A joint optimization scheme of resource allocation in downlink NOMA with statistical channel state information

In a real communication scenario,it is very difficult to obtain the real-time channel state infor-mation(CSI)accurately,so the non-orthogonal multiple access(NOMA)system with statistical CSI has been researched.Aiming at the problem that the maximization of system sum rate cannot be solved directly,a step-by-step resource allocation optimization scheme based on machine learning is proposed.First,in order to achieve a trade-off between the system sum rate and user fairness,the system throughput formula is derived.Then,according to the combinatorial characteristics of the system throughput maximization problem,the original optimization problem is divided into two sub-problems,that are power allocation and user grouping.Finally,genetic algorithm is introduced to solve the sub-problem of power allocation,and hungarian algorithm is introduced to solve the sub-problem of user grouping.By comparing the ergodic data rate of NOMA users with statistical CSI and perfect CSI,the effectiveness of the statistical CSI sorting is verified.Compared with the orthogonal multiple access(OMA)scheme,the NOMA scheme with the fixed user grouping scheme and the random user grouping scheme,the system throughput performance of the proposed scheme is signifi-cantly improved.

Analysis of asymptotically tight approximation SER for cooperative NOMA systems

The closed-form formula derivation of the power domain cooperative non-orthogonal multiple access(NOMA)system is of great significance for further improving the performance of the system.However,the system performance formulas of the channel capacity and the paired bit error rate pairwise error probability(PEP)are too complicated,which have increased the difficulty in system performance optimization.Therefore,based on the amplify forward(AF)relay cooperative NOMA model,the signal interference noise ratio(SINR)formulas of the two user nodes are constructed.Through the assumption of that,the symbol error rate(SER)of each user is fair,the simplification condition of moment generating function(MGF)with the harmonic mean form is satisfied.Combined with the SER calculation formula of MGF,the system SER asymptotically tight approximation formula with simple structure is derived at high signal-to-noise ratio(SNR).The Monte Carlo simulation results show that,the formula can accurately describe the SER performance of the power domain cooperative NOMA system with the non-ideal successive interference cancellation(SIC)system when SNR is high.Under the condition of certain total power,the optimal power allocation factor is solved in order to minimize the total system SER.

Grouping pilot allocation scheme based on matching algorithm in massive MIMO system

Pilot allocation is one of the effective means to reduce pilot pollution in massive multiple-input multiple-output(MIMO)systems.The goal of this paper is to improve the uplink achievable sum rates of strong users,and ensure the quality of service(QoS)requirements of weak users at the same time,so that the sum rates of system can be improved.Combining with the technical advantage of pilot grouping,a low complexity pilot allocation scheme based on matching algorithm is proposed,which divides the users in the target cell into weak user group and strong user group,and adopts the minimum-maximum matching method to allocate pilots in weak user group.Through the introduction of Hungarian algorithm,a pilot allocation method is designed to ensure the fairness of the strong users.The simulation results show that,compared with the smart pilot allocation scheme,the pilot allocation scheme based on Hungarian algorithm,the pilot allocation scheme based on user grouping and the random pilot allocation scheme,the system performance of the proposed scheme has been effectively improved.

高强度聚焦超声联合全氟戊烷液滴在乳腺癌治疗增效中的实验研究

目的:探讨高强度聚焦超声(High-Intensity Focused Ultrasound,HIFU)联合全氟戊烷液滴(Perfluoropentane droplets,PFP),对小鼠乳腺癌4T1细胞治疗的增效作用。方法:制备PFP,检测其平均粒径及形态结构。试验设立三组:HIFU假照组,单纯HIFU治疗组,HIFU联合PFP治疗组。流式细胞仪检测HIFU分组治疗乳腺癌细胞后细胞存活率及死亡率;体内动物试验分组处理后,二维超声观察HIFU辐照前后肿瘤回声灰度变化情况,超声造影剂灌注缺损面积占总面积百分比评价不同治疗方式对裸鼠皮下移植瘤的消融能力。结果:所制备的PFP平均粒径为1.2μm,形态呈规则球形。细胞试验显示,HIFU联合PFP治疗组乳腺癌细胞死亡率(23.50±1.34)%显著高于单纯HIFU治疗组(14.34±0.55)%和HIFU假照组(11.76±0.62)%(P<0.05);动物试验显示HIFU联合PFP治疗组肿瘤消融面积占总面积百分比(84.03±4.47)%显著高于单纯HIFU治疗组(41.23±4.24)%(P<0.05),HIFU假照组无明显灌注缺损区域。结论:HIFU联合PFP可显著增强对乳腺癌细胞及组织的消融能力。

超声影像方法在预测HIFU治疗子宫肌瘤疗效中的应用

子宫肌瘤是育龄期女性最常见的良性肿瘤,高强度聚焦超声(High Intensity Focused Ultrasound,HIFU)作为一种微创治疗技术,已经广泛运用于子宫肌瘤的治疗,但是对于某些特殊类型的肌瘤消融效率较低,并导致很多严重的并发症。这类肌瘤在二维灰阶超声、多普勒超声、超声造影方面有特殊的表现。对上述超声影像方法在预测HIFU治疗子宫肌瘤疗效中的作用进行了综述。但各种超声影像学技术存在一定误差,提供子宫肌瘤内部微血管灌注信息仍不完全,在未来研究中可使用包括微血管成像技术(Superb Micro-vascular Imaging,SMI)、造影剂微血管灌注成像(Contrast Micro-Imaging,CMI)、磁共振成像(Magnetic Resonance Imaging,MRI)多种技术在内的多模态分析,为HIFU治疗子宫肌瘤疗效预测提供更多参考和信息。

应用Deeplab V3+网络实现小儿髋关节超声图像识别

利用Graf法进行发育性髋关节发育不良(Developmental Dysplasia of the Hip, DDH)诊断时主要依靠骨-软骨交界面、股骨头、滑膜皱襞、关节囊及软骨膜、盂唇、软骨顶、骨性顶这7个解剖结构进行解剖验证,而初级医生对上述结构识别困难,因此文章提出了一种基于DeeplabV3+的网络模型用于7个结构的分割识别。首先对纳入的106例图像进行手动标记和预处理,之后将其分别输入DeeplabV3+和U-Net两种网络模型中,最终对其预测图表现和分割性能进行比较。与目前DDH图像分割中常用且表现优越的U-Net网络相比,DeeplabV3+网络的预测图包含的结构较多,边界分割也较清晰,其图像分割评价指标如相似性系数、豪斯多夫距离和平均豪斯多夫距离平均值的表现也优于U-Net网络。文章利用DeeplabV3+网络实现了DDH超声图像的7个结构分割,对临床医生进行后续图像的角度测量和分型诊断具有重要意义。

家庭医生签约对社区高血压患者血压控制的效果分析

目的:探讨分析家庭医生签约对社区高血压患者血压控制的效果。方法:收治高血压患者120例,并进行1年的随访管理,对管理前后的血压及相关因素进行分析。结果:实施家庭医生签约后,患者对高血压相关知识的知晓率、治疗的依从性及血压控制较实施前有明显改善,差异有统计学意义(P<0.05)。结论:家庭医生签约可将慢病管理窗口前移,显著改善患者的血压水平。