Optimal Cooperative Spectrum Sensing Based on Butterfly Optimization Algorithm

Since the introduction of the Internet of Things (IoT), several researchers have been exploring its productivity to utilize and organize the spectrum assets. Cognitive radio (CR) technology is characterized as the best aspirant for wireless communications to augment IoT competencies. In the CR networks, secondary users (SUs) opportunistically get access to the primary users (PUs) spectrum through spectrum sensing. The multipath issues in the wireless channel can fluster the sensing ability of the individual SUs. Therefore, several cooperative SUs are engaged in cooperative spectrum sensing (CSS) to ensure reliable sensing results. In CSS, security is still a major concern for the researchers to safeguard the fusion center (FC) against abnormal sensing reports initiated by the malicious users (MUs). In this paper, butterfly optimization algorithm (BOA)-based soft decision method is proposed to find an optimized weighting coefficient vector correlated to the SUs sensing notifications. The coefficient vector is utilized in the soft decision rule at the FC before making any global decision. The effectiveness of the proposed scheme is compared for a variety of parameters with existing schemes through simulation results. The results confirmed the supremacy of the proposed BOA scheme in both the normal SUs’ environment and when lower and higher SNRs information is carried by the different categories of MUs.     

An Optimized Algorithm for CR-MIMO Wireless Networks

With the rapid development of wireless communication technology, the spectrum resources are increasingly strained which needs optimal solutions. Cognitive radio (CR) is one of the key technologies to solve this problem. Spectrum sensing not only includes the precise detection of the communication signal of the primary user (PU), but also the precise identification of its modulation type, which can then determine the a priori information such as the PU’ service category, so as to use this information to make the cognitive user (CU) aware to discover and use the idle spectrum more effectively, and improve the spectrum utilization. Spectrum sensing is the primary feature and core part of CR. Classical sensing algorithms includes energy detection, cyclostationary feature detection, matched filter detection, and so on. The energy detection algorithm has a simple structure and does not require prior knowledge of the PU transmitter signal, but it is easily affected by noise and the threshold is not easy to determine. The combination of multiple-input multiple-output (MIMO) with CR improves the spectral efficiency and multi-path fading utilization. To best utilize the PU spectrum while minimizing the overall transmit power, an iterative technique based on semidefinite programming (SDP) and minimum mean squared error (MMSE) is proposed. Also, this article proposed a new method for max-min fairness beamforming. When compared to existing algorithms, the simulation results show that the proposed algorithms perform better in terms of total transmitted power and signal-to-interference plus noise ratio (SINR). Furthermore, the proposed algorithm effectively improved the system performance in terms of number of iterations, interference temperature threshold and balance SINR level which makes it superior over the conventional schemes.     

Optimisation of cooperative spectrum sensing in cognitive radio network

Spectrum sensing is a key problem in cognitive radio (CR). Because of a low SNR, fading and sensing time constraints, a single CR may not be able to reliably sense the presence of primary radios, which motivates the study of sensing by multiple cognitive users. Here, the authors consider cooperative spectrum sensing (CSS) using a counting rule where several cognitive users sense whether primary users exist or not and send their decisions to the centre where the final decision is made. Optimal strategies under both the Neyman-Pearson criterion and the Bayesian criterion for CSS are derived using a counting rule. In addition, the authors present simple methods to calculate the optimal settings. Another contribution here is the analysis of a randomised rule at the centre, which is a long-existing problem in the field of distributed detection systems.     

Fairness and throughput enhancement based resource allocation scheme for underlay cognitive radio networks

Acquiring good throughput and diminishing interference to primary users (PU) are the main objectives for secondary users in a cognitive radio (CR) network. This paper proposes a centralized subcarrier and power allocation scheme for underlay multi-user orthogonal frequency division multiplexing considering the rate loss and the interference those the PU can tolerate. The main purpose of the proposed scheme is to efficiently distribute the available subcarriers among cognitive users to enhance both the fairness and the throughput performance of the cognitive network while maintaining the QoS of primary users. Simulation results show that the proposed scheme achieves a significantly higher CR network throughput than that of the conventional interference power constraint (IPC) based schemes and provides a significantly enhanced fairness performance. Also, contrary to the conventional IPC based schemes, the proposed scheme is able to significantly increase the achieved throughput as the number of CR users increases.     

Comprehensive asynchronous symmetric rendezvous algorithm in cognitive radio networks

Spectrum has become a scant quantity with recent upsurge in the field of wireless communication. Cognitive radio network (CRN) alleviates the overgrowing spectrum scarcity and underutilization problem by adequately sharing the frequency bands between licensed and unlicensed users. CRN allows unlicensed users or secondary users (SUs) to opportunistically utilize the free portion of the spectrum allocated to the licensed users or primary users. The fundamental process in the formation of CRN is the rendezvous process where SUs meet on commonly available channels and establish reliable links for effective communication. Existing rendezvous solutions based on the assumption of a common control channel (CCC) among the SUs are infeasible and less efficient in the dynamic environment of CRNs. Therefore, channel hopping (CH) technique without CCC support, often referred to as blind rendezvous, is usually employed for accomplishing the rendezvous between SUs. This paper presents a comprehensive asynchronous symmetric rendezvous (CASR) algorithm that does not require time synchronization and guarantees rendezvous of SUs in finite time. CASR algorithm exploits the MAC address of SU as the unique identifier (ID) and generates CH sequence based on the dynamic manipulation of ID according to the number of available communication channels. Leveraging the unique ID of each SU, CASR algorithm succeeded in rendezvous guarantee while perpetuating a good time to rendezvous. The efficiency of CASR algorithm is estimated theoretically and verified through various simulation experiments. Simulation results affirm that CASR algorithm performs better in terms of average time-to-rendezvous as compared with existing rendezvous algorithms.     

Spectral efficiency of spectrum-pooling systems

The authors investigate the idea of using cognitive radio to reuse locally unused spectrum to increase the total system capacity. The authors consider a multiband/wideband system in which the primary and cognitive users wish to communicate to different receivers, subject to mutual interference and assume that each user knows only his/her channel and the unused spectrum through adequate sensing. The basic idea under the proposed scheme is based on the notion of spectrum pooling. The idea is quite simple; a cognitive radio will listen to the channel and, if sensed idle, will transmit during the voids. It turns out that, although its simplicity, the proposed scheme showed very interesting features with respect to the spectral efficiency and the maximum number of possible pairwise cognitive communications. We impose the constraint that users successively transmit over available bands through selfish water filling. For the first time, our study has quantified the asymptotic (with respect to the band) achievable gain of using spectrum pooling in terms of spectral efficiency compared with classical radio systems. The authors then derive the total spectral efficiency as well as the maximum number of possible pairwise communications of such a spectrum-pooling system.     

Resource Allocation for Throughput Maximization in Cognitive Radio Network with NOMA

Spectrum resources are the precious and limited natural resources. In order to improve the utilization of spectrum resources and maximize the network throughput, this paper studies the resource allocation of the downlink cognitive radio network with non-orthogonal multiple access (CRN-NOMA). NOMA, as the key technology of the fifth-generation communication (5G), can effectively increase the capacity of 5G networks. The optimization problem proposed in this paper aims to maximize the number of secondary users (SUs) accessing the system and the total throughput in the CRN-NOMA. Under the constraints of total power, minimum rate, interference and SINR, CRN-NOMA throughput is maximized by allocating optimal transmission power. First, for the situation of multiple sub-users, an adaptive optimization method is proposed to reduce the complexity of the optimization solution. Secondly, for the optimization problem of nonlinear programming, a maximization throughput optimization algorithm based on Chebyshev and convex (MTCC) for CRN-NOMA is proposed, which converts multi-objective optimization problem into single-objective optimization problem to solve. At the same time, the convergence and time complexity of the algorithm are verified. Theoretical analysis and simulation results show that the algorithm can effectively improve the system throughput. In terms of interference and throughput, the performance of the sub-optimal solution is better than that of orthogonal-frequency-division-multiple-access (OFDMA). This paper provides important insights for the research and application of NOMA in future communications.     

基于卡方检验的多天线认知无线网络协作频谱感知算法

研究了基于分集的多天线认知无线网络的频谱感知技术。针对天线独立性会导致已有的基于协方差矩阵的协作频谱感知算法性能急剧下降甚至失效的问题,提出了一种基于卡方拟合优度检验的多天线协作频谱感知算法。该算法将频谱感知问题转化为一个多项分布检验的问题,然后利用卡方拟合优度检验判决频谱是否空闲,从而实现频谱感知。理论分析和仿真表明,该算法的性能不受天线相关性以及噪声不确定度的影响。     

Performance Analysis of Multi-Channel CR Enabled IoT Network with Better Energy Harvesting

Wireless Sensor Networks (WSNs) can be termed as an auto-configured and infrastructure-less wireless networks to monitor physical or environmental conditions, such as temperature, sound, vibration, pressure and motion etc. WSNs may comprise thousands of Internet of Things (IoT) devices to sense and collect data from its surrounding, process the data and take an automated and mechanized decision. On the other side the proliferation of these devices will soon cause radio spectrum shortage. So, to facilitate these networks, we integrate Cognitive Radio (CR) functionality in these networks. CR can sense the unutilized spectrum of licensed users and then use these empty bands when required. In order to keep the IoT nodes functional all time, continuous energy is required. For this reason the energy harvested techniques are preferred in IoT networks. Mainly it is preferred to harvest Radio Frequency (RF) energy in the network. In this paper a region based multi-channel architecture is proposed. In which the coverage area of primary node is divided as Energy Harvesting Region and Communication Region. The Secondary User (SU) that are the licensed user is IoT enabled with Cognitive Radio (CR) techniques so we call it CR-enabled IoT node/device and is encouraged to harvest energy by utilizing radio frequency energy. To harvest energy efficiently and to reduce the energy consumption during sensing, the concept of overlapping region is given that supports to sense multiple channels simultaneously and help the SU to find best channel for transmitting data or to harvest energy from the ideal channel. From the experimental analysis, it is proved that SU can harvest more energy in overlapping region and this architecture proves to consume less energy during data transmission as compared to single channel. We also show that channel load can be highly reduced and channel utilization is proved to be more proficient. Thus, this proves the proposed architecture cost-effective and energy-efficient.     

Using Embedded Dynamic Random Access Memory to Reduce Energy Consumption of Magnetic Recording Read Channel

Although the performance of a magnetic recording read channel can be improved by employing advanced iterative signal detection and coding techniques, the method nevertheless tends to incur significant silicon area and energy consumption overhead. Motivated by recent significant improvement of high-density embedded dynamic random access memory (eDRAM) towards high manufacturability at low cost, we explored the potential of integrating eDRAM in read channel integrated circuits (IC) to minimize the silicon area and energy consumption cost incurred by iterative signal detection and coding. As a result of the memory-intensive nature of iterative signal detection and coding algorithms, the silicon cost can be reduced in a straightforward manner by directly replacing conventional SRAM with eDRAM. However, reducing the energy consumption may not be trivial. In this paper, we present two techniques that trade eDRAM storage capacity to reduce the energy consumption of iterative signal detection and coding datapath. We have demonstrated dDRAM's energy saving potential by designing a representative iterative read channel at the 65 nm technology node. Simulation shows that we can eliminate over 99.99% of post-processing computation for dominant error events detection, and achieve up to a 67% reduction of decoding energy consumption.     

Interaction between radio link level truncated ARQ, and TCP in multi-rate wireless networks: a cross-layer performance analysis

A complete queueing model for radio link layer performance analysis is developed assuming adaptive modulation and coding (AMC) at the physical layer and truncated automatic repeat request (ARQ)-based error control at the link layer. From the model, queue length distribution and average queueing delay can be calculated. The average queueing delay is then used to estimate transmission control protocol (TCP) throughput performance using a fixed-point approach. Using the model, we are able to choose signal-to-noise ratio thresholds of different transmission modes for AMC at the physical layer for different persistence levels of ARQ at the link layer so that TCP throughput is maximized. We observe that channel correlation negatively impacts the TCP throughput performance. Also, throughput enhancement of TCP NewReno over TCP Reno is observed to be non-negligible only if no ARQ-based error recovery is employed at the link layer.     

基于gOMP算法的FBMC水声通信信道估计方法

传统基于训练序列及块状导频结构的滤波器组多载波（Filter Bank Multicarrier,FBMC）信道估计方法花费额外的频谱资源,这在频谱资源较为紧张的水声通信环境中具有一定的局限性。针对这一问题并结合水声信道稀疏性的特点,文章提出了一种基于压缩感知的离散导频结构FBMC信道估计方法。首先基于等效导频能量最大化的思想,设计了一种新的离散导频结构来解决FBMC系统信道估计时存在的固有虚部干扰问题;然后配合该结构,提取出导频处的接收信息并利用重构效果优良的压缩感知gOMP算法对水声信道进行重构。该方法在保证水声信道估计精度的同时有效提高了FBMC系统的频谱利用率,改善了水声通信的性能。仿真结果表明,文中所提方法相较于传统方法在估计精度和频谱利用率方面具有一定的优越性。     

Wideband spectrum sensing in unknown white Gaussian noise

The spectrum sensing of a wideband frequency range is studied by dividing it into multiple subbands. It is assumed that in each subband either a primary user (PU) is active or absent in a additive white Gaussian noise environment with an unknown variance. It is also assumed that at least a minimum given number of subbands are vacant of PUs. In this multiple interrelated hypothesis testing problem, the noise variance is estimated and a generalised likelihood ratio detector is proposed to identify possible spectrum holes at a secondary user (SU). Provided that it is known that a specific PU can occupy a subset of subbands simultaneously, a grouping algorithm which allows faster spectrum sensing is proposed. The collaboration of multiple SUs can also be considered in order to enhance the detection performance. The collaborative algorithms are compared in terms of the required exchange information among SUs in some collaboration methods. The simulation results show that the proposed detector outperforms the energy detector in the presence of noise variance mismatch above 2.3 dB. Some involved trade-offs in the spectrum sensing using the proposed detector are discussed.     

Outage Capacity Analysis for Cognitive Non-Orthogonal Multiple Access Downlink Transmissions Systems in the Presence of Channel Estimation Error

In this paper, we propose a downlink cognitive non-orthogonal multiple access (NOMA) network, where the secondary users (SUs) operate in underlay mode. In the network, secondary transmitter employs NOMA signaling for downlink transmission, and the primary user (PU) is interfered by the transmission from SU. The expressions for the outage probabilities are derived in closed-form for both primary and secondary users in the presence of channel estimation error. Numerical simulation results show that the channel estimation error and the inter-network interference cause degradation of the downlink outage performance. Also the power allocation and the location have a significant impact on the outage probability. The numerical experiments demonstrate that the analytic expressions of the outage probabilities match with the simulation results.     

Adaptive code-division multiple-access system for communications over indoor wireless optical channels based on random optical codes

The authors have designed an adaptive optical codes-based system for communications over the indoor wireless optical channel when large numbers of users access to the channel simultaneously. This system uses a code-division multiple access (CDMA) scheme based on the named random optical codes (ROC). The authors present the characteristics of this kind of optical codes and several results about its performance over noisy indoor wireless optical channels. Finally, the authors describe a CDMA system which adapts its performance to the number of users which are accessing simultaneously to the channel. The proposed system is able to maintain a target bit error rate adapting its data throughput independently of the number of simultaneous users in the optical environment, whenever certain conditions are accomplished.     

Analysis of operating policies for manufacturing cells

We present an analytical model for error-recovery problems of unitary production cells and develop a framework for economic justification. Each production cell has its own machine and functional characteristics (e.g. precision, speed, operating cost). Each alternative operating policy of error-recovery for a production cell leads to a different system throughput, scrap rate, and required quantities of parts. However, error recovery cannot be accomplished without in-process inspections. Thus, the central problem discussed in this paper is to maximize profits or throughput rate by selecting an appropriate production cell along with an optimal set of inspection and error recovery policies.     

单载波频域判决反馈均衡水声通信技术研究

水声信道中多途干扰严重,由多途效应引起的码间干扰是影响水声通信系统的关键性因素。单载波频域均衡(Single-Carrier Frequency Domain Equalization,SC-FDE)技术基于正交频分复用(Orthogonal Frequency Division Multiplexing,OFDM)技术提出,能有效对抗水声信道中的多途干扰,同时能避免OFDM技术峰值平均功率比高的不足。文中先介绍判决反馈均衡算法,并与其他均衡算法的抗多途性能进行比较。然后为提高系统均衡的可靠性和水声信道带宽利用率,对传统数据帧结构进行改进。将独特字(Unique Words,UW)序列均分,提高水声信道估计的精度,进而降低误码率,增加传输的可靠性;增加数据帧中有用信息符号,系统误码性能几乎不变,水声信道频带有效利用率提高。最后开展水池试验,验证了算法的有效性和可靠性。     

基于神经网络的遥感图像分类的新方法研究

随着神经网络理论的深入研究,人工神经网络在遥感图像分析与处理的各个方面都有广泛的适用性,并且已经取得了较好的效果,是遥感信息提取的一种有效途径。本文介绍了BP神经网络在遥感影像分类中的应用,通过自适应和在网络权值调整过程中加入特征因子算法,并结合Matlab软件,改进了BP神经网络的优化算法,使网络对误差变化敏感且收敛速度陕,减少了人为因素的干预,改善了学习速率和网络的适应能力,而且精度可靠。     

Proportional Fairness-Based Power Allocation Algorithm for Downlink NOMA 5G Wireless Networks

Non-orthogonal multiple access (NOMA) is one of the key 5G technology which can improve spectrum efficiency and increase the number of user connections by utilizing the resources in a non-orthogonal manner. NOMA allows multiple terminals to share the same resource unit at the same time. The receiver usually needs to configure successive interference cancellation (SIC). The receiver eliminates co-channel interference (CCI) between users and it can significantly improve the system throughput. In order to meet the demands of users and improve fairness among them, this paper proposes a new power allocation scheme. The objective is to maximize user fairness by deploying the least fairness in multiplexed users. However, the objective function obtained is non-convex which is converted into convex form by utilizing the optimal Karush-Kuhn-Tucker (KKT) constraints. Simulation results show that the proposed power allocation scheme gives better performance than the existing schemes which indicates the effectiveness of the proposed scheme.     

Information theoretic criterion-based spectrum sensing for cognitive radio

Energy detection is a promising candidate for spectrum sensing of cognitive radio systems due to its merits of simplicity and easy implementation. However, energy detection needs to subjectively pre-configure a threshold and requires the knowledge of noise power. Furthermore, energy detection is vulnerable to noise uncertainty, which inevitably occurs in practical implementations. To solve the above problems, two spectrum sensing methods requiring no knowledge of noise power and no subjective threshold settings are proposed based on the information theoretic criterion. Additionally, the most important advantage of these methods is that their performance is totally unaffected by noise uncertainty. Finally, simulation results are provided to demonstrate the benefits of these methods.