Jamming-Aided Secure Communication in Ultra-Dense LEO Integrated Satellite-Terrestrial Networks

The ultra-dense low earth orbit(LEO)integrated satellite-terrestrial networks(UDLEO-ISTN)can bring lots of benefits in terms of wide coverage,high capacity,and strong robustness.Meanwhile,the broadcasting and open natures of satellite links also reveal many challenges for transmission security protection,especially for eavesdropping defence.How to efficiently take advantage of the LEO satellite’s density and ensure the secure communication by leveraging physical layer security with the cooperation of jammers deserves further investigation.To our knowledge,using satellites as jammers in UDLEO-ISTN is still a new problem since existing works mainly focused on this issue only from the aspect of terrestrial networks.To this end,we study in this paper the cooperative secrecy communication problem in UDLEOISTN by utilizing several satellites to send jamming signal to the eavesdroppers.An iterative scheme is proposed as our solution to maximize the system secrecy energy efficiency(SEE)via jointly optimizing transmit power allocation and user association.Extensive experiment results verify that our designed optimization scheme can significantly enhance the system SEE and achieve the optimal power allocation and user association strategies.

Cooperative laparoscopic endoscopic and hybrid laparoscopic surgery for upper gastrointestinal tumors: Current status

AIM: To investigate the cooperative laparoscopic and endoscopic techniques used for the resection of upper gastrointestinal tumors.METHODS: A systematic research of the literature was performed in Pub Med for English and French language articles about laparoscopic and endoscopic cooperative,combined,hybrid and rendezvous techniques. Only original studies using these techniques for the resection of early gastric cancer,benign tumors and gastrointestinal stromal tumors of the stomach and the duodenum were included. By excluding case series of less than 10 patients,25 studies were identified. The study design,number of cases,tumor pathology size and location,the operative technique name,the endoscopy team and surgical team role,operative time,type of closure of visceral wall defect,blood loss,complications and length of hospital stay of these studies were evaluated. Additionally all cooperative techniques found were classified and are presented in a systematic approach.RESULTS: The studies identified were case series and retrospective cohort studies. A total of 706 patients were operated on with a cooperative technique. The tumors resected were only gastrointestinal stromal tumors(GIST) in 4 studies,GIST and various benign submucosal tumors in 22 studies,early gastric cancer(p T1 a and p T1b) in 6 studies and early duodenal cancer in 1 study. There was important heterogeneity between the studies. The operative techniques identified were:laparoscopic assisted endoscopic resection,endoscopic assisted wedge resection,endoscopic assisted transgastric and intragastric surgery,laparoscopic endoscopic cooperative surgery(LECS),laparoscopic assisted endoscopic full thickness resection(LAEFR),clean non exposure technique and non-exposed endoscopic wallinversion surgery(NEWS). Each technique is illustrated with the roles of the endoscopic and laparoscopic teams; the indications,characteristics and short term results are described.CONCLUSION: Along with the traditional cooperative techniques,new procedures like LECS,LAEFR and NEWS hold great promise for the future of minimally invasive oncologic procedures.

Optimal Energy-Efficient Transmission for Hybrid Spectrum Sharing in Cooperative Cognitive Radio Networks

In order to improve the energy efficiency(EE)in cognitive radio(CR),this paper investigates the joint design of cooperative spectrum sensing time and the power control optimization problem for the secondary user systems to achieve the maximum energy efficiency in a cognitive network based on hybrid spectrum sharing,meanwhile considering the maximum transmit power,user quality of service(QoS)requirements,interference limitations,and primary user protection.The optimization of energy efficient sensing time and power allocation is formulated as a non-convex optimization problem.The Dinkelbach’s method is adopted to solve this problem and to transform the non-convex optimization problem in fractional form into an equivalent optimization problem in the form of subtraction.Then,an iterative power allocation algorithm is proposed to solve the optimization problem.The simulation results show the effectiveness of the proposed algorithms for energy-efficient resource allocation in the cognitive network.

Cooperative Jamming for Physical Layer Security in Hybrid Satellite Terrestrial Relay Networks

To integrate the satellite communications with the LTE/5G services, the concept of Hybrid Satellite Terrestrial Relay Networks(HSTRNs) has been proposed. In this paper, we investigate the secure transmission in a HSTRN where the eavesdropper can wiretap the transmitted messages from both the satellite and the intermediate relays. To effectively protect the message from wiretapping in these two phases, we consider cooperative jamming by the relays, where the jamming signals are optimized to maximize the secrecy rate under the total power constraint of relays. In the first phase, the Maximal Ratio Transmission(MRT) scheme is used to maximize the secrecy rate, while in the second phase, by interpolating between the sub-optimal MRT scheme and the null-space projection scheme, the optimal scheme can be obtained via an efficient one-dimensional searching method. Simulation results show that when the number of cooperative relays is small, the performance of the optimal scheme significantly outperforms that of MRT and null-space projection scheme. When the number of relays increases, the performance of the null-space projection approaches that of the optimal one.

SER analysis and power allocation for hybrid cooperative transmission system

The symbol-error-rate（SER） and power allocation for hybrid cooperative（HC） transmission system are investigated.Closed-form SER expression is derived by using the moment generating function（MGF）-based approach.However,the resultant SER contains an MGF of the harmonic mean of two independent random variables（RVs）,which is not tractable in SER analysis.We present a simple MGF expression of the harmonic mean of two independent RVs which avoids the hypergeometric functions used commonly in previous studies.Using the simple MGF,closed-form SER for HC system with M-ary phase shift keying（M-PSK） signals is provided.Further,an approximation as well as an upper bound of the SER is presented.It is shown that the SER approximation is asymptotically tight.Based on the tight SER approximation,the power allocation of the HC system is investigated.It is shown that the optimal power allocation does not depend on the fading parameters of the source-destination（SD） channel and it only depends on the source-relay（SR） and relay-destination（RD） channels.Moreover,the performance gain of the power allocation depends on the ratio of the channel quality between RD and SR.With the increase of this ratio,more performance gain can be acquired.

Complex task planning method of space-aeronautics cooperative observation based on multi-layer interaction

With the new development trend of multi-resource coordinated Earth observation and the new goal of Earth observation application of“short response time,high observation accuracy,and wide coverage”,space-aeronautics cooperative complex task planning problem has become an urgent problem to be solved.The focus of this problem is to use multiple resources to perform collaborative observations on complex tasks.By analyzing the process from task assignment to receiving task observation results,we propose a multi-layer interactive task planning framework which is composed of a preprocessing method for complex tasks,a task allocation layer,a task planning layer,and a task coordination layer.According to the characteristics of the framework,a hybrid genetic parallel tabu(HGPT)algorithm is proposed on this basis.The algorithm uses genetic annealing algorithm(GAA),parallel tabu(PT)algorithm,and heuristic rules to achieve task allocation,task planning,and task coordination.At the same time,coding improvements,operator design,annealing operations,and parallel calculations are added to the algorithm.In order to verify the effectiveness of the algorithm,simulation experiments under complex task scenarios of different scales are carried out.Experimental results show that this method can effectively solve the problems of observing complex tasks.Meanwhile,the optimization effect and convergence speed of the HGPT is better than that of the related algorithms.

Deep Unfolding for Cooperative Rate Splitting Multiple Access in Hybrid Satellite Terrestrial Networks

Rate splitting multiple access(RSMA)has shown great potentials for the next generation communication systems.In this work,we consider a two-user system in hybrid satellite terrestrial network(HSTN)where one of them is heavily shadowed and the other uses cooperative RSMA to improve the transmission quality.The non-convex weighted sum rate(WSR)problem formulated based on this model is usually optimized by computational burdened weighted minimum mean square error(WMMSE)algorithm.We propose to apply deep unfolding to solve the optimization problem,which maps WMMSE iterations into a layer-wise network and could achieve better performance within limited iterations.We also incorporate momentum accelerated projection gradient descent(PGD)algorithm to circumvent the complicated operations in WMMSE that are not amenable for unfolding and mapping.The momentum and step size in deep unfolding network are selected as trainable parameters for training.As shown in the simulation results,deep unfolding scheme has WSR and convergence speed advantages over original WMMSE algorithm.

A method for power suppliers’optimal cooperative bidding strategies considering network losses

The bidding strategies of power suppliers to maximize their interests is of great importance.The proposed bilevel optimization model with coalitions of power suppliers takes restraint factors into consideration,such as operating cost reduction,potential cooperation,other competitors’bidding behavior,and network constraints.The upper model describes the coalition relationship between suppliers,and the lower model represents the independent system operator’s optimization without network loss(WNL)or considering network loss(CNL).Then,a novel algorithm,the evolutionary game theory algorithm(EGA)based on a hybrid particle swarm optimization and improved firefly algorithm(HPSOIFA),is proposed to solve the bi-level optimization model.The bidding behavior of the power suppliers in equilibrium with a dynamic power market is encoded as one species,with the EGA automatically predicting a plausible adaptation process for the others.Individual behavior changes are employed by the HPSOIFA to enhance the ability of global exploration and local exploitation.A novel improved firefly algorithm(IFA)is combined with a chaotic sequence theory to escape from the local optimum.In addition,the Shapley value is applied to the profit distribution of power suppliers’cooperation.The simulation,adopting the standard IEEE-30 bus system,demonstrates the effectiveness of the proposed method for solving the bi-level optimization problem.

Cross-layer design of combining AMC with HARQ in cooperative relay system with perfect and imperfect CSI

A cross-layer design which combines adaptive modulation and coding (AMC) at the physical layer with a hybrid automatic repeat request (HARQ) protocol at the data link layer (LL) is presented, in cooperative relay system over Nakagami-m fading channels with perfect and imperfect channel state information (CSI). In order to maximize spectral efficiency (SE) under delay and packet error rate (PER) performance constraints, a state transition model and an optimization framework with perfect CSI are presented. Then the framework is extended to cooperative relay system with imperfect CSI. The numerical results show that the scheme can achieve maximum SE while satisfying transmitting delay requirements. Compared with the imperfect CSI, the average PER with perfect CSI is much lower and the spectral efficiency is much higher.

Enhanced cooperative packet retransmission employing joint cooperative diversity and symbol mapping diversity

A joint cooperation diversity and symbol mapping diversity (SMD) strategy is proposed for cooperative packet retransmission system with high-order modulation such as 16QAM. Substantial SER/BER (symbol error rate/bit error rate) gains result from multiple packet transmissions over independent paths and distinct bit-to-symbol mappings for each packet transmis-sion. The SER/BER performance of relay assisted retransmission system is analyzed. Simulation results show that the joint-diversity strategy can provide more BER gains than other relaying strategies (i.e., decode-and-forward and constellation rearrangement relaying strategies) when no relay makes a decision error; but if some relays make decision errors, the joint-di-versity strategy outperforms other relaying strategies only when the relays are closer to the source than to the destination.

基于混合两阶段鲁棒的多微网合作优化运行

针对微网独立运行时面临运行成本高,受可再生能源出力和多能负荷功率不确定性影响大等问题,提出一种基于混合两阶段鲁棒优化的多微网合作运行方法。首先,为了应对源荷双重不确定性挑战,在传统两阶段鲁棒优化基础上,提出一种基于多场景数据的最恶劣概率场景驱动的混合两阶段鲁棒优化方法,并采用可并行计算列与约束生成(column and constraint generation,C&CG)算法来提高求解效率。然后,在建立的多微网点对点分布式能源交易系统框架上,根据纳什谈判理论构造多微网合作成本最小化问题和收益分配问题,并提出一种耦合可并行计算C&CG的交替方向乘子法进行求解。最后,根据各微网不同的贡献率,设计一种基于点对点电能交易贡献度的非对称纳什谈判机制来分配各微网的合作收益。算例结果表明,所提方法能兼顾系统的鲁棒性、经济性和隐私性,并实现每个微网公平合理的收益分配。

考虑分散协作及数量折扣的双目标电动车辆路径优化

当前传统燃油车辆造成了极大的空气污染和资源浪费,电动车辆和协作物流是降低碳排放、提高运输效率的有效途径。本文基于协作物流的思想,建立以运输利润最大及配送任务完成量最大为双目标,考虑分散协作及数量折扣的带时间窗电动车辆路径优化模型。设计将贪婪随机自适应搜索—进化邻域搜索(GRASP-ELS)混合算法与ε-约束法相结合的ε-约束混合进化算法,并通过算例对模型和算法进行测试。实验结果表明:所提出的算法优于多目标优化算法NSGA-Ⅱ;通过灵敏度分析给出管理启示。本文为分散协作情境下电动车辆配送优化提供方法借鉴与决策参考。

基于差分进化粒子群混合算法的多无人机协同区域搜索策略

为提高无人机群在未知环境中的区域搜索效率,提出一种多无人机协同区域搜索策略。首先,根据区域搜索任务需求,建立包含区域覆盖率、区域不确定度、目标存在概率三种属性的区域信息地图;其次,以最大化搜索效率、同时最小化无人机搜索过程中的能耗为目标,建立无人机区域搜索滚动时域优化目标函数,指导无人机在线决策搜索路线;然后针对传统群智能优化算法易陷入局部最优的缺陷,设计差分进化粒子群混合算法在线求解该多目标优化问题,提高算法的寻优性能,从而提高无人机的搜索效率。最后,通过数值仿真实验,对所提算法进行验证,仿真结果表明,文中设计的基于差分进化粒子群混合算法的多无人机协同区域搜索策略与传统的群智能优化算法相比具有更高的区域搜索效率。

基于改进混合粒子群优化算法的多无人机协同围捕方法研究

针对多无人机协同围捕问题,在无人机运动学约束基础上,考虑各无人机应同时到达围捕位置,提出了多机协同围捕任务规划两层求解架构。在任务协调层通过改进混合粒子群优化方法,以各无人机同时到达指定围捕位置的最小时间为目标,优化调度给出多目标围捕方案;在航路规划层考虑无人机初始状态及运动学约束,通过Dubins曲线调整实现各无人机同时到达围捕位置。仿真结果表明了所提方法的有效性。

计及阻容式撬棒的混合型风电场协同控制及故障特性分析

为解决混合型风电场低穿措施复杂难以协同及低穿后故障特性难以分析的问题,提出双馈风电机组应用阻容式撬棒以改善低电压穿越期间混合型风电场的频偏及无功特性。首先建立双馈风电机组群与永磁直驱风力发电机组群模型,通过分群聚合等效的方法建立混合型风电场简化等效模型。在此基础上,分析计及阻容撬棒的混合型风电场故障期间各类型风电机组的无功调节能力及调节特性。据此制定混合型风电场的无功协同控制策略以优化低电压穿越期间无功输出能力,分析采用协同控制策略后混合型风电场的短路特性,并对短路电流进行解析。最后基于PSCAD/EMTDC仿真软件建立了混合型风电场仿真模型,对协同策略的有效性及故障电流表达式的正确性进行仿真验证。

欧盟威胁应对中的“全政府-全社会”路径——基于情报合作的分析

[研究目的]近年来,欧盟愈发重视通过“全政府”和“全社会”的方式来应对各类安全威胁,并将其应用到情报合作中。对于欧盟相关对策的梳理可为我国贯彻总体国家安全观提供一定借鉴。[研究方法]从“全政府-全社会”概念的起源谈起,梳理了欧盟对于这一概念的认识及其实践情况,并在此基础上总结了欧盟情报合作的变革思路以及未来发展可能面临的挑战。[研究结论]通过研究发现,欧盟在“全政府-全社会”路径的推动下,极大地提升了其情报一体化程度。然而,欧盟的情报合作仍面临着成员国参与不积极、缺乏基本的情报资源和相关整合难度过大等问题。

长周期地震动对SRC框架-RC核心筒混合结构协同工作的影响

长周期地震动因含有丰富的低频成分易使(超)高层建筑等长周期结构发生严重震害。SRC(steel reinforced concrete)框架-RC(reinforced concrete)核心筒混合结构作为广泛应用于高烈度区的双重抗侧力结构体系,确保其强震下的协同工作是实现多道抗震防线,形成合理破坏模式的关键。该文通过与普通地震动对比,阐明了远场长周期地震动对SRC框架-RC核心筒混合结构协同工作的影响规律,并基于谐振激励下的结构动力分析模型及经验模态分解初步揭示了其内在机理。算例分析结果表明:受低频特性影响,远场长周期地震动作用下结构框架剪力分担率与底层倾覆力矩占比明显大于普通地震动,最大框架剪力分担率所在楼层与普通地震动相比出现下移,且当峰值加速度增至400 gal时,SRC框架中下部楼层剪力分担率超过40%,底部倾覆力矩占比超过70%,按照现行规范设计的SRC框架将难以保证远场长周期地震动作用下结构的抗震安全;激励频率对于SRC框架-RC核心筒混合结构协同工作的影响与振型参与方式有关,低频激励(周期为0.5倍~2.0倍结构基本周期)下结构响应主要受低阶振型主导;远场长周期地震动的卓越分量是导致框架剪力分担率增大的原因。

Statistical QoS Provisioning Architecture for 6G Satellite-Terrestrial Integrated Networks

The emergence of massive ultra-reliable and low latency communications (mURLLC) as a category of age/time/reliability-sensitive service over 6G wireless networks has received considerable research attention, which has presented unprecedented challenges. As one of the key enablers for 6G,satellite-terrestrial integrated networks (STIN) have been developed to offer more expansive connectivity and comprehensive 3D coverage in space-aerial-terrestrial domains for supporting 6G mission-critical mURLLC applications while fulfilling diverse and rigorous quality of service (QoS) requirements. In the context of these mURLLC-driven satellite services, data freshness assumes paramount importance, as outdated data may engender unpredictable or catastrophic outcomes.To effectively measure data freshness in satellite-terrestrial integrated communications,age of information(AoI)has recently surfaced as a new dimension of QoS metric to support time-sensitive applications. It is crucial to design new analytical models that ensure stringent and diverse QoS metrics bounded by different key parameters,including AoI,delay,and reliability,over 6G satellite-terrestrial integrated networks. However,due to the complicated and dynamic nature of satellite-terrestrial integrated network environments, the research on efficiently defining new statistical QoS provisioning schemes while taking into account varying degrees of freedom has still been in their infancy. To remedy these deficiencies, in this paper we develop statistical QoS provisioning schemes over 6G satellite-terrestrial integrated networks in the finite blocklength regime. Particularly, we firstly introduce and review key technologies for supporting mURLLC.Secondly,we formulate a number of novel fundamental statistical-QoS metrics in the finite blocklength regime.Finally,we conduct a set of simulations to validate and evaluate our developed statistical QoS provisioning schemes over satellite-terrestrial integrated networks.

信息年龄约束下的无人机数据采集能耗优化路径规划算法

信息年龄(AoI)是评价无线传感器网络(WSN)数据时效性的重要指标,无人机辅助WSN数据采集过程中采用优化飞行轨迹、提升速度等运动策略保障卸载至基站的数据满足各节点AoI限制。然而,不合理的运动策略易导致无人机因飞行距离过长、速度过快产生非必要能耗,造成数据采集任务失败。针对该问题,该文首先提出信息年龄约束的无人机数据采集能耗优化路径规划问题并进行数学建模;其次,设计一种协同混合近端策略优化(CH-PPO)强化学习算法,同时规划无人机对传感器节点或基站的访问次序、悬停位置和飞行速度,在满足各传感器节点信息年龄约束的同时,最大限度地减少无人机能量消耗。再次,设计一种融合离散和连续策略的损失函数,增强CH-PPO算法动作的合理性,提升其训练效果。仿真实验结果显示,CH-PPO算法在无人机能量消耗以及影响该指标因素的比较中均优于对比的3种强化学习算法,并具有良好的收敛性、稳定性和鲁棒性。

基于人机混合智能的协同作战研究

体系作战是未来海上战争的主要模式,兵力协同是面向体系作战的具体手段;人机混合智能技术将人类智能和机器智能有机地结合起来,充分发挥人类和机器各自的智能优势,以提高系统整体的性能和效率,完成对海上协同作战任务的混合决策与作战;文章对现有人机混合智能决策作战的研究方法进行了论述和对比分析,并针对海战场协同作战决策系统,分析了不同模式的人机混合智能技术在海上协同作战方面的应用;在此基础上,提出了一种系统的人机混合智能协同作战方法,能够提高决策效率、增强态势感知能力和优化资源分配,为后续深入研究和完善海上智能协同作战提供了理论基础。