User Transmission Research Articles

User scheduling and power allocation for nonfull buffer traffic in NOMA downlink systems

SummaryNonorthogonal multiple access (NOMA) is one of the key technologies for 5G, where the system capacity can be increased by allowing simultaneous transmission of multiple users at the same radio resource. The most of the proportional fairness (PF)–based resource allocation studies for NOMA systems assumes full buffer traffic model, while the traffic in real‐life scenarios is generally nonfull buffer. In this paper, we propose User Demand–Based Proportional Fairness (UDB‐PF) and Proportional User Satisfaction Fairness (PUSF) algorithms for user scheduling and power allocation in NOMA downlink systems when traffic demands of the users are limited and time‐varying. UDB‐PF extends the PF‐based scheduling by allocating optimum power levels towards satisfying the traffic demand constraints of user pair in each resource block. The objective of PUSF is to maximize the network‐wide user satisfaction by allocating sufficient frequency and power resources according to traffic demands of the users. In both cases, user groups are selected first to simultaneously transmit their signals at the same frequency resource, while the optimal transmission power level is assigned to each user to optimize the underlying objective function. In addition, the genetic algorithm (GA) approach is employed for user group selection to reduce the computational complexity. When the user traffic rate requirements change rapidly over time, UDB‐PF yields better sum rate (throughput) while PUSF provides better network‐wide user satisfaction results compared with the PF‐based user scheduling. We also observed that the GA‐based user group selection significantly reduced the computational load while achieving the comparable results of the exhaustive search.

Allocation of optimal energy in an energy-harvesting cooperative multi-band cognitive radio network

This paper studies the achievable total throughput of an energy harvesting cooperative cognitive radio (CR) network. A CR transmitter cooperates with a primary user (PU) transmission if PU is found to be present in the given channel while it transmits its own data in the absence of PU. The CR transmitter is an energy harvesting node which harvests simultaneously from non-RF signal as well as RF signal of PU. The CR transmitter uses the harvested energy on shared basis for cooperation and transmission. The same study is also extended for cooperation of multiple CRs in multiple PU band scenario. In cooperation in muti-band scenario, all CRs sense all PU channels and sensing informations are fused at fusion centre to know about the status of PU. Performance is investigated in terms of total network throughput for several parameters such as sensing time, energy splitting parameter, and energy allocation ratio etc. Novel analytical expressions for total useful throughput and optimal energy allocation ratio parameter under the considered network scenario are developed. Useful throughput and optimal energy allocation ratio parameter are also estimated for a target secondary network (CR network) throughput under a quality of service constraint of PU such as collision probability. It is observed that the value of optimal energy allocation parameter gets reduced if the number of CRs in cooperation increases or the number of PU channels increases.

Energy-Efficient Cloudlet Management for Privacy Preservation in Wireless Metropolitan Area Networks

Currently, cloudlet based wireless metropolitan area network (WMAN) is emerging as an effective paradigm to extend the performance of mobile devices, which enables the execution of computational intensive mobile applications. But the normal operation of cloudlets consumes a large amount of energy, which brings about carbon dioxide emissions, aggravation of the greenhouse effect, etc. Meanwhile the data transmission of various mobile users among cloudlets would cause leakage of personal privacy. In view of this challenge, we propose an energy-efficient cloudlet management method, named ECM, for privacy preservation in WMAN. Technically, an optimization model is designed to formalize our problem. Then, based on live virtual machine (VM) migration technique, a corresponding privacy-aware VM scheduling method for energy saving is designed to determine which VMs should be migrated and where they should be migrated. Finally, experimental data demonstrate that the proposed method is both efficient and effective.

Resource Allocation with Successive Coding for OFDM-Based Cognitive System Subject to Statistical CSI

This paper investigates the resource allocation problem for a multicarrier underlay cognitive radio system, under the assumption that only statistical Channel State Information (CSI) about the primary channels is available at the secondary user. More specifically, we maximize the system utility under primary and secondary user outage constraints and the total power constraint. The secondary user transmission is also constrained by the interference threshold imposed by the primary user. Moreover, the secondary receiver adapts its decoding strategy, which is either treating interference as noise or using successive interference cancellation or superposition coding. This leads to a nonconvex optimization problem, with either perfect or statistical CSI. Consequently, we propose a sequential-based algorithm to efficiently obtain a solution to the problem. The simulation results show that the sequential algorithm is convergent and that our global proposed scheme achieves larger secondary and sum rates than other algorithms where the decoding strategy is not adapted.

Energy Efficiency in Cooperative Cognitive Radio Network in the Presence of Malicious Users

Energy efficiency (EE) in cooperative cognitive radio networks (CCRNs) enhances opportunistic data transmission through efficient utilization of power. A novel CCRN with a frame structure accommodating cooperative spectrum sensing (CSS) and cooperation in primary user's (PU) transmission or opportunistic secondary users’ (SU) transmission is considered aiming to maximize EE. A set of optimal values for spectrum sensing (SS) time, self, and cooperative transmission power gains are calculated under the constraints of SU power budget, PU detection probability, and SU and PU spectrum efficiency. The proposed system is further investigated in the presence of two separate malicious operations, namely PU emulation operation and spectrum sensing data falsification followed by their detection and weight allocation in data transmission of SU. The goal here is to analyze and evaluate the consequent gain in EE for the CCRN while maintaining the same SS reliability and target PU's transmission rate. Extensive results with a target set of parameters highlight the efficacy of the system.

Cognitive MIMO-RF/FSO Cooperative Relay Communication With Mobile Nodes and Imperfect Channel State Information

This paper analyzes the performance of an underlay cognitive radio based decode-and-forward mixed multiple-input multiple-output radio frequency/free space optical cooperative relay system with multiple mobile secondary and primary user nodes. The effect of imperfect channel state information (CSI) arising due to channel estimation error is also considered at the secondary user transmitters (SU-TXs) and relay on the power control and symbol detection processes respectively. A unique aspect of this paper is that both fixed and proportional interference power constraints are employed to limit the interference at the primary user receivers. Analytical results are derived to characterize the exact and asymptotic outage and bit error probabilities of the above system under practical conditions of node mobility and imperfect CSI, together with impairments of the optical channel, such as path loss, atmospheric turbulence, and pointing errors, for orthogonal space-time block coded transmission between each SU-TX and relay. Finally, simulation results are presented to yield various interesting insights into the system performance such as the benefits of a midamble versus preamble for channel estimation.

Harvesting-Throughput Tradeoff for CDMA-Based Underlay Cognitive Radio Networks With Wireless Energy Harvesting

This paper considers a green cognitive radio network wherein each secondary user (SU) is solely powered by an energy harvester which extracts energy from RF signals of a primary user transmitter. Each SU operates in a harvesting–transmitting fashion periodically. In each period, all SUs first harvest energy for a fixed duration and then transmit data using the harvested energy to one access point for the rest of the period in the code-division multiple access method. Considering the intrinsic harvesting-throughput tradeoff, we jointly optimize the harvesting time and transmit powers of SUs to maximize the sum throughput of the network, subject to the primary interference constraint and the energy causality constraint. Despite of the nonconvex nature of the formulated optimization problem, we find an equivalent but convex substitution to the original problem. Then, we propose a dual-decomposition-based solution method to solve the problem. Simulations finally demonstrate the efficiency of this paper.

Coverage and rate analysis in the uplink of millimeter wave cellular networks with fractional power control

In this paper, using the concept of stochastic geometry, we present an analytical framework to evaluate the signal-to-interference-and-noise-ratio (SINR) coverage in the uplink of millimeter wave cellular networks. By using a distance-dependent line-of-sight (LOS) probability function, the location of LOS and non-LOS users are modeled as two independent non-homogeneous Poisson point processes, with each having a different pathloss exponent. The analysis takes account of per-user fractional power control (FPC), which couples the transmission of users based on location-dependent channel inversion. We consider the following scenarios in our analysis: (1) pathloss-based FPC (PL-FPC) which is performed using the measured pathloss and (2) distance-based FPC (D-FPC) which is performed using the measured distance. Using the developed framework, we derive expressions for the area spectral efficiency. Results suggest that in terms of SINR coverage, D-FPC outperforms PL-FPC scheme at high SINR where the future networks are expected to operate. It achieves equal or better area spectral efficiency compared with the PL-FPC scheme. Contrary to the conventional ultra-high frequency cellular networks, in both FPC schemes, the SINR coverage decreases as the cell density becomes greater than a threshold, while the area spectral efficiency experiences a slow growth region.

Dynamic Threshold Selection Approach in Voting Rule for Detection of Primary User Emulation Attack

DOI: 10.5152/iujeee.2018.1819 Cognitive radio (CR) technology presents a mechanism for efficient spectrum usage. Spectrum sensing is an essential CR function which includes an intelligent signal processing algorithm to identify the vacant frequency bands. Cooperative spectrum sensing (CSS) has been widely adopted to improve the performance of CR networks. Unfortunately, CR networks are vulnerable to security threats. In this study, we propose an optimal threshold selection approach to address one of the most important attacks called primary user emulation attack (PUEA). In PUEA, a malicious attacker mimics some important primary signal features and deceives CR sensors to prevent them from accessing the available channels. In this study, we assume a malicious PUEA which is relatively located near the potential user (PU) transmitter and senses the spectrum and accurately detects the vacant frequency bands to transmit its fake signal. We estimate attack strength and then apply the K-out-of-N rule to obtain an optimum and dynamic threshold K, minimizing the global error probability. Here, the attack strength is defined as the ratio of the average transmission power of the PUEA to the average power of the PU. The achieved simulation results indicate that the performance of the suggested method is satisfactory in detecting the malicious PUEA compared with conventional methods.

Virtual Tai-Chi System: A smart-connected modality for rehabilitation

This work intends to develop an intelligent, four-dimensional (namely X-Y-Z plus somatosensory), partial control, and virtual-reality-enabled Tai-Chi System (VTCS). Tai-Chi is a traditional mind-body wellness and healing art, and its clinical benefits have been well documented. VTCS integrates Tai-Chi with a series of cutting-edge computer technologies including 4D sensor technology, big-data, signal processing and analysis, human body kinematics, deep learning, virtual reality, and 4D-reconstruction, etc. The aforementioned system will generate a controllable and consistent 4D experience to help, push and coach (HPC) people to get involved in sports activities. In particular, VTCS makes Tai-Chi movements suitable to individuals who suffer from mobility disabilities due to diseases or injuries as an accessible rehabilitation and fitness modality. VTCS consists of the following modules: acquisition, transmission and reconstruction of user׳s 4D data, data preprocessing, identification of user׳s kinetic movement, and individualized movement choreography. Under the support of collaborative hospitals, the physiological and psychological benefits brought about by VTCS will be critically assessed.

Outage performance of double-relay cooperative transmission network with energy harvesting

The double-relay cooperative user transmission network with energy harvesting is investigated and time switching-based double-relay cooperative transmission (TSDRCT) protocol is designed in this paper. In such a system, a source node transmits information to its destination node with the help of two energy harvesting cooperative nodes. The system outage probability is analyzed and an explicit expression for the outage probability is derived for decode-and-forward (DF) relay protocols, then simulation experiments are provided. The simulation results demonstrate the accuracy of the theoretical analysis, and also show that the proposed TSDRCT with energy harvesting relay is much better than traditional non-cooperative scheme in term of outage performance, and it does not increase system energy consumption.

Spectral and Energy-Efficient Wireless Powered IoT Networks: NOMA or TDMA?

Wireless powered communication networks (WPCNs), where multiple energy-limited devices first harvest energy in the downlink and then transmit information in the uplink, have been envisioned as a promising solution for the future Internet-of-Things (IoT). Meanwhile, non-orthogonal multiple access (NOMA) has been proposed to improve the system spectral efficiency (SE) of the fifth-generation (5G) networks by allowing concurrent transmissions of multiple users in the same spectrum. As such, NOMA has been recently considered for the uplink of WPCNs based IoT networks with a massive number of devices. However, simultaneous transmissions in NOMA may also incur more transmit energy consumption as well as circuit energy consumption in practice which is critical for energy constrained IoT devices. As a result, compared to orthogonal multiple access schemes such as time-division multiple access (TDMA), whether the SE can be improved and/or the total energy consumption can be reduced with NOMA in such a scenario still remains unknown. To answer this question, we first derive the optimal time allocations for maximizing the SE of a TDMA-based WPCN (T-WPCN) and a NOMA-based WPCN (N-WPCN), respectively. Subsequently, we analyze the total energy consumption as well as the maximum SE achieved by these two networks. Surprisingly, it is found that N-WPCN not only consumes more energy, but also is less spectral efficient than T-WPCN. Simulation results verify our theoretical findings and unveil the fundamental performance bottleneck, i.e., "worst user bottleneck problem", in multiuser NOMA systems.

Performance Analysis of Cellular Networks with D2D communication Based on Queuing Theory Model

In this paper, we develop a spatiotemporal model to analysis of cellular user in underlay D2D communication by using stochastic geometry and queuing theory. Firstly, by exploring stochastic geometry to model the user locations, we derive the probability that the SINR of cellular user in a predefined interval, which constrains the corresponding transmission rate of cellular user. Secondly, in contrast to the previous studies with full traffic models, we employ queueing theory to evaluate the performance parameters of dynamic traffic model and formulate the cellular user transmission mechanism as a M/G/1 queuing model. In the derivation, Embedded Markov chain is introduced to depict the stationary distribution of cellular user queue status. Thirdly, the expressions of performance metrics in terms of mean queue length, mean throughput, mean delay and mean dropping probability are obtained, respectively. Simulation results show the validity and rationality of the theoretical analysis under different channel conditions.

Physical layer security in cognitive radio network with energy harvesting relay and jamming in the presence of direct link

In this paper, we examine the physical (PHY) layer security in terms of secrecy outage of an energy harvesting (EH) relay based underlay cognitive radio network (CRN) in the presence of an eavesdropper. A dual hop communication network consisting of an energy harvesting relay that harvests energy from radio transmission of secondary user (SU) network using a time switching relay (TSR) scheme is studied. The relay works in decode and forward (DF) mode and forwards the confidential message to the destination, if it is successfully decoded at the relay. The advantage of the direct link between source to destination is exploited, if the relay link is in outage. Furthermore, simultaneous transmission of message signal and jamming signal to the legitimate nodes and illegitimate node respectively degrades the eavesdropping link capacity. We evaluate the secrecy outage probability (SOP) of the network under study. It is found that exploiting the direct link at the destination increases the secrecy in transmission as compared to the case of only relay based transmission without direct link. The impact of interference threshold, energy harvesting time, power allocation factor, target data rate, target secrecy rate and direct link on SOP of this proposed network is investigated.

Maximum-Largest Weighted Delay First Algorithm for Heterogeneous Traffic in 4G Networks

Real time applications with strict QoS like delay sensitive applications require an advanced technology to adopt them. This is where Long Term Evolution-Advanced (LTE-A) fulfills this requirement. With this ever evolving technology the need for improvements is required. Packet scheduling is one of the important key features of LTE-A, where it dictates user selection and transmission of those user’s packets based on the priority of the users to reach the receiver correctly. Packet scheduling is one mean to achieve those QoS requirements that real-time applications require. Such algorithms are HARQ Aware Scheduling Algorithm (HAS), Retransmission Aware Proportional Fair Algorithm (RAPF), Chase Combining Based Max C/I Scheduling and Maximum- Largest WeightedDealy First algorithm (M-LWDF). In this paper, M-LWDF is one of the best algorithms in LTE-A which was chosen for further investigated to support QoS in high mobility environment. Packet Loss Ratio (PLR), and Mean User Throughput performance measures were used to validate the performance of M-LWDF algorithm against other algorithms using similar mobile environment. Simulation results indicate the capability of M-LWDF algorithm within the threshold of the performance measures against other benchmarks where it has demonstrated more efficiency to support and improve the performance of real-time multimedia traffic.

Coverage, Capacity, and Energy Efficiency Analysis in the Uplink of mmWave Cellular Networks

In this paper, using the concept of stochastic geometry, we present an analytical framework to evaluate the signal-to-interference-and-noise-ratio (SINR) coverage in the uplink of millimeter wave cellular networks. By using a distance-dependent line-of-sight (LOS) probability function, the location of LOS and nonLOS users are modeled as two independent nonhomogeneous Poisson point processes, with each having a different pathloss exponent. The analysis takes account of per-user fractional power control (FPC), which couples the transmission of users based on location-dependent channel inversion. We consider the following scenarios in our analysis:1) pathloss-based FPC (PL-FPC) which is performed using the measured pathloss and 2) distance-based FPC (D-FPC) which is performed using the measured distance. Using the developed framework, we derive expressions for the area spectral efficiency and energy efficiency. Results suggest that in terms of SINR coverage, D-FPC outperforms PL-FPC scheme at high SINR where the future networks are expected to operate. It achieves equal or better area spectral efficiency and energy efficiency compared with the PL-FPC scheme. Contrary to the conventional ultra-high frequency cellular networks, in both FPC schemes, the SINR coverage decreases as the cell density becomes greater than a threshold, while the area spectral efficiency experiences a slow growth region.

Spectrum management in cognitive radio ad-hoc network using Q-learning

Cognitive radio ad-hoc networks (CRAHN’s) is the new buzzword wherever spectrum congestion is a matter of discussion. It was proposed to handle spectrum insufficiency, by shifting the traffic to those portions of spectrum which are not in use at that time, without affecting the transmissions of legitimate users. In this paper firstly we have discussed about CRAHN’s, secondly we have discussed about reinforcement learning and then challenges which are to be handled to implement reinforcement learning in CRAHN’s. Reinforcement learning can be implemented in many areas in cognitive radio ad hoc networks, like spectrum sensing, spectrum management, spectrum mobility, and spectrum sharing. Primarily in this paper our focus is on spectrum management. We propose a reinforcement learning technique to handle spectrum management. Our approach uses Q learning algorithm (implemented in python) to prove that if reinforcement learning is used in this area, there will be drastic improvement in performance of CRAHN’s and it enables efficient assignment of spectrum by maximizing long-term reward. We then execute our algorithm against various network scenarios. In the end we have concluded our experiment’s result, which shows that Q learning model takes some episodes to learn, after that it gives us highly optimized result, which saves secondary users to interrupt primary users with an extremely good accuracy.

Enhanced Spectrum Sharing and Cognitive Radio Using Asynchronous Primary and Secondary Users

We show that timing mismatch between the primary and the secondary users results in improving the cognitive radio networks (CRNs) performance. We perform oversampling to exploit the advantages of asynchrony in CRNs. We design detectors for asynchronous transmission to boost the signal received by the primary user in the selfless overlay CRN paradigm. Accordingly, more power is conserved for the secondary user transmission without the performance of the primary user or spectrum license holder being degraded. Simulation results present a green CRN with an almost 6-dB power gain compared with the current CRN frameworks.

Study on Energy Conservation for Cellular Systems: A Global Optimization Approach

With the increasing popularity of wireless devices and multimedia services, data transmission in cellular systems has increased dramatically, resulting in huge energy consumption. This impacts negatively on the environment (e.g., high $\text{CO}_2$ emissions and the depletion of nonrenewable energy sources) and increases the operation cost for telecommunications. Effectively solving this issue has become a significant research topic. In this study, we aim to minimize the total power consumption for cellular systems by jointly considering base station (BS) deployment and power allocation, while providing user transmission rate and quality of experience (QoE) guarantees. We construct a mathematical model which is a nonconvex mixed integer nonlinear programming (MINLP) problem. To solve it with global optimality, we design a novel branch-and-bound (B&B) algorithm based on the characteristics of the MINLP problem. We compare our proposed B&B algorithm with a reference B&B algorithm using the relaxation method published in previous literatures. Numerical results show that our algorithm substantially surpassed the reference algorithm in terms of computational complexity. Moreover, we investigate in detail the effect of distinct factor on the energy consumption of cellular systems. Our results not only provide insights into the design of green cellular systems but also serve as performance benchmarks for heuristic and distributed algorithms developed for practical implementations.

THE COMPARISON OF NON-COOPERATIVE SPECTRUM SENSING TECHNIQUES IN COGNITIVE RADIO

Cognitive radio is believed to be the future wireless communication system. Since in existing wireless communication system, static allocation of spectrum is used and that led to the problem called spectrum scarcity, the concept of cognitive radio was proposed by the Mitola in 1998. Spectrum sensing is an important and challenging issue in CR. Spectrum sensing is the detection of the primary user transmission in the allocated licensed spectrum band. In this paper different non-cooperative spectrum sensing and their comparison is shown.