Adaptive Beam Pattern Selection and Resource Allocation for NOMA-Based LEO Satellite Systems

The low earth orbit (LEO) satellite system is one of the promising solutions to provide broadband services to a wide-coverage area for future integrated LEO-6G networks, where users' demands vary with time and geographical locations. Conventional satellites with fixed beam pattern and footprint planning may not be capable of meeting such dynamic requests and irregular traffic distributions. As the development of flexible satellite payload with beamforming capabilities, spot beams with flexible size and shape are considered potential solutions to this issue. As an early investigation, in this paper, we consider the scenarios where satellite payloads are equipped with multiple beam patterns and study the optimal beam pattern selection. We exploit the potential synergies of joint resource optimization between adaptive beam patterns and non-orthogonal multiple access (NOMA) in a LEO satellite system, where NOMA is employed to reduce intra-beam interference and flexible beam pattern is adopted to mitigate inter-satellite interference. The formulated problem is to minimize the capacity-demand gap of terminals, which falls into mixed-integer nonconvex pro-gramming (MINCP). To tackle the discrete variables and non-convexity, we design a joint approach to allocate power and select beam patterns. Numerical results show that the proposed scheme achieves capacity-demand gap reduction of 37.8% over conventional orthogonal multiple access (OMA) and 42.5% over the fixed-beam-pattern scheme.This work has been supported by the Luxembourg national research fund (FNR) under the project ROSETTA (C17/IS/11632107) and MegaLEO (C20/IS/14767486).Peer ReviewedPostprint (author's final draft

Power and Rate Allocation in Cognitive Satellite Uplink Networks

peer reviewedIn this paper, we consider the cognitive satellite uplink where satellite terminals reuse frequency bands of Fixed-Service (FS) terrestrial microwave links which are the incumbent users in the Ka 27.5-29.5 GHz band. In this scenario, the transmitted power of the cognitive satellite terminals has to be controlled so as to satisfy the interference constraints imposed by the incumbent FS receivers. We investigate and analyze a set of optimization frameworks for the power and rate allocation problem in the considered cognitive satellite scenario. The main objective is to shed some light on this rather unexplored scenario and demonstrate feasibility of the terrestrial-satellite co-existence. In particular, we formulate a multi-objective optimization problem where the rates of the satellite terminals form the objective vector and derive a general iterative framework which provides a Pareto-optimal solution. Next, we transform the multi-objective optimization problem into different single-objective optimization problems, focusing on popular figures of merit such as the sumrate or the rate fairness. Supporting results based on numerical simulations are provided which compare the different proposed approaches.SATSEN

Guest Editorial: Space Information Networks: Technological Challenges, Design Issues, and Solutions

It has been expected that the space information networks (SIN), as an extension of the terrestrial network, would provide high-speed, high-capacity, global continuous communication, and data transmission services anywhere for anyone at any time. With rapid advances in relevant technologies (e.g., satellite miniaturization technology, reusable rocket launch technology, and semiconductor technology), low-orbit satellites, drones, and airships can be integrated into the SIN to supply more comprehensive network connectivity. The standard development organizations including 3GPP, ITU, and ETSI already starts corresponding standardization activities to support nonterrestrial networks in SIN. It can be foreseen that SIN will be expanded to provide not only telephone services but also various kinds of Internet services, and it is thus able to serve many more users with different demands

Effect of ABCB1 and ABCC3 Polymorphisms on Osteosarcoma Survival after Chemotherapy: A Pharmacogenetic Study

Standard treatment for osteosarcoma patients consists of a combination of cisplatin, adriamycin, and methotrexate before surgical resection of the primary tumour, followed by postoperative chemotherapy including vincristine and cyclophosphamide. Unfortunately, many patients still relapse or suffer adverse events. We examined whether common germline polymorphisms in chemotherapeutic transporter and metabolic pathway genes of the drugs used in standard osteosarcoma treatment may predict treatment response. METHODOLOGY/PRINCIPAL FINDINGS: In this study we screened 102 osteosarcoma patients for 346 Single Nucleotide Polymorphisms (SNPs) and 2 Copy Number Variants (CNVs) in 24 genes involved in the metabolism or transport of cisplatin, adriamycin, methotrexate, vincristine, and cyclophosphamide. We studied the association of the genotypes with tumour response and overall survival. We found that four SNPs in two ATP-binding cassette genes were significantly associated with overall survival: rs4148416 in ABCC3 (per-allele HR = 8.14, 95%CI = 2.73-20.2, p-value = 5.1x10(-)(5)), and three SNPs in ABCB1, rs4148737 (per-allele HR = 3.66, 95%CI = 1.85-6.11, p-value = 6.9x10(-)(5)), rs1128503 and rs10276036 (r(2) = 1, per-allele HR = 0.24, 95%CI = 0.11-0.47 p-value = 7.9x10(-)(5)). Associations with these SNPs remained statistically significant after correction for multiple testing (all corrected p-values [permutation test] </= 0.03). CONCLUSIONS: Our findings suggest that these polymorphisms may affect osteosarcoma treatment efficacy. If these associations are independently validated, these variants could be used as genetic predictors of clinical outcome in the treatment of osteosarcoma, helping in the design of individualized therapy

Genomic characterization of individuals presenting extreme phenotypes of high and low risk to develop tobacco-induced lung cancer

Single nucleotide polymorphisms (SNPs) may modulate individual susceptibility to carcinogens. We designed a genome-wide association study to characterize individuals presenting extreme phenotypes of high and low risk to develop tobacco-induced non-small cell lung cancer (NSCLC), and we validated our results. We hypothesized that this strategy would enrich the frequencies of the alleles that contribute to the observed traits. We genotyped 2.37 million SNPs in 95 extreme phenotype individuals, that is: heavy smokers that either developed NSCLC at an early age (extreme cases); or did not present NSCLC at an advanced age (extreme controls), selected from a discovery set (n=3631). We validated significant SNPs in 133 additional subjects with extreme phenotypes selected from databases including >39,000 individuals. Two SNPs were validated: rs12660420 (p(combined)=5.66x10(-5); ORcombined=2.80), mapping to a noncoding transcript exon of PDE10A; and rs6835978 (p(combined)=1.02x10(-4); ORcombined=2.57), an intronic variant in ATP10D. We assessed the relevance of both proteins in early-stage NSCLC. PDE10A and ATP10D mRNA expressions correlated with survival in 821 stage I-II NSCLC patients (p=0.01 and p<0.0001). PDE10A protein expression correlated with survival in 149 patients with stage I-II NSCLC (p=0.002). In conclusion, we validated two variants associated with extreme phenotypes of high and low risk of developing tobacco-induced NSCLC. Our findings may allow to identify individuals presenting high and low risk to develop tobacco-induced NSCLC and to characterize molecular mechanisms of carcinogenesis and resistance to develop NSCLC

BRCA2 polymorphic stop codon K3326X and the risk of breast, prostate, and ovarian cancers

Background: The K3326X variant in BRCA2 (BRCA2*c.9976A&gt;T; p.Lys3326*; rs11571833) has been found to be associated with small increased risks of breast cancer. However, it is not clear to what extent linkage disequilibrium with fully pathogenic mutations might account for this association. There is scant information about the effect of K3326X in other hormone-related cancers. Methods: Using weighted logistic regression, we analyzed data from the large iCOGS study including 76 637 cancer case patients and 83 796 control patients to estimate odds ratios (ORw) and 95% confidence intervals (CIs) for K3326X variant carriers in relation to breast, ovarian, and prostate cancer risks, with weights defined as probability of not having a pathogenic BRCA2 variant. Using Cox proportional hazards modeling, we also examined the associations of K3326X with breast and ovarian cancer risks among 7183 BRCA1 variant carriers. All statistical tests were two-sided. Results: The K3326X variant was associated with breast (ORw = 1.28, 95% CI = 1.17 to 1.40, P = 5.9x10- 6) and invasive ovarian cancer (ORw = 1.26, 95% CI = 1.10 to 1.43, P = 3.8x10-3). These associations were stronger for serous ovarian cancer and for estrogen receptor–negative breast cancer (ORw = 1.46, 95% CI = 1.2 to 1.70, P = 3.4x10-5 and ORw = 1.50, 95% CI = 1.28 to 1.76, P = 4.1x10-5, respectively). For BRCA1 mutation carriers, there was a statistically significant inverse association of the K3326X variant with risk of ovarian cancer (HR = 0.43, 95% CI = 0.22 to 0.84, P = .013) but no association with breast cancer. No association with prostate cancer was observed. Conclusions: Our study provides evidence that the K3326X variant is associated with risk of developing breast and ovarian cancers independent of other pathogenic variants in BRCA2. Further studies are needed to determine the biological mechanism of action responsible for these associations

Breast cancer risk variants at 6q25 display different phenotype associations and regulate ESR1, RMND1 and CCDC170.

We analyzed 3,872 common genetic variants across the ESR1 locus (encoding estrogen receptor α) in 118,816 subjects from three international consortia. We found evidence for at least five independent causal variants, each associated with different phenotype sets, including estrogen receptor (ER(+) or ER(-)) and human ERBB2 (HER2(+) or HER2(-)) tumor subtypes, mammographic density and tumor grade. The best candidate causal variants for ER(-) tumors lie in four separate enhancer elements, and their risk alleles reduce expression of ESR1, RMND1 and CCDC170, whereas the risk alleles of the strongest candidates for the remaining independent causal variant disrupt a silencer element and putatively increase ESR1 and RMND1 expression.This is the author accepted manuscript. The final version is available from Nature Publishing Group via http://dx.doi.org/10.1038/ng.352