Association of Brain Arterial Elongation With Risk of Stroke and Death in Stroke-Free Individuals: Results From NOMAS.

BACKGROUND: Brain arterial dilation and elongation characterize dolichoectasia, an arteriopathy associated with risk of stroke and death. We aim to determine whether brain arterial elongation increases the risk of stroke and death independent of brain arterial diameters. METHODS: We analyzed 1210 stroke-free participants (mean age 71±9 years, 41% men, 65% Hispanic) with available time-of-flight magnetic resonance angiogram from the Northern Manhattan Study, a population-based cohort study across a multiethnic urban community. We obtained baseline middle cerebral artery M1-segment (MCA-M1) and basilar artery (BA) mean lengths and diameters using a semi-automated software. Cox proportional hazards models adjusted for brain arterial diameters and potential confounders yielded adjusted hazards ratios with 95% CIs for the primary outcomes of incident stroke and all-cause mortality, as well as secondary outcomes including noncardioembolic stroke, vascular death, and any vascular event. RESULTS: Neither MCA-M1 nor BA lengths correlated with incident stroke or all-cause mortality. Both MCA-M1 and BA larger diameters correlated with all-cause mortality (MCA-M1 aHR, 1.52 [95% CI, 1.03-2.23], BA aHR, 1.28 [95% CI, 1.02-1.61]), as well as larger MCA-M1 diameters with vascular death (aHR, 1.84 [95% CI, 1.02-3.31]). Larger MCA-M1 and BA diameters did not correlate with incident stroke. However, larger BA diameters were associated with posterior circulation noncardioembolic stroke (aHR, 2.93 [95% CI, 1.07-8.04]). There were no statistical interactions between brain arterial lengths and diameters in relation to study outcomes. CONCLUSIONS: In a multiethnic cohort of stroke-free adults, brain arterial elongation did not correlate with risk of stroke or death, nor influenced the significant association between brain arterial dilation and vascular risk.

Are sucking patterns and early spontaneous movements related to later developmental functioning outcomes? A cohort study.

Sucking patterns and early spontaneous movements have an important role in the determination of later developmental problems, but the relationship of the two together with long-term outcomes has not been investigated. The objectives of this study were to (i) examine the relationship between sucking patterns using the Neonatal Oral Motor Assessment Scale (NOMAS) and fidgety movements and other movement patterns using detailed General Movements Assessment (GMA), and (ii) investigate the relationship between these early assessment methods and developmental functioning outcomes at later ages. We analyzed the NOMAS from 34 weeks' postmenstrual age up to 10 weeks post-term and GMA between 9 and 20 weeks post-term age, and the Bayley Scales of Infant and Toddler Development-Third Edition (Bayley-III) was applied for the developmental functioning outcomes to 62 infants (61%, 62/102) between 12 and 42 months of age. Among 102 infants at-risk, 70 (69%) showed a normal sucking pattern, and 85 (83%) had fidgety movements. The median Motor Optimality Score-Revised (MOS-R), as determined by GMA, of all infants was 24. The NOMAS was related to the MOS-R and its subcategories (p < 0.05) in all infants at-risk. The NOMAS, MOS-R and its subcategories were also related to cognitive, language, and motor development at later ages according to Bayley-III (p < 0.05).   Conclusion: This longitudinal study showed that the quality of sucking patterns, fidgety movements, and MOS-R were related to later developmental functioning, indicating that abnormal sucking patterns, aberrant fidgety movements, and lower MOS-R might predict developmental disorders. What is Known: • Sucking patterns and early spontaneous movements in which central pattern generators play an important role are related. • Sucking patterns and early spontaneous movements might be used separately to predict developmental outcomes. What is New: • Sucking patterns and early spontaneous movements, when used together, were related to later developmental functioning, including cognitive, language, and motor development in at-risk infants. • Predictive value of sucking patterns was lower for each developmental functioning outcome than early spontaneous movements.

Prevalence and associated risk factors for noma in Nigerian children: a systematic review and meta-analysis.

OBJECTIVES: To determine the prevalence, case-fatality rate, and associated risk-factors of Noma in children in Nigeria. METHODS: Search was conducted in PubMed, Google Scholar, and Cochrane Library databases. Data were extraction using a double-blind approach. Discrepancies were resolved by a third reviewer. Heterogeneity was evaluated using I2 statistics. Random-effects model was used for the meta-analysis and subgroup analysis was conducted. The study quality was evaluated using standard Critical-Appraisal-Checklist. RESULTS: Of the 1652 articles identified, 12 studies that met the inclusion criteria included 871 cases of Noma. Two studies had high-risk of bias and were excluded in the meta-analysis. Pooled prevalence of Noma was 2.95% (95%CI:2.19-3.71; Z = 7.60; p < 0.00001, I2:100.0). Case fatality was reported in one study. Sex-distribution had a male-to-female ratio of 1.1:1. Malnutrition (88.42%, 95%CI:52.84-124.00; I2:100.0), measles (40.60%; 95% CI:31.56-49.65; I2:100.0) and malaria (30.75%; 95% CI:30.06-31.45; I2:100.0) were the most notable associated risk-factors. Prevalence of Noma was non-significantly lower in southern (1.96%,95%CI:1.49-2.44;6 studies) than in northern (4.43%; 95%CI:-0.98-9.83; 4 studies) Nigeria. One study reported the prevalence of Noma in children younger than 5 years. CONCLUSIONS: About every 3 in 100 children in Nigeria had Noma and the prevalence was non-significantly higher in northern than southern Nigeria. Malnutrition, measles, and malaria were major associated risk-factors. Case-fatality rate and prevalence based on different age-groups were inconclusive.

Immune Markers Are Associated With Asymptomatic Intracranial Large Artery Stenosis and Future Vascular Events in NOMAS.

BACKGROUND: Inflammation contributes to atherosclerosis but is incompletely characterized in intracranial large artery stenosis (ICAS). We hypothesized that immune markers would be associated with ICAS and modify the risk ICAS confers on future vascular events. METHODS: This study included a subsample of stroke-free participants in the prospective NOMAS (Northern Manhattan Study), who had blood samples analyzed with a 60-plex immunoassay (collected from 1993 to 2001) and ICAS assessment with time-of-flight magnetic resonance angiography (obtained from 2003 to 2008). We dichotomized ICAS as either ≥50% stenosis or not (including no ICAS). We ascertained post-magnetic resonance imaging vascular events. We used least absolute shrinkage and selection operator procedures to select immune markers independently associated with ICAS. Then, we grouped selected immune markers into a derived composite Z score. Using proportional odds regression, we quantified the association of the composite immune marker Z score, ICAS, and risk of vascular events. RESULTS: Among 1211 participants (mean age, 71±9 years; 59% women; 65% Hispanic participants), 8% had ≥50% ICAS. Using least absolute shrinkage and selection operator regression, we identified CXCL9 (C-X-C motif chemokine ligand 9), HGF (hepatocyte growth factor), resistin, SCF (stem cell factor), and VEGF-A(vascular endothelial growth factor A) to have the strongest positive relationships with ≥50% ICAS in fully adjusted models. Selected markers were used to derive a composite immune marker Z score. Over an average follow-up of 12 years, we found that each unit increase in immune marker Z scores was associated with an 8% (95% CI, 1.05-1.11), 11% (95% CI, 1.06-1.16), and 5% (95% CI, 1.01-1.09) increased hazard of death, vascular death, and any vascular event, respectively, in adjusted models. We did not find a significant interaction between immune marker Z scores and ICAS in their relationship with any longitudinal outcome. CONCLUSIONS: Among a diverse stroke-free population, selected serum immune markers were associated with ICAS and future vascular events. Further study is needed to better understand their role in the pathogenesis of ICAS and as a potential therapeutic target in stroke prevention.

Physical Activity Is Inversely Associated With Severe Intracranial Stenosis in Stroke-Free Participants of NOMAS.

BACKGROUND: Although protective in secondary stroke prevention of intracranial arterial stenosis (ICAS), it is uncertain if the benefits of leisure time physical activity (LTPA) extend to asymptomatic ICAS or extracranial carotid stenosis (ECAS). Therefore, we sought to determine LTPA's relationship with ECAS and ICAS in a stroke-free, race-ethnically diverse cohort. METHODS: This cross-sectional study included participants from the magnetic resonance imaging substudy of the Northern Manhattan Study, of whom 1274 had LTPA assessments at enrollment. LTPA was represented continuously as metabolic equivalent score (MET-score) and ordinally as model-based cluster analysis (LTPA-cluster), both based on the same LTPA assessments. We evaluated ECAS sonographically using carotid intima-media thickening and number of carotid plaques. ICAS was assessed with time-of-flight magnetic resonance angiograph and defined as ≥50% or ≥70% stenosis. We applied regression analyses to evaluate the association between LTPA with ECAS and ICAS, adjusting for confounders. RESULTS: Of 1274 included participants (mean age 71±9 years; 60% women; 65% Hispanic), the mean MET-score was 10±16 and 60% were in a LTPA-cluster with any activity. Among those with carotid ultrasound (n=1234), the mean carotid intima-media thickening was 0.97±0.09 mm, and 56% of participants had at least one carotid plaque identified. Among those with magnetic resonance angiograph (n=1211), 8% had ≥50% ICAS and 5% had ≥70% ICAS. For ICAS, MET-score was associated with ≥70% ICAS (adjusted odds ratio per unit increase in MET-score [95% CI, 0.97 [0.94-0.99]) but not with ECAS measures (carotid intima-media thickening, adjusted ß-estimate per unit increase in MET-score [95% CI], 0.002 [-0.003 to 0.006] or number of plaques, adjusted ß-estimate [95% CI], 0.0001 [-0.0001 to 0.0003]). Substituting MET-score with LTPA-clusters replicated the association between ≥70% ICAS and LTPA (adjusted odds ratio per each increased LTPA-cluster [95% CI], 0.83 [0.70-0.99]). CONCLUSIONS: In this diverse stroke-free population, we found LTPA most strongly associated with asymptomatic ≥70% ICAS. Given the high-risk nature of ≥70% ICAS, these findings may emphasize the role of LTPA in people at risk for ICAS.

Sleep Duration Is Associated With Subclinical Carotid Plaque Burden.

BACKGROUND: Sleep duration is associated with stroke risk and is 1 of 8 essential components of cardiovascular health according to the American Heart Association. As stroke disproportionately burdens Black and Hispanic populations in the United States, we hypothesized that long and short sleep duration would be associated with greater subclinical carotid atherosclerosis, a precursor of stroke, in the racially and ethnically diverse NOMAS (Northern Manhattan Study). METHODS: NOMAS is a study of community-dwelling adults. Self-reported nightly sleep duration and daytime sleepiness were collected between 2006 and 2011. Carotid plaque presence, total plaque area, and intima-media thickness were measured by ultrasound between 1999 and 2008. Linear and logistic regression models examined the cross-sectional associations of sleep duration groups (primary exposure) or daytime sleepiness (secondary exposure) with measures of carotid atherosclerosis. Models adjusted for age, time between ultrasound and sleep data collection, sex, race and ethnicity, education, health insurance, smoking, alcohol use, physical activity, body mass index, hypertension, diabetes, hypercholesterolemia, and cardiac disease. RESULTS: The sample (n=1553) had a mean age of 64.7±8.5 years and was 61.9% female, 64.8% Hispanic, and 18.2% non-Hispanic Black. Of the sample, 55.6% had carotid plaque, 22.3% reported nightly short sleep (<7 hours), 66.6% intermediate sleep (≥7 and <9 hours), and 11.1% had long sleep (≥9 hours). Compared with intermediate sleep, long sleep was associated with greater odds of carotid plaque presence relative to plaque absence (odds ratio, 1.6 [95% CI, 1.1-2.4]) and larger total plaque area (odds ratio, 1.4 [95% CI, 1.0-1.9]) after full covariate adjustment. Short sleep and daytime sleepiness were not significantly associated with any carotid measures. CONCLUSIONS: The association between long sleep and subclinical carotid atherosclerosis may explain prior associations between long sleep and stroke.

Marinagarivorans cellulosilyticus sp. nov., a cellulolytic bacterium isolated from the deep-sea off Noma-misaki, Japan.

Cells from strain GE09T, isolated from an artificially immersed nanofibrous cellulose plate in the deep sea, were Gram-stain-negative, motile, aerobic cells that could grow with cellulose as their only nutrient. Strain GE09T was placed among members of Cellvibrionaceae, in the Gammaproteobacteria, with Marinagarivorans algicola Z1T, a marine degrader of agar, as the closest relative (97.4 % similarity). The average nucleotide identity and digital DNA-DNA hybridization values between GE09T and M. algicola Z1T were 72.5 and 21.2 %, respectively. Strain GE09T degraded cellulose, xylan and pectin, but not starch, chitin and agar. The different carbohydrate-active enzymes encoded in the genomes of strain GE09T and M. algicola Z1T highlights their differences in terms of target energy sources and reflects their isolation environments. The major cellular fatty acids of strain GE09T were C18 : 1 ω7c, C16 : 0 and C16 : 1 ω7c. The polar lipid profile showed phosphatidylglycerol and phosphatidylethanolamine. The major respiratory quinone was Q-8. Based on these distinct taxonomic characteristics, strain GE09T represents a new species in the genus Marinagarivorans, for which we propose the name Marinagarivorans cellulosilyticus sp. nov. (type strain GE09T=DSM 113420T=JCM 35003T).

Starkeya nomas sp. nov., a prosthecate and budding bacterium isolated from an immunocompromized patient.

Strain HF14-78462T is an environmental bacterium found in clinical samples from an immunocompromized patient in 2014 at Hospital Universitari i Politècnic La Fe (Valencia, Spain). Phenotypically, strain HF14-78462T cells were Gram-stain-negative, aerobic, non-spore forming and non-motile small rods which formed mucous and whitish-translucent colonies when incubated at 20-36 °C. Phylogenetic analyses based on the 16S rRNA genes and the whole genomes of closest sequenced relatives confirmed that strain HF14-78462T is affiliated with the genus Starkeya. The strain was oxidase, catalase and urease positive; but indole, lysine decarboxylase, ornithine decarboxylase and DNase negative, did not produce H2S and was able to utilize a wide variety of carbon sources including acetamide, adonitol, amygdalin, l-arabinose, citric acid, glucose, mannitol and melibiose. Unlike Starkeya novella and Starkeya koreensis, strain HF14-78462T failed to grow in thiosulphate-oxidizing media and had a narrower temperature growth range. Its genome was characterized by a size of 4.83 Mbp and a C+G content of 67.75 mol%. Major fatty acids were C18:1 ω7c, cyclo C19 : 0 and C16 : 0, its polar acids were diphosphatidylglycerol, phosphatidylcholine, phosphatidylethanolamine, phosphatidylglycerol and an aminophospholipid; while the ubiquinones were Q9 (1.8 %) and Q10 (98.2 %). Digital DNA-DNA hybridization values were 41 and 41.4 against S. novella and S. koreensis, respectively, while average nucleotide identity values were around 84 %. Phenotypic, average nucleotide identity and phylogenomic comparative studies suggest that strain HF14-78462T is a new representative of the genus Starkeya and the name Starkeya nomas sp. nov. is proposed. The type strain is HF14-78462T (=CECT 30124T=LMG 31874T).

Joint Design of a Simultaneous Reflection and Transmission RIS in Mode-Switching Mode to Assist NOMA Systems.

Simultaneous transmitting and reflecting reconfigurable intelligent surfaces (STAR-RISs) can reflect signals and transmissive signals simultaneously and can extend the coverage of signals. A conventional RIS mainly focuses on the case where the signal source and the target are on the same side. In this paper, a STAR-RIS-assisted non-orthogonal multiple access (NOMA) downlink communication system is considered to maximize the achievable rate for users by jointly optimizing the power-allocation coefficients, active beamforming, and STAR-RIS beamforming under the mode-switching (MS) protocol. The critical information of the channel is first extracted using the Uniform Manifold Approximation and Projection (UMAP) method. Based on the key extracted channel features, STAR-RIS elements and users are clustered individually using the fuzzy C-mean clustering (FCM) method. The alternating optimization method decomposes the original optimization problem into three sub-optimization problems. Finally, the sub-problems are converted to unconstrained optimization methods using penalty functions for the solution. Simulation results show that when the number of elements of RIS is 60, the achievable rate of the STAR-RIS-NOMA system is about 18% higher than that of the RIS-NOMA system.

Adaptive Clustering of Users in Power Domain NOMA.

By enabling multiple non-orthogonal transmissions, power domain non-orthogonal multiple access (PD-NOMA) potentially increases a system's spectral efficiency. This technique can become an alternative for future generations of wireless communication networks. The efficiency of this method fundamentally depends on two previous processing steps: an appropriate grouping of users (transmission candidates) as a function of the channel gains and the choice of power levels that will be used to transmit each signal. Thus far, the solutions presented in the literature to address the problems of user clustering and power allocation do not consider the dynamics of communication systems, i.e., the temporal variation in the number of users and the channel conditions. In order to consider these dynamic characteristics in the clustering of users in NOMA systems, this work proposes a new clustering technique based on a modification of the DenStream evolutionary algorithm, chosen for its evolutionary capacity, noise robustness and online processing. We evaluated the performance of the proposed clustering technique considering, for simplicity, the use of an already widely known power allocation strategy called improved fractional strategy power allocation (IFSPA). The results show that the proposed clustering technique can follow the system dynamics, clustering all users and favoring the uniformity of the transmission rate between the clusters. Compared to orthogonal multiple access (OMA) systems, the proposed model's gain was approximately 10%, obtained on a challenging communication scenario for NOMA systems since the channel model adopted does not favor a large difference in the channel gains between users.

Machine-Learning-Based Indoor Localization under Shadowing Condition for P-NOMA VLC Systems.

The localization of agents for collaborative tasks is crucial to maintain the quality of the communication link for successful data transmission between the base station and agents. Power-domain Non-Orthogonal Multiple Access (P-NOMA) is an emerging multiplexing technique that enables the base station to accumulate signals for different agents using the same time-frequency channel. The environment information such as distance from the base station is required at the base station to calculate communication channel gains and allocate suitable signal power to each agent. The accurate estimate of the position for power allocation of P-NOMA in a dynamic environment is challenging due to the changing location of the end-agent and shadowing. In this paper, we take advantage of the two-way Visible Light Communication (VLC) link to (1) estimate the position of the end-agent in a real-time indoor environment based on the signal power received at the base station using machine learning algorithms and (2) allocate resources using the Simplified Gain Ratio Power Allocation (S-GRPA) scheme with the look-up table method. In addition, we use the Euclidean Distance Matrix (EDM) to estimate the location of the end-agent whose signal was lost due to shadowing. The simulation results show that the machine learning algorithm is able to provide an accuracy of 0.19 m and allocate power to the agent.

The role of intracranial artery calcification (IAC) in stroke subtype and risk of vascular events.

OBJECTIVE: To test the hypothesis that intracranial arterial calcification (IAC) is associated with intracranial large artery stenosis (ILAS) and a higher risk of vascular events and mortality. METHOD: We leveraged data from two cohorts, the New York-Presbyterian Hospital/Columbia University Irving Medical Center Stroke Registry Study (NYP/CUIMC-SRS) and the Northern Manhattan Study (NOMAS) to test our hypotheses. We measured IAC using CT scans of participants in both cohorts and expressed IAC as present (vs not) and in tertiles. For the CUIMC-SRS, demographic, clinical and ILAS status was collected retrospectively. In NOMAS, we used research brain MRI and MRA to define asymptomatic ILAS and covert brain infarcts(CBI). We built models adjusted for demographics and vascular risk factors for cross-sectional and longitudinal analyses. RESULTS: Cross-sectionally, IAC was associated with ILAS in both cohorts (OR 1.78, 95% CI: 1.16-2.73 for ILAS-related stroke in the NYP/CUIMC-SRS and OR 3.07, 95%CI 1.13-8.35 for ILAS-related covert brain infarcts in NOMAS). In a meta-analysis of both cohorts, IAC in the upper (HR 1.25, 95%CI 1.01-1.55) and middle tertile (HR 1.27, 95%CI 1.01-1.59) was associated with higher mortality compared with participants with no IAC. There were no longitudinal associations between IAC and risk of stroke or other vascular events. CONCLUSION: In these multiethnic populations, IAC is associated with symptomatic and asymptomatic ILAS as well as higher mortality. IAC may be a useful marker of higher mortality, the role of IAC as an imaging marker of risk of stroke is less certain.

Intracranial Large Artery Stenosis and Past Infectious Exposures: Results From the NOMAS Cohort.

BACKGROUND: Intracranial large artery stenosis (ILAS) is an important contributor to ischemic stroke in the United States and worldwide. There is evidence to suggest that chronic exposure to certain infectious agents may also be associated with ILAS. We aimed to study this association further in an ethnically diverse, prospective, population-based sample of Northern Manhattan. METHODS: We enrolled a random sample of stroke-free participants from an urban, racially, and ethnically diverse community in 1993. Participants have been followed prospectively and a subset underwent brain magnetic resonance angiograms from 2003 to 2008. Intracranial stenoses of the circle of Willis and vertebrobasilar arteries were scored as 0=no stenosis, 1≤50% (or luminal irregularities), 2=50% to 69%, 3≥70% stenosis, and 4=flow gap. We summed the individual score of each artery to produce a global ILAS score (possible range, 0-44). Past infectious exposure to Chlamydia pneumoniae, Helicobacter pylori, cytomegalovirus, and herpes simplex virus 1 and 2 was determined using serum antibody titers. RESULTS: Among 572 NOMAS (Northern Manhattan Study) participants (mean age 71.0±8.0 years, 60% women, 68% Hispanic) with available magnetic resonance angiogram and serological data, herpes simplex virus 2 (beta=0.051, P<0.001) and cytomegalovirus (beta=0.071, P<0.05) were associated with ILAS score after adjusting for demographics and vascular risk factors. Stratifying by anterior and posterior circulations, herpes simplex virus 2 remained associated with the anterior circulation (beta=0.055 P<0.01) but not with posterior circulation ILAS score. CONCLUSIONS: Chronic infectious exposures, specifically herpes simplex virus 2 and cytomegalovirus were associated with asymptomatic ILAS as seen on magnetic resonance angiogram imaging. This may represent an additional target of intervention in the ongoing effort to stem the substantial global burden of strokes related to ILAS.

Evaluation of Full-Duplex SWIPT Cooperative NOMA-Based IoT Relay Networks over Nakagami-m Fading Channels.

In this paper, we investigate the performance of non-orthogonal multiple access (NOMA)-based full-duplex Internet-of-Things (IoT) relay systems with simultaneous wireless information and power transfer (SWIPT) over Nakagami-m fading channels to improve the performance of a cell-edge user under perfect and imperfect successive interference cancellation (SIC). Two scenarios, i.e., direct and non-direct links, between the source node and cell-edge user are examined. The exact closed-form analytical and approximate expressions for the outage probability, system throughput, energy efficiency, and ergodic capacities are derived and validated via Monte Carlo simulations to characterize the proposed system performance. To further improve the system performance, we also provide a low-complexity algorithm to maximize the system throughput over-optimizing the time-switching factor. The results show that our proposed NOMA system can achieve superior performance compared to its orthogonal multiple access (OMA) counterpart under perfect SIC and with a low-to-medium signal-to-noise ratio under imperfect SIC, according to the level of residual self-interference and the quality of links.

Threshold-Based User-Assisted Cooperative Relaying in Beamspace Massive MIMO NOMA Systems.

The incorporation of user-assisted cooperative relaying into beamspace massive multiple-input multiple-output (mMIMO) non-orthogonal multiple access (NOMA) system can extend the coverage area and improve the spectral and energy efficiency for millimeter wave (mmWave) communications when a dynamic cluster of mobile user terminals (MUTs) is formed within a beam. We propose threshold-based user-assisted cooperative relaying into a beamspace mMIMO NOMA system in a downlink scenario. Specifically, the intermediate MUTs between the next-generation base station (gNB) and the cell-edge MUT become relaying MUTs after the successful decoding of the signal of the cell-edge MUT only when they meet the predetermined signal-to-interference plus noise ratio (SINR) threshold. A zero forcing (ZF) precoder and iterative power allocation are used to minimize both inter- and intra-beam interferences to maximize the system sum rate. We then evaluate the performance of this system in a delay-intolerant cell-edge MUT scenario. Moreover, the outage probability of the cell-edge MUT of the proposed scheme is investigated and an analytic expression is derived. Simulation results confirm that the proposed threshold-based user-assisted cooperative relaying beamspace mMIMO NOMA system outperforms the user-assisted cooperative relaying in beamspace mMIMO NOMA, beamspace MIMO-NOMA, and beamspace MIMO orthogonal multiple access (OMA) systems in terms of spectrum efficiency, energy efficiency, and outage probability.

SWIPT-Pairing Mechanism for Channel-Aware Cooperative H-NOMA in 6G Terahertz Communications.

The constraints of 5G communication systems compel further improvements to be compatible with 6G candidate technologies, especially to cope with the limited wavelengths of blockage-sensitive terahertz (THz) frequencies. In this paper integrating cooperative simultaneous wireless information and power transfer (SWIPT) and hybrid-non-orthogonal multiple access (H-NOMA) using THz frequency bands are suggested. We investigated and developed an optimal SWIPT-pairing mechanism for the multilateral proposed system that represents a considerable enhancement in energy/spectral efficiencies while improving the significant system specifications. Given the system performance investigation and the gains achieved, in this paper, wireless communication systems were optimized and upgraded, making use of promising technologies including H-NOMA and THz communications. This process aimed to alleviate the THz transmission challenges and improve wireless connectivity, resource availability, processing, robustness, capacity, user-fairness, and overall performance of communication networks. It thoroughly optimized the best H-NOMA pairing scheme for cell users. The conducted results showed how the proposed technique managed to improve energy and spectral efficiencies compared to the related work by more than 75%, in addition to the dynamism of the introduced mechanism. This system reduces the transceivers' hardware and computational complexity while improving reliability and transmission rates, without the need for complex technologies, e.g., multi-input multi-output or reflecting services.

Cooperative Power-Domain NOMA Systems: An Overview.

Interference has been a key roadblock against the effectively deployment of applications for end-users in wireless networks including fifth-generation (5G) and beyond fifth-generation (B5G) networks. Protocols and standards for various communication types have been established and utilised by the community in the last few years. However, interference remains a key challenge, preventing end-users from receiving the quality of service (QoS) expected for many 5G applications. The increased need for better data rates and more exposure to multimedia information lead to a non-orthogonal multiple access (NOMA) scheme that aims to enhance spectral efficiency and link additional applications employing successive interference cancellation and superposition coding mechanisms. Recent work suggests that the NOMA scheme performs better when combined with suitable wireless technologies specifically by incorporating antenna diversity including massive multiple-input multiple-output architecture, data rate fairness, energy efficiency, cooperative relaying, beamforming and equalization, network coding, and space-time coding. In this paper, we discuss several cooperative NOMA systems operating under the decode-and-forward and amplify-and-forward protocols. The paper provides an overview of power-domain NOMA-based cooperative communication, and also provides an outlook of future research directions of this area.

Performance Evaluation of Cooperative OMA and NOMA Systems in 6G Deployment Scenarios.

Optimization of the energy efficiency, fairness, and rates of the system is a vital part of communication systems. Multiple access techniques have a huge potential to enhance such performance parameters. This paper studies the performance of NOMA and OMA systems in a singular cell environment, where the cellular users are distributed randomly, and cooperative relays are considered for better system reliability. The relay nodes forward the signals to the cell-edge users. This paper considers a practical scenario where all the relay equipment is distributed with non-uniform battery power levels. The performance of OMA and NOMA schemes is compared based on the key performance indicators: sum rate, fairness, and energy efficiency. The fairness factor determines fairness in the allocation of resources to all the system's users. The performance of the two schemes is assessed in three deployment scenarios: urban, suburban, and rural scenarios. Through numerical results, it is proved that the performance of the NOMA dominates the OMA scheme.

Joint User-Slice Pairing and Association Framework Based on H-NOMA in RAN Slicing.

Multiservice cellular in Radio Access Network (RAN) Slicing has recently attained huge interest in enhancing isolation and flexibility. However, RAN slicing in heterogeneous networks (HetNet) architecture is not adequately explored. This study proposes a pairing-network slicing (NS) approach for Multiservice RAN that cares about quality of service (QoS), baseband resources, capacities of wireless fronthaul and backhaul links, and isolation. This intriguing approach helps address the increased need for mobile network traffic produced by a range of devices with various QoS requirements, including improved dependability, ultra-reliability low-latency communications (uRLLC), and enhanced broadband Mobile Services (eMBB). Our study displays a unique RAN slicing framework for user equipment (UE) for joint user-association. Multicell non-orthogonal multiple access (NOMA)-based resource allocation across 5G HetNet under successive interference cancelation (SIC) is seen to achieve the best performance. Joint user-slice pairing and association are optimization problems to maximize eMBB UE data rates while fulfilling uRLLC latency and reliability criteria. This is accomplished by guaranteeing the inter- and intra-isolation property of slicing to eliminate interferences between eMBB and uRLLC slices. We presented the UE-slice association (U-S. A) algorithm as a one-to-many matching game to create a stable connection between UE and one of the base stations (BSs). Next, we use the UE-slice pairing (U-S. P) algorithm to find stable uRLLC-eMBB pairs that coexist on the same spectrum. Numerical findings and performance analyses of the submitted association and pairing technique show they can all be RAN slicing criteria. We prove that the proposed algorithm optimizes system throughput while decreasing uRLLC latency by associating and pairing every uRLLC user in mini slots.

Multi-User Joint Detection Using Bi-Directional Deep Neural Network Framework in NOMA-OFDM System.

Non-orthogonal multiple access (NOMA) has great potential to implement the fifth-generation (5G) requirements of wireless communication. For a NOMA traditional detection method, successive interference cancellation (SIC) plays a vital role at the receiver side for both uplink and downlink transmission. Due to the complex multipath channel environment and prorogation of error problems, the traditional SIC method has a limited performance. To overcome the limitation of traditional detection methods, the deep-learning method has an advantage for the highly efficient tool. In this paper, a deep neural network which has bi-directional long short-term memory (Bi-LSTM) for multiuser uplink channel estimation (CE) and signal detection of the originally transmitted signal is proposed. Unlike the traditional CE schemes, the proposed Bi-LSTM model can directly recover multiuser transmission signals suffering from channel distortion. In the offline training stage, the Bi-LTSM model is trained using simulation data based on channel statistics. Then, the trained model is used to recover the transmitted symbols in the online deployment stage. In the simulation results, the performance of the proposed model is compared with the convolutional neural network model and traditional CE schemes such as MMSE and LS. It is shown that the proposed method provides feasible improvements in performance in terms of symbol-error rate and signal-to-noise ratio, making it suitable for 5G wireless communication and beyond.