Route selection for interference minimization to primary users in cognitive radio ad hoc networks: A cross layer approach

An opportunistic routing problem in a cognitive radio ad hoc network is investigated with an aim to minimize the interference to primary users (PUs) and under the constraint of a minimum end-to-end data rate for secondary users (SUs). Both amplify-and-forward (AF) and decode-and-forward (DF) relaying techniques are considered for message forwarding by SU nodes in the network. Unlike popular transmit power control based solutions for interference management in cognitive radio networks, we adopt a cross layer approach. The optimization problem is formulated as a joint power control, channel assignment and route selection problem. Next, closed form expression for transmission power is derived and corresponding channel selection scheme and routing metric are designed based on this solution. The proposed route selection schemes are shown to depend not only on gains of the interference channels between SUs and PUs but also on the values of the spectrum sensing parameters at the SU nodes in the network. Two distributed routing schemes are proposed based on our analysis; (i) optimal_DF and (ii) suboptimal_AF. The routing schemes could be implemented using existing table driven as well as on demand routing protocols. Extensive simulation results are provided to evaluate performance of our proposed schemes in random multihop networks. Results show significant reduction in PUs’ average interference experience and impressive performance as opportunistic routing schemes can be achieved by our schemes compared to traditional shortest path based routing schemes. Performance improvement is also reported over prominent recent schemes.     

A multi-timescale resource allocation algorithm based on self-learning for distributed fog radio access networks

Faced with limited network resources, diverse service requirements and complex network structures, how to efficiently allocate resources and improve network performances is an important issue that needs to be addressed in 5G or future 6G networks. In this paper, we propose a multi-timescale collaboration resource allocation algorithm for distributed fog radio access networks (F-RANs) based on self-learning. This algorithm uses a distributed computing architecture for parallel optimization and each optimization model includes large time-scale resource allocation and small time-scale resource scheduling. First, we establish a large time-scale resource allocation model based on long-term average information such as historical bandwidth requirements for each network slice in F-RAN by long short-term memory network (LSTM) to obtain its next period required bandwidth. Then, based on the allocated bandwidth, we establish a resource scheduling model based on short-term instantaneous information such as channel gain by reinforcement learning (RL) which can interact with the environment to realize adaptive resource scheduling. And the cumulative effects of small time-scale resource scheduling will trigger another round large time-scale resource reallocation. Thus, they constitute a self-learning resource allocation closed loop optimization. Simulation results show that compared with other algorithms, the proposed algorithm can significantly improve resource utilization.     

Transmit power and bits/channel use adaption in competitive cognitive radio networks

In this paper, we propose an optimization framework to determine the distribution of power and bits/channel use to secondary users in a competitive cognitive radio networks. The objectives of the optimization framework are to minimize total transmission power, maximize total bits/channel use and also to maintain quality of service. An upper bound on probability of bit error and lower bound on bits/channel use requirement of secondary users are considered as quality of service. The optimization problem is also constrained by total power budget across channels for a user. Simulating the framework in a centralized manner shows that more transmit power is required to allocate in a channel with higher noise power. However, allocation of bits/channel use is directly proportional to signal to interference plus noise power ratio. The proposed framework is more capable of supporting high bits/channel use requirement than existing resource allocation framework. We also develop the game theoretic user based distributed approach of the proposed framework. We see that user based distributed solution also follows centralized solution.     

Utilization of spatial ternary coding scheme in optical CDMA system

In this paper, we propose a spatial ternary coding scheme for optical code-division multiple access systems. Since the multiple access interference (MAI) and beat noise leads to the error floor effect, using error correction mechanism is a preferable manner to further enhance the system performance. The proposed spatial ternary coding scheme possesses larger free distance, which is an effective way to relieve such deteriorating effect. It is expected that more users accommodated in the network can obtain higher throughput, while the side effects of MAI and beat noise will turn out to be more serious. To further reduce such adverse impact, the optical hard-limiter is also proposed. Once the channel condition is improved, it will give rise to the more powerful utilization of error correction code. The countermeasures utilized in the proposed system can effectively fight against the MAI and beat noise, and can allow more simultaneous users accommodated in the network. Therefore, it is a promising way for future high-speed optical access networks.     

Performance analysis of overlay cognitive NOMA network with imperfect SIC and imperfect CSI

In this paper, we investigate a multiple users cooperative overlay cognitive radio non-orthogonal multiple access (CR-NOMA) network in the presence of imperfect successive interference cancellation (SIC) and imperfect channel state information (CSI). In the context of cellular network, cell-center cognitive secondary users act as relays to assist transmission from the primary user (PU) transmitter to the cell-edge PU receiver via NOMA. According to the received signals between the primary transmitter and multiple cognitive secondary center users, the best cell-center cognitive SU with the maximum signal to noise ratio (SNR) is selected to transmit the PU’s signals and its own signal to cell-edge users through NOMA principle. Then, the PU cell-edge user combine the signals received from direct transmission in the first phase and relay transmission from the best cell-center cognitive SU in the second phase by selection combining (SC). To measure the performance of the system quantitatively, we derive the end-to-end outage probability and capacity for the primary and secondary networks by taking the imperfect SIC and CSI into consideration. Finally, the performance analysis is validated by the simulations, and show that serious interference caused by imperfect SIC and (or) imperfect CSI reduce the system performance.     

航空通信网络中复杂干扰过滤技术研究

航空通信环境中存在复杂的干扰信号,对正常的通信信号造成强烈的干扰。利用传统算法进行干扰信号过滤,无法避免由于干扰信号过于复杂导致过滤不充分的缺陷。提出一种基于加权残差优化算法的航空通信网络中复杂干扰过滤方法。对原始信号进行降频处理,能够消除峰值干扰信号,提高了信号的准确性。根据加权残差修正优化算法的相关原理,对通信信号进行残差优化处理,经过处理后的通信信号在受到干扰时会形成零陷,实现了对复杂干扰信号的过滤。实验结果表明,利用该算法进行航空通信网络中复杂干扰信号过滤,能够有效提高过滤的准确性,效果令人满意。     

Design and performance analysis in multiuser optical CDMA systems

The article presents comparative performance analysis of the proposed Optical CDMA system for 32 and 16 users with two dimensional codes. Numerical simulations have been done under interference significant environment, considering noise and dark current at data rates 2.5, 5, 7.5 and 10 Gbps over single mode fiber for transmission distance of more than 270 km. Results illustrate overall good performance, degraded with augment in bit rate and transmission distance, impervious with raise in number of simultaneous active users. Depicts significant performance improvement with inclusion of forward error correction RS (255,239), for low attenuation and chirp factor. It perceived, this is one of the efficient functional techniques for next generation broadband optical networks together with higher security owing to encoding and decoding, as it allow multiple users in the network to access the same fiber channel asynchronously.     

A survey on UAV placement optimization for UAV-assisted communication in 5G and beyond networks

With the increase in capacity demands and the requirement of ubiquitous coverage in the fifth generation and beyond wireless communications networks, unmanned aerial vehicles (UAVs) have acquired a great attention owing to their outstanding characteristics over traditional base stations and relays. UAVs can be deployed faster and with much lower expenditure than ground base stations. In addition, UAVs can enhance the network performance thanks to their strong line-of-sight link conditions with their associated users and their dynamic nature that adapts to varying network conditions. Optimization of the UAV 3D locations in a UAV-assisted wireless communication network was considered in a large body of research as it is a critical design issue that greatly affects communication performance. Although the topic of UAV placement optimization was considered in few surveys, these surveys reviewed only a small part of the growing literature. In addition, the surveys were brief and did not discuss many important design issues such as the objectives of the optimization problem, the adopted solution techniques, the air-to-ground channel models, the transmission media for access and backhaul links, the limited energy nature of the UAV on-board batteries, co-channel interference and spectrum sharing, the interference management, etc. Motivated by the importance of the topic of UAV placement optimization as well as the need for a detailed review of its recent literature, we survey 100 of the recent research papers and provide in-depth discussion to fill the gaps found in the previous survey papers. The considered research papers are summarized and categorized to highlight the differences in the deployment scenario and system model, the optimization objectives and parameters, the proposed solution techniques, and the decision-making strategies and many other points. We also point to some of the existing challenges and potential research directions that have been considered in the surveyed literature and that requires to be considered     

基于最优滤波器的强混沌背景中谐波信号检测方法研究

强混沌背景中的微弱谐波信号检测有重要的工程研究意义. 目前的检测方法主要是基于Takens理论的混沌相空间重构方法, 然而这些方法往往对信干噪比要求高, 且对高斯白噪声敏感等. 本文注意到混沌信号的二阶统计特性是不变的, 根据这个特点提出了一种基于最优滤波器的强混沌背景中的微弱谐波信号检测方法. 该方法首先构建一个数据矩阵, 在频域上对每个频率通道分别检测谐波信号, 从而将信号检测问题转化为最优化问题, 然后利用最优化理论设计滤波器, 使待检测频率通道的信号增益保持不变, 而尽量抑制其他频率通道的信号, 最后通过判断每一频率通道的输出信干噪比来检测谐波信号. 与传统方法相比, 本文方法有如下优点: 1)可以检测更低信干噪比下的微弱谐波信号; 2)可检测的信号幅度范围更大; 3)抗白噪声性能更强. 仿真结果证明了本文方法的有效性.     

Robust secrecy rate maximization in IRS-assisted cognitive radio networks

In this paper, we focus on the secrecy rate maximization problem in intelligent reflecting surface (IRS)-assisted cognitive radio (CR) networks. In order to improve the security, there is a common scheme to add artificial noise (AN) to the transmitted signal, which is also applied in this paper. Further, in CR networks, the secondary users always cannot obtain accurate channel state information (CSI) about the primary user and eavesdropper. By taking jointly design for the IRS phase shift matrix, the transmitted beamforming of the secondary base station (BS), and the covariance matrix of AN, our objective is to maximize the minimal secrecy rate of all secondary users. Due to the serious coupling among the designed variables, it cannot be solved by conventional methods. We propose an alternating optimization (AO) algorithm. In simulation results, we apply primary users and secondary users randomly distributed in the communication area, which numerically demonstrate the superiority of our proposed scheme.     

An energy efficient scheme by exploiting multi-hop D2D communications for 5G networks

The multi-hop Device-to-Device (M-D2D) communication has a potential to serve as a promising technology for upcoming 5G networks. The prominent reason is that the M-D2D communication has the potential to improve coverage, enhanced spectrum efficiency, better link quality, and energy-efficient communication. One of the major challenges for M-D2D communication is the mitigation of interference between the cellular user (CUs) and M-D2D users. Considering this mutual interference constraint, this work investigates the problem of optimal matching of M-D2D links and CUs to form spectrum-sharing partners to maximize overall sum rates of the cell under QoS and energy efficiency (EE) constraints. In this paper, we investigate the interference management for multi-hop (more than one-hop) D2D communication scenarios where we propose a channel assignment scheme along with a power allocation scheme. The proposed channel assignment scheme is based on the Hungarian method in which the channel assignment for M-D2D pairs is done by minimum interference value. The power allocation scheme is based on Binary Particle swarm optimization (BPSO). This scheme calculates the specific power values for all the individual M-D2D links. We have done a comprehensive simulation and the result portrays that our proposed scheme performs better compared to the previous work mentioned in the literature. The results clearly indicate that the proposed scheme enhances the EE of up to 13% by producing the optimal assignment of channels and power for the CUs and M-D2D users.     

Energy Efficiency of User-Centric,Cell-Free Massive MIMO-OFDM with Instantaneous CSI

In the user-centric, cell-free, massive multi-input, multi-output (MIMO) orthogonal frequency division multiplexing (OFDM) system, a large number of deployed access points (APs) serve user equipment (UEs) simultaneously, using the same time–frequency resources, and the system is able to ensure fairness between each user; moreover, it is robust against fading caused by multi-path propagation. Existing studies assume that cell-free, massive MIMO is channel-hardened, the same as centralized massive MIMO, and these studies address power allocation and energy efficiency optimization based on the statistics information of each channel. In cell-free, massive MIMO systems, especially APs with only one antenna, the channel statistics information is not a complete substitute for the instantaneous channel state information (CSI) obtained via channel estimation. In this paper, we propose that energy efficiency is optimized by power allocation with instantaneous CSI in the user-centric, cell-free, massive MIMO-OFDM system, and we consider the effect of CSI exchanging between APs and the central processing unit. In addition, we design different resource block allocation schemes, so that user-centric, cell-free, massive MIMO-OFDM can support enhanced mobile broadband (eMBB) for high-speed communication and massive machine communication (mMTC) for massive device communication. The numerical results verify that the proposed energy efficiency optimization scheme, based on instantaneous CSI, outperforms the one with statistical information in both scenarios.     

基于休眠机理的三维小基站蜂窝网络能效优化

小基站通常部署在写字楼、商贸区等城市密集区域以弥补传统宏基站在覆盖和传输方面的不足.小基站的分布一般是根据高峰时的网络负荷设计的,这必然导致网络负荷较低时的资源浪费.讨论了在平均接入率和信道容量双重约束下基于休眠机理的三维小基站蜂窝网络的能效优化问题.借助泊松点过程理论推导了三维小基站网络下行信道容量和平均接入率的数学表达式.通过分析下行信道容量和平均接入率的单调性得出同时满足传输信道容量和接入率要求的最佳休眠概率.分析了小基站最大用户连接数的最佳值,通过对该参数的合理配置,可以在满足通信指标的前提下最大程度地降低网络能耗.仿真结果表明,设计的基站休眠机理可以使小基站网络的能耗下降约21%.     

Optimal resource scheduling algorithm for cell boundaries users in heterogenous 5G networks

Deployment of small cells over the existing cellular network is an effective solution to improve the system coverage and throughput of fifth generation (5G) mobile communication networks. The arrival of the 5G mobile networks have demonstrated the importance of advanced scheduling techniques to manage the limited frequency spectrum available while achieving 5G transmission requirements. Cellular networks of the future necessitate the formulation of efficient resource allocation schemes that mitigate the interference between the different cells. In this research work, we formulate an optimization problem for heterogenous networks (HetNets) for resource allocation to maximize the system throughput among the cell center users (CCUs) and cell edge users (CEUs). We solve the optimization problem by effective utilization of the weight factors distribution for resource allocation. A novel Utility-based Resource Scheduling Algorithm (URSA) optimizes the resource sharing among the users with better delay budget of each application. The designed URSA ameliorates fairness along with reduced cross layer interference for real and non-real time applications. Performance of the URSA has been evaluated and compared most relevant state of art algorithms using the matlab based simulators. Furthermore, simulation results validate the superiority of the proposed scheduling scheme against conventional techniques in terms of throughput, fairness, and spectral efficiency.     

Deep Q-learning based optimal resource allocation method for energy harvested cognitive radio networks

In this article, we propose a deep Q-learning based algorithm for optimal resource allocation in energy harvested cognitive radio networks (EH-CRN). In EH-CRN, channel resources of primary users (PU) networks are shared with secondary users (SU) and energy harvesting allows nodes of the CRN to acquire energy from the environment for operation sustainability. However, amount of energy harvested from the environment is not fixed and requires dynamic allocation of resources for obtaining optimum network and throughput capacity. In this work, we overcome the limitations of existing Q-learning based resource allocation schemes which are constrained by large state-space systems and have slow convergence. Proposed deep Q-learning based algorithm improves the resource allocation in EH-CRN, while considering quality of service (QoS), energy and interference constraints. Simulation results show that proposed algorithm provide improved convergence and better resource utilization compared to other techniques in literature.     

Exploitation of the Fiber Capacity in Optical Networks Using Time,Frequency, and Space Division Multiple Accesses

In this work we investigate how to obtain very high capacity transmissions in optical networks taking into account the limitations due to the physical channel. We consider both the case in which all the users are connected by a star coupler and the case in which the users are directly connected by the network topology. As a reference, we consider a ring network and a Shuffle Multihop Network (SMN). The use of optical systems to implement high-capacity networks is numerically investi gated by means of numerical simulations taking into consideration the channel limitations due to the chromatic dispersion, the Kerr effect, and the amplified spontaneous emission (ASE) noise of the optical amplifiers. In our model, we consider that the signal, during the routing process that is performed at the user position, undergoes only an attenuation. We suppose the use of intensity modulated signals and receivers with direct detection. Packet switching and digital transmission are assumed with soliton and conventional nonreturn to zero signals. Both wave length and time division multiple accesses are considered. The results show that, in the case of the Time Division Multiple Access (TDMA) technique, the use of a star coupler to connect the users reduces the capacity of a network with respect to the case in which a direct connection of the users is used. This is due to the strong power fluctuations that are present during the signal propagation and to the large quantity of accumulated ASE noise. On the other hand, the use of a star coupler shows the advantage to being easily reconfigurable. The Wavelength Divison Multiple Access (WDMA) technique permits us to achieve higher capacities with respect to the TDMA. This is due to the fact that in the propagation conditions, due to the presence of a star coupler, high bit rate signals are strongly degraded. On the other hand, several low bit rate signals operating at different wavelengths can propagate with a low power level, avoiding strong degradation due to the Four Wave Mixing (FWM) effect. Among the topologies considered in this work, the SMN is the one that generally permits us to reach the highest throughput because in the SMN the signal hops in a limited number of Network Interface Units (NIUs) before reaching the final destination.     

Exploitation of the Fiber Capacity in Optical Networks Using Time, Frequency, and Space Division Multiple Accesses

In this work we investigate how to obtain very high capacity transmissions in optical networks taking into account the limitations due to the physical channel. We consider both the case in which all the users are connected by a star coupler and the case in which the users are directly connected by the network topology. As a reference, we consider a ring network and a Shuffle Multihop Network (SMN). The use of optical systems to implement high-capacity networks is numerically investi gated by means of numerical simulations taking into consideration the channel limitations due to the chromatic dispersion, the Kerr effect, and the amplified spontaneous emission (ASE) noise of the optical amplifiers. In our model, we consider that the signal, during the routing process that is performed at the user position, undergoes only an attenuation. We suppose the use of intensity modulated signals and receivers with direct detection. Packet switching and digital transmission are assumed with soliton and conventional nonreturn to zero signals. Both wave length and time division multiple accesses are considered. The results show that, in the case of the Time Division Multiple Access (TDMA) technique, the use of a star coupler to connect the users reduces the capacity of a network with respect to the case in which a direct connection of the users is used. This is due to the strong power fluctuations that are present during the signal propagation and to the large quantity of accumulated ASE noise. On the other hand, the use of a star coupler shows the advantage to being easily reconfigurable. The Wavelength Divison Multiple Access (WDMA) technique permits us to achieve higher capacities with respect to the TDMA. This is due to the fact that in the propagation conditions, due to the presence of a star coupler, high bit rate signals are strongly degraded. On the other hand, several low bit rate signals operating at different wavelengths can propagate with a low power level, avoiding strong degradation due to the Four Wave Mixing (FWM) effect. Among the topologies considered in this work, the SMN is the one that generally permits us to reach the highest throughput because in the SMN the signal hops in a limited number of Network Interface Units (NIUs) before reaching the final destination.     

Power efficient and coordinated eICIC-CPC-ABS method for downlink in LTE-advanced heterogeneous networks

In 2020, mobile data traffic is expected to be a thousand times more than the current scenario. In order to handle this increased capacity, improvement in spectral efficiency is one of the challenging task. In long term evolution (LTE) and long term evolution advanced (LTE-A), deployment of small cell base station (SBS) and hotspot are step to handle the increased capacity of the network and quality of service. In this scenario, the SBSs are deployed under the coverage of macro cell base station (MBS). Neighbour MBS and neighbour SBS create intra and inter-cell interference to the users in the overlapped region. In order to mitigate interference, coordination between base stations is required. In this paper, we propose an enhanced intercell interference coordination by considering centralized processing controller with almost blank subframe (eICIC-CPC-ABS) for heterogeneous networks (HetNets). Centralized processing controller (CPC) at MBS decides the radio resource allocation of each SBSs based on user location. The dynamic frequency and reduced transmission power depend on the user locations. The analytical and simulation results demonstrate that the proposed method (eICIC-CPC-ABS) provides higher signal to interference plus noise ratio (SINR) compared to existing models: inter cell interference coordination (ICIC) and enhanced inter cell interference coordination (eICIC). The proposed method provides significant savings in transmitting power. Additionally, it increases the network capacity and coverage.     

异构网络动态配置空白子帧干扰协调算法

为了解决LTE-A系统下两层异构网络中的小区间干扰协调问题,提出了在增强小区中调度几乎空白子帧的干扰方案。为了降低干扰和进一步提高信道利用率,设计了一种动态分配几乎空白子帧的算法。该算法基于小区增强覆盖技术,指出由增强小区用户与总用户的比例来动态的调整几乎空白子帧比例。仿真结果对比了固定比例的几乎空白子帧和动态设定几乎空白子帧的算法,表明动态配置几乎空白子帧的算法,提高了系统容量,改善了信道利用率。     

Joint Deep Reinforcement Learning and Unsupervised Learning for Channel Selection and Power Control in D2D Networks

Device-to-device (D2D) technology enables direct communication between devices, which can effectively solve the problem of insufficient spectrum resources in 5G communication technology. Since the channels are shared among multiple D2D user pairs, it may lead to serious interference between D2D user pairs. In order to reduce interference, effectively increase network capacity, and improve wireless spectrum utilization, this paper proposed a distributed resource allocation algorithm with the joint of a deep Q network (DQN) and an unsupervised learning network. Firstly, a DQN algorithm was constructed to solve the channel allocation in the dynamic and unknown environment in a distributed manner. Then, a deep power control neural network with the unsupervised learning strategy was constructed to output an optimized channel power control scheme to maximize the spectrum transmit sum-rate through the corresponding constraint processing. As opposed to traditional centralized approaches that require the collection of instantaneous global network information, the algorithm proposed in this paper used each transmitter as a learning agent to make channel selection and power control through a small amount of state information collected locally. The simulation results showed that the proposed algorithm was more effective in increasing the convergence speed and maximizing the transmit sum-rate than other traditional centralized and distributed algorithms.