Underlay Mode Research Articles

Hybrid Overlay-Underlay Cognitive Radio Networks With Energy Harvesting

Envisioning the potentials of energy harvesting technology and the improved spectrum reuse by joint utilization of overlay and underlay modes, this paper studies the throughput performance of a novel cognitive radio network (CRN) scenario with a mobile energy-harvesting secondary transmitter (ST). The hybrid overlay-underlay scheme allows the secondary users to access the spectrum even when the primary signal is detected. We are the first to partition the unit area into three parts for secondary users: overlay mode area, underlay mode area, and harvesting zone. Then, we propose a metric to classify the CRN into the spectrum-limited state and the energy-limited state, and accordingly maximize the throughput through the monotonicity analysis of throughput and collision probability. The secondary throughput is maximized under the energy constraint and collision constraint. Moreover, we quantitatively discuss the impacts of underlay mode transmission on the classification of network states and the corresponding optimal spectrum sensing, respectively. We find that with a relatively small detection threshold, ST transmits the considerable amount of packets in underlay mode, while it transmits few packets in overlay mode. Theoretical results are validated by simulations, and our findings shed light on the design and operation of mobile energy-harvesting CRNs.

CSI Based Multiple Relay Selection and Transmit Power Saving Scheme for Underlay CRNs Using FRBS and Swarm Intelligence

In this article, a multiple relay selection (MRS) scheme for signal-to-noise ratio (SNR) enhancement is proposed for underlay relay-assisted cognitive radio networks (RCRNs). A secondary source-destination pair experiencing deep fading on direct path is assisted by amplify-and-forward (AF) relays in an underlay mode. In this energy-constrained scenario, the aim is to maximize the secondary network's end-to-end SNR through an intelligent power-saving method incorporated with MRS. In contrast to the prior relay selection (RS) schemes, the relay-selection factor is the difference of SNR of the source-relay link and corresponding relay-destination link for each relay along with its corresponding interference channel coefficient. The difference factor aims to achieve the SNR upper bound while performing minimum power amplification, eventually resulting in interference mitigation as well. The proposed algorithm has been implemented using Fuzzy Rule Based System (FRBS), Artificial Bee Colony (ABC) and Particle Swarm Optimization (PSO) and their performance has been compared through simulations.

Joint Mode Selection and Resource Allocation for D2D-Enabled NOMA Cellular Networks

The 5G cellular network employs non-orthogonal multiple access (NOMA) to enhance network connectivity and capacity, and device-to-device (D2D) communications to improve spectrum efficiency. However, the underlay D2D communications may destroy the execution condition for the successive interference cancellation (SIC) decoding of NOMA cellular networks by introducing the extra interference, which degrades the cellular transmission reliability. Thus, we develop the interlay mode as a special D2D mode for NOMA system, which enables the power domain multiplexing of the D2D pair and cellular users to eliminate the strong interference between them by the SIC decoding. When D2D pair conducts the selection between the interlay mode and underlay mode, the SIC decoding constraint should be satisfied at both D2D receiver and NOMA base station. In order to maximize the system sum rate while meeting the SIC decoding constraint, we propose a joint D2D mode selection and resource allocation scheme with interlay mode, which can be formulated as a combinatorial optimization problem. To tackle the combinatorial nature of mode selection and spectrum assignment, we first prove that the original problem can be reformulated as a maximum weight clique problem, and then propose a graph-based algorithm by applying branch-and-bound method to obtain its optimal solution. Finally, simulation results are provided to demonstrate that the interlay mode along with the proposed algorithms can coordinate D2D communications and NOMA cellular network to significantly improve the system sum rate and the D2D access rate.

Performance Analysis and Power Optimization for Spectrum-Sharing Mixed RF/FSO Relay Networks With Energy Harvesting

In this paper, the energy harvesting in mixed multiple-input-single-output radio frequency (RF)/free space optical (FSO) networks is studied. Assuming underlay mode, the secondary user (SU) source with limited battery communicates with its destination via a hybrid SU relay. The SU source harvests energy from both the hybrid relay and the primary network. The hybrid SU relay node is equipped with two antennas; one for energy transmission to the secondary user and the other for data reception. The SU source transmits its data over an RF link to the relay. Then, the relay decodes the SU data before retransmitting it to the SU destination over an optical link. The RF/FSO channels are assumed to follow Nakagami-m/Malaga-M fading models with pointing errors on the FSO link. Closed-form expressions for the exact outage probability, average bit error rate, and ergodic capacity are derived. For high signal-to-noise ratio values, closed-form expressions for the asymptotic outage probability and average bit error rate are derived. Based on the asymptotic results, a power allocation model is proposed to enhance the system outage performance. Some simulation and numerical results are employed to validate the derived expressions.

Reliability-Intercept Gap Analysis of Underlay Cognitive Networks Under Artificial Noise and Primary Interference

Underlay mode of cognitive radio networks (CRNs) permits secondary users (SUs) to simultaneously operate with primary users (PUs), inducing mutual interference between them. Nevertheless, primary interference (interference from PUs to SUs) is either neglected or treated as Gaussian noise in existing works. Moreover, artificial noise, which is deliberately introduced to harm signal reception of wire-tappers, can enhance information securing capability of CRNs. This paper analyzes a gap between reliability probability (successful decoding probability of legitimate receiver) and intercept probability (successful decoding probability of wire-tappers), which accounts for artificial noise, peak transmit power constraint, interference power constraint, and fading channels, and considers primary interference as non-Gaussian noise. Towards this end, exact closed-form expressions of reliability probability and intercept probability are first derived and then validated by computer simulations. Numerous results illustrate that both probabilities are saturated at either large peak interference power or large peak transmit power, the primary interference dramatically deteriorates them while the artificial noise creates a large gap between them, demonstrating its effectiveness in securing legitimate information.

Throughput Optimization for Interference Aware Underlay CRN

Minimization of interference to primary user (PU), maximizing the throughput and connectivity of secondary users (SUs) while providing the quality of service are the major challenges for success of an underlay mode cognitive radio network (CRN). In this work we propose a model for addressing channel sharing problem for an ad-hoc underlay CRN. The objective is to maximize the throughput of the SUs while keeping the level of interference caused to the PU by the SUs under a given PU threshold. During the underlay communication, each SU receives certain signal strength based on their distances from the PU. A head node is chosen amongst the SUs using a technique based on received signal strength by the SUs. The head collects the information from all the other SUs in terms of data rate requirement, interference produced to PU and the SNR level of the SUs through a common control channel. Using the information received a dynamic programming based model is proposed to decide which SUs can be selected to access a channel for underlay mode communication. A channel is allowed to be accessed such that the throughput of the network is maximized while the overall interference to the PU receiver is kept within the specified tolerable limit. The head node dynamically assigns the channel among the selected SUs. The efficacy of the proposed model has been evaluated with numerical evaluation and simulation study. A greedy algorithm has been formulated which selects the SUs based on their data rate to interference ratio for simulation and comparative study with the proposed model. The results show that the proposed model outperforms the greedy algorithm while increasing the overall connectivity.

Joint Spectrum Resource Allocation in NOMA-based Cognitive Radio Network With SWIPT

In a conventional cognitive radio (CR) network, only when the primary user’s (PU) frequency bands are sensed to be free, secondary users (SUs) can utilize these frequency band resources. Therefore, spectrum sensing (SS) can improve spectrum utilization. Spectrum sharing means that the SUs are allowed to utilize the licensed spectrum bands belonging to the PU to transmit information with PU simultaneously. Spectrum sharing performs well under the conditions that the interference to the PU is assured to be less than a certain threshold. Non-orthogonal multiple access (NOMA) has attracted considerable interests in recent years, which is seen as an important wireless access scheme for the coming 5G wireless communication system. Simultaneous wireless information and power transfer (SWIPT) is proposed as a popular technique to extend the operation duration of power-supply-limited wireless networks. The CR-NOMA is seen as a special form of the power-domain NOMA, wherein the requirements of the SU and PU are strictly met so that excellent system performance can be achieved. In this paper, a joint frame structure is described, wherein SUs first perform SWIPT for spectrum sensing and then transmit information via an overlay and underlay mode. Moreover, the optimization problem to maximize the achievable throughput for the CR network is presented to obtain the optimal sensing slot, while the total transmission power and the minimum rate requirements of the SUs are both constrained. A joint power allocation and sensing time optimizing algorithm based on dichotomy method are proposed to achieve the optimal solution. The simulation results show that there is a maximal throughput via setting an optimal sensing time for the secondary network.

On outage secrecy minimisation in an energy harvesting relay assisted cognitive radio networks

This work considers an energy harvesting (EH) based two-hop relay assisted cognitive radio system that consists of a secondary transmitter, a relay node and a cooperative jammer operated in an underlay mode with a primary transmitter–receiver pair. An optimisation problem is formulated to minimise the secrecy outage probability under the constraints of simultaneously meeting the energy causality of the secondary transmit nodes, interference to the primary receiver and secondary outage probability. An analytical expression of the secrecy outage probability is developed followed by deriving the closed-form expressions to determine the optimal transmit power of the source, the relay node and the fraction of the time slot for EH. Simulation results show that the minimum value of the secrecy outage probability is and less over the existing works.

Resource Allocation in D2D Communication in Cellular Mode

Device-to-Device (D2D) has attracted substantial research attention recently and has been recognized as an essential approach to performance improvement in 5G networks, due to its potential to improve coverage, spectrum efficiency, and energy within the existing cellular network. In this paper, we refer to an LTE-A scenario in which the underlay mode is adopted to allow D2D pairs to communicate directly by sharing sub-channels with Cellular Users (CUEs) and cellular mode (CELLM), where two D2D users communicate through the eNB as conventional CUEs and no direct D2D link is established. In this case, the eNB is used as a relay. Our aim is to propose heuristic resource allocation schemes to distribute radio resources among CUEs and D2Ds in a cell taking the interference because of pairing into account. Finally, an analytical approach is proposed to characterize CUE and D2D capacity as well as outage probability for D2D cellular mode. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Performance Analysis, Comparison, and Optimization of Interweave and Underlay Spectrum Access in Cognitive Radio Networks

Cognitive radio networks (CRNs) have been proposed to exploit licensed bands opportunistically, with secondary users’ (SU) activity being subordinated to primary users (PU). The two most popular types of spectrum access in the CRN are interweave and underlay . There is no clear consensus which one provides better results, for different metrics, despite the fact that there has been a lot of research dedicated to each mode. In this paper, we analyze this problem theoretically, providing formulas that are in closed form. These expressions allow the performance comparison of interweave and underlay modes under a unified network setup. Our focus are two metrics, throughput and delay , which we analyze relying on the renewal-reward theory and queueing theory, respectively. These results enable an SU to decide what mode to use depending on what the optimization objective is, given the key network parameters. Furthermore, relying on the results of our analysis, we propose hybrid policies, which are dynamic, and allow the SU to switch between the two modes at any point. These policies offer an additional performance improvement of up to 50%. We validate our results with extensive realistic simulations.

On outage minimization in relay assisted cognitive radio networks with energy harvesting

This paper considers a fully energy harvested two hop relay assisted cognitive radio (CR) system operated in an underlay mode. The frame structure of the CR network consists of three non-overlapping time slots. The first time slot is meant for energy harvesting (EH) at the relay node (from both the primary interference signal and the secondary transmitter signal), while during the second slot, the secondary user transmits its data to the relay (information transmission). During the third time slot, forwarding of data by the relay and EH at secondary transmitter (from the primary interference signal) are done simultaneously. An optimization problem is formulated that minimizes the outage probability under the constraints of maintaining the energy causality and interference threshold to the primary receiver due to both the secondary transmitter and the relay node. Closed form expressions for the optimal transmit power of the source and the relay node as well as the time slot for EH are derived. The convexity of the constrained objective function is proved mathematically and the analytical solutions are verified through a large set of simulation results. Simulation results also show that a gain ∼ 11.71% and ∼ 12.7% in outage probability minimization is achieved for the proposed scheme over the existing works.

Cognitive Multi-Cell Visible Light Communication With Hybrid Underlay/Overlay Resource Allocation

In order to improve the spectral efficiency of indoor visible light communication (VLC) systems, in this letter, motivated by the concept of cognitive radio, we propose a new multi-cell cognitive VLC (C-VLC) system. The proposed multi-cell C-VLC system is comprised of both primary users and secondary users (SUs), by defining them based on users’ service requirements. We investigate the unique optical constraints of transmitters in our proposed C-VLC system, and further propose a flexible hybrid underlay/overlay resource allocation approach to maximize the sum rate of SUs for the multi-cell C-VLC system, which is very different from radio frequency communication systems. Numerical results show that the proposed C-VLC system with hybrid overlay/underlay resource allocation achieves sum rate improvements of up to 29.2%, 20.6%, and 9%, compared with the conventional non-cognitive VLC system, the C-VLC system with only the underlay mode and the C-VLC system with only the overlay mode, respectively.

An Economic Aspect of Device-to-Device Assisted Offloading in Cellular Networks

Traffic offloading via device-to-device (D2D) communications has been proposed to alleviate the traffic burden on base stations and to improve the spectral and energy efficiency of cellular networks. The success of D2D communications relies on the willingness of users to share contents. In this paper, we study an economic aspect of traffic offloading via content sharing among multiple devices and propose an incentive framework for D2D assisted offloading. In the proposed incentive framework, the operator improves its overall profit, defined as the network economic efficiency (ECE), by encouraging users to act as D2D transmitters (D2D-Txs) which broadcast their popular contents to nearby users. We analytically characterize D2D-assisted offloading in cellular networks for two operating modes: 1) underlay mode and 2) overlay mode. We model the optimization of network ECE as a two-stage Stackelberg game, considering the densities of cellular users and D2D-Txs, the operator’s incentives, and the popularity of contents. The closed-form expressions of network ECE for both underlay and overlay modes of D2D communications are obtained. Numerical results show that the achievable network ECE of the proposed incentive D2D-assisted offloading network can be significantly improved with respect to the conventional cellular networks, where the D2D communications are disabled.

Constructing a Robust Topology for Reliable Communications in Multi-Channel Cognitive Radio Ad Hoc Networks

In multi-channel CRAHNs, the spectrum efficiency can be improved via spectrum reutilization by secondary users. However, unpredictable transmission interruptions may occur when primary users reclaim their channels, resulting in the partition of the CRAHN and the failure of the end-to-end transmission. Therefore, in CRAHNs, considering the activities of primary users, how to maintain a connected network topology is fundamental in ensuring reliable secondary communications. Even though one licensed channel is reclaimed by a PU, multiple SUs may be affected. The situation gets even worse when multiple channels are reclaimed simultaneously. In this article, we elaborate on k-channel connectivity in the context of multi-channel CRAHNs. We first introduce the preliminaries of topology connectivity with the focus on the k-channel connectivity and then discuss the challenges of robust topology control by guaranteeing the k-channel connectivity in both interweave mode and underlay mode. After reviewing the recent research on topology control algorithms, we propose a distributed k-channel connectivity algorithm in underlay mode to minimize the number of required channels while satisfying the k-channel connectivity and conflict-free property. Next, we illustrate the potential benefits of k-channel connectivity through simulation results. Finally, possible directions for future research are pointed out in the conclusions.

Rate Adaptation, Scheduling, and Mode Selection in D2D Systems With Partial Channel Knowledge

Device-to-device (D2D) communication enables simultaneous data transmissions by cellular users (CU) and D2D user pairs, but at the expense of additional interference between them. The literature on resource allocation in D2D systems often assumes that the base station (BS) has complete channel state information (CSI) about all the links between all the users in a cell. However, acquiring the CSI of cross links between the CUs and the D2D receivers is a critical bottleneck because the number of cross links is the product of the number of CUs and D2D pairs. We study a novel partial CSI model in which the overhead of feeding back the CSI of the cross links is much lower. For a cell with one D2D pair and multiple CUs, we propose a novel throughput-optimal joint mode selection, user scheduling, and rate adaptation policy that exploits information about the statistics of the cross links and incorporates inter-cell interference. We derive closed-form expressions for the feedback-conditioned goodput for the underlay mode, which drives this optimal policy. We also present extensions that incorporate user fairness, quantized CSI, and multiple D2D pairs and multiple subchannels.

Recent Advances on Cellular D2D Communications

Device-to-device (D2D) communications have attracted a great deal of attention fromresearchers in recent years.[...]

Throughput of cognitive radio networks with improved energy detector under security threats

SummarySpectrum sensing in cognitive radio networks (CRNs) is subjected to some security threats such as primary user emulation (PUE) attack and spectrum sensing data falsification (SSDF) attack. In PUE attack, a malicious user (MUPUE) transmits an emulated primary signal throughout the spectrum sensing interval to secondary users (SUs) to forestall them from accessing the primary user (PU) spectrum bands. In SSDF attack, malicious users (MUSSDF) intentionally report false sensing decisions to the fusion center (FC) to influence the overall decision. While most of the existing literatures have studied the effects of these 2 types of attacks separately, the present paper evaluates the secondary network performance in terms of throughput under both the PUE and SSDF attacks with improved energy detectors (IEDs) where SU's spectrum access is hybrid, ie, either in overlay or in underlay mode. An analytical expression on throughput of SU under the simultaneous influence of both of these attacks is developed. Impact of several parameters such as IED parameter, attacker probabilities, and attacker strength on the throughput of SU is investigated. Performance of the present scheme is also compared with only PUE and only SSDF attacks. A simulation test bed is developed in MATLAB to validate our analytical results.

Efficient Resource Allocation in Device-to-Device Communication Using Cognitive Radio Technology

Device-to-device (D2D) communication is developed as a new paradigm to enhance network performance according to LTE and WiMAX advanced standards. The D2D communication may have dedicated spectrum (overlay) or shared spectrum (underlay). However, the allocated dedicated spectrum may not be effectively used in the overlay mode, while interference between the D2D users and cellular users cause impairments in the underlay mode. Can the resource allocation of a D2D system be optimized using the cognitive approach where the D2D users opportunistically access the underutilized radio spectrum? That is the focus of this paper. In this paper, the transmission rate of the D2D users is optimized while simultaneously satisfying five sets of constraints related to power, interference, and data rate, modeling D2D users as cognitive secondary users. Furthermore, a two-stage approach is considered to allocate the radio resources efficiently. A new adaptive subcarrier allocation scheme is designed first, and then, a novel power allocation scheme is developed utilizing geometric water-filling approach that provides optimal solution with low computation complexity for this nonlinear problem. Numerical results show that the proposed approach achieved significant performance enhancement than the existing schemes.

Energy Efficient Precoder Design for Non-Regenerative MIMO-CRN

This letter presents a problem of designing a relay precoding matrix for a multi-input multi-output cognitive relay network, where a secondary system (SS) works in an underlay mode and communicates through a non-regenerative relay. An optimization problem is formulated to maximize the energy efficiency of the SS subject to a transmit power constraint and an interference constraint. An efficient scheme based on the fractional programming and augmented Lagrangian multiplier method is proposed to solve the resultant problem. Numerical results are provided to show the effectiveness of the proposed scheme.

Capacity of finite secondary cognitive radio networks: Bounds and optimizations

Though there are works that show the asymptotic capacity bounds in a wireless network considering interference constraints from all transmitting nodes, there are no such evaluation of capacity bounds for finite secondary cognitive radio networks where the primaries pose additional constraints. In this paper, we find the bounds for the maximum achievable capacity of a randomly deployed secondary cognitive radio network with finite number of nodes in the presence of primary users, i.e., in the underlay mode. Since solving the functional constrained optimization problem of maximizing the secondary network’s capacity subject to other radio constraints is computationally complex, we derive analytical bounds for the solution. That is achieved by deriving a pre-engineered deployment with the best possible pairings of transmitters and receivers, from the random deployment. The capacity of the former is used to upper bound the capacity of the latter. The bounds are based on the maximum signal to interference and noise ratio (SINR) of all transmitter-receiver pairs and their geometrical placement. The derived bounds provide an insight about the network’s maximum and minimum achievable capacities since solving the optimization problem shows in-scalability both in time and search space dimensionality. To this end, we reduce the optimizer’s search space by eliminating transmitters and receivers that do not contribute positively to the system capacity. Such reduction depends on primary transmit power, primary’s interference tolerance, and mutual distances between primaries and secondaries. Further, we propose a metric that gives the relative goodness of node pairs for being potential winners for power allocation from the global power optimizer. The metric also facilitates certain trade-offs such as achieving optimal capacity using all nodes or better execution time using a partial set of nodes (expected winners). We show how the metric along with the elimination schemes can be used for pre-processing (search space dimension reduction) the input power vector before it is fed to any power optimizer. Through simulation results we show the theoretical bounds and the capacity obtained via the proposed optimizations. We also show the gains obtained due to search space reduction.