet with small cells in tier-1 overlaid with massive multiple-input-multiple-output equipped macro-cell base stations in tier-2. The angular spreads of the interference and the desired signals are analyzed by using the theory of 3-D multipath shape-factors and analytical expressions are derived for their second-order fading statistics, viz: level-crossing-rate (LCR), average-fade-duration (AFD), spatial autocovariance, and the coherence distance. Further, analytical expressions to investigate the second-order fading statistics against signal-to-interference ratio are also derived. The validation of the derived analytical expressions is established through a comparison with computer-based simulations. To provide insights into the network sum interference mechanism, the LCR and AFD expressions are derived for the special case when the rate of fluctuation of the desired signal is much higher than that of the interference signal and vice versa. Furthermore, the impact of the model's physical parameters, such as the link distance and the receiver's direction of motion as well as the fading distribution parameters such as its intensity and shape factors on the fading statistics of the interference are evaluated. These results demonstrate that the elevation angle has a significant impact on the interference characterization in HetNet architectures such that it cannot be ignored in modeling emerging 5G communication scenarios.

This paper investigates the coexistence between two key enabling technologies for fifth generation (5G) mobile networks, non-orthogonal multiple access (NOMA), and millimeter-wave (mmWave) communications. Particularly, the application of random beamforming to mmWave-NOMA systems is considered in order to avoid the requirement that the base station know all the users' channel state information. Stochastic geometry is used to characterize the performance of the proposed mmWave-NOMA transmission scheme by using key features of mmWave systems, i.e., that mmWave transmission is highly directional and potential blockages will thin the user distribution. Two random beamforming approaches that can further reduce the system overhead are also proposed, and their performance is studied analytically in terms of sum rates and outage probabilities. Simulation results are also provided to demonstrate the performance of the proposed schemes and verify the accuracy of the developed analytical results.

This paper proposes three game-theoretic approaches for coalition formation in cooperative networks with simultaneous wireless information and power transfer. To improve the reception reliability of destinations with poor channel conditions, we first divide destinations in the network into two types: Type I and Type II. Type I destinations refer to the destinations with capability of successful information decoding and energy harvesting, which serve as relays to help other destinations. Type II destinations have poor connections to the source and hence compete to obtain help from Type I destinations. Accordingly, cooperative relaying strategies for the two types of destinations are proposed on the basis of coalition formation game. First, we propose to utilize the dynamic programming (DP) approach to obtain the optimal coalition structure in the network, though at the cost of heavy time and storage complexity. Then, two distributed hedonic coalition formation (DHCF) approaches are developed to generate coalition structures, which are more efficient than the DP approach. Simulation results show that all proposed approaches outperform the non-cooperative one (i.e., direct link transmission). The results also illustrate that the DP approach achieves the largest data rate and lowest outage probability for destinations, and the DHCF approaches achieve near-to-optimal performance.

A feature of the Internet of Things (IoT) is that some users in the system need to be served quickly for small packet transmission. To address this requirement, a new multiple-input multiple-output non-orthogonal multiple access (MIMO-NOMA) scheme is designed in this paper, where one user is served with its quality of service requirement strictly met, and the other user is served opportunistically by using the NOMA concept. The novelty of this new scheme is that it confronts the challenge that the existing MIMO-NOMA schemes rely on the assumption that users' channel conditions are different, a strong assumption which may not be valid in practice. The developed precoding and detection strategies can effectively create a significant difference between the users' effective channel gains, and therefore, the potential of NOMA can be realized even if the users' original channel conditions are similar. Analytical and numerical results are provided to demonstrate the performance of the proposed MIMO-NOMA scheme.

In this paper, downlink beamforming (BF) for hybrid non-orthogonal multiple access (NOMA) systems is considered, in order to combat inter and intra cluster interference. First, to minimize the inter- and intra-cluster interference, the projection hybrid NOMA (PH-NOMA) BF algorithm is introduced, by combining conventional zero-forcing BF (ZFBF) and hybrid NOMA (H-NOMA) precoding. Second, to further reduce the overall interference, two user pairing algorithms, termed projection-based pairing algorithm (PBPA) and inversion-based pairing algorithm (IBPA), are also proposed, by adopting the properties of quasi-degradation developed previously. Consequently, the proposed BF algorithm is obtained by combining PH-NOMA and PBPA/IBPA. Moreover, the system performance in terms of outage probability and diversity is analyzed for both the proposed BF algorithms and conventional ZFBF. Finally, computer simulations are conducted to demonstrate the efficiency of the proposed BF algorithms and to validate the correctness of the performance analysis.

In this paper, we first study the average sum rate of sparse code multiple access (SCMA) systems, where a general scenario is considered under the assumption that the distances between the mobile users and the base station are not necessarily identical. Closed-form analytical results are derived for the average sum rate based on which an optimal factor graph matrix is designed for maximizing the capacity of the SCMA systems. Moreover, we propose a low-complexity iterative algorithm to facilitate the design of the optimal graph matrix. Finally, Monte Carlo simulations are provided to corroborate the accuracy of the theoretical results and the efficiency of the proposed iterative algorithm.

Consider a simple two-way relaying channel in which two single-antenna sources exchange information via a multiple-antenna relay. For such a scenario, all the existing approaches that can achieve full cooperative diversity order are based on antenna/relay selection, for which the difficulty in designing the beamforming lies in the fact that a single beamformer needs to serve two destinations. In this paper, a new full-cooperative diversity beamforming scheme that ensures that the relay signals are coherently combined at both destinations is proposed, and analytical results are provided to demonstrate the performance gains. Moreover, the impact of channel estimation error is also evaluated. Finally, numerical results are provided to verify the accuracy of the provided analytical results, and also to show that this proposed scheme can outperform existing schemes based on antenna selection.

This paper proposes a joint energy efficiency (EE) and spectrum efficiency (SE) tradeoff analysis as a multi-objective optimization problem (MOP) in the uplink of multi-user multi-carrier two-tier orthogonal frequency division multiplexing access heterogeneous networks subject to users' maximum transmission power and minimum rate constraints. The proposed MOP is modeled such that the network providers can dynamically tune the tradeoff parameters to switch between different communication scenarios with diverse design requirements. In order to find its Pareto optimal solution, the MOP is transformed, using a weighted sum method, into a single-objective optimization problem (SOP), which itself can further be transformed from a fractional form, by exploiting fractional programming, into a subtractive form. Since the formulated SOP is hard to solve due to the combinatorial channel allocation indicators, we reformulate the SOP into a better tractable problem by relaxing the combinatorial indicators using the idea of time-sharing. We then prove that this reformulated SOP is strictly quasi-concave with respect to the transmission power and the subcarrier allocation indicator. We then propose an iterative two-layer distributed framework to achieve an upper bound Pareto optimal solution of the original proposed MOP. The numerical simulations demonstrate the effectiveness of our proposed two-layer framework achieving an upper bound Pareto optimal solution, which is very close to an optimal solution, with fast convergence, lower and acceptable polynomial complexity, and balanced EE-SE tradeoff.

In this paper, a new evaluation criterion is developed to investigate the performance of non-orthogonal multiple access (NOMA) from an information theoretic point of view. In particular, the relations among the capacity region of the broadcast channel and two rate regions achieved by NOMA and time-division multiple access (TDMA) are first illustrated. Based on these relations, a new evaluation criterion is proposed for NOMA in wireless fading scenarios, where the key idea is to compare NOMA with TDMA statistically in terms of not only the sum rate but also the individual rates. In a wireless downlink scenario with user pairing, the developed analytical results show that NOMA can outperform TDMA not only in terms of the sum rate but also in terms of each user's individual rate, particularly when the difference between the users' channels is large. The optimal power allocation for a special case of NOMA user pairing is also established.