Enhance Spectrum Efficiency Research Articles

Comments on SIC Design for SISO NOMA Systems Over Doubly Selective Channels

Non-orthogonal multiple access principle applied in power domain (power-domain NOMA) enhances spectrum efficiency and connectivity of mobile communication systems through sharing between Orthogonal Multiple Access (OMA) and other multiple users. It is the almost main current trend for research and standards for 5G and beyond. Spectrum sharing generates multi-users interference (Multiple Access Interference, MAI) which destroys orthogonality in OMA systems. Meanwhile the so-called Successive Interference Cancellation (SIC) techniques are used to suppress MAI and the Cognitive Radio (CR) principle (CR-NOMA) for decoding order for multiple users inspired effective SIC algorithms. The CR-NOMA principle is applied in the present material as well, but with significant changes for SIC design as for Doubly Selective channels. Due to the above reasons, two original SIC design methods are proposed hereafter following the CR-NOMA principle. Regarding to it the OMA signal (primary user) is decoded first using a Chaos-based quasi-optimum Extended Kalman Filter (EKF). The set of “secondary users” (multiusers) are proposed to be decoded secondly by the following two different methods: Chaos-based EKF filters or, sequential <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">m</i> hypothesis testing. The proposed approach for SIC design is rather simple, fast and accurate for practical implementation.

Prior Information Aided Deep Learning Method for Grant-Free NOMA in mMTC

In massive machine-type communications (mMTC), the conflict between millions of potential access devices and limited channel freedom leads to a sharp decrease in spectrum efficiency. The nature of sporadic activity in mMTC provides a solution to enhance spectrum efficiency by employing compressive sensing (CS) to perform multiuser detection (MUD). However, CS-MUD suffers from high computation complexity and fails to meet the strict latency requirement in some critical applications. To address this problem, in this paper, we propose a novel deep learning (DL) based framework for grant-free non-orthogonal multiple access (GF-NOMA), where we utilize the information distilled from the initial data recovery phase to further enhance channel estimation, which in turn improves data recovery performance. Besides, we design an interpretable and structured Model-driven Prior Information Aided Network (M-PIAN) and provide theoretical analysis that demonstrates the proposed M-PIAN can converge faster and support more users. Experiments show that the proposed method outperforms existing CS algorithms and DL methods in both computation complexity and reconstruction accuracy.

Joint optimisation techniques for trade-off aware spectrum sensing in cognitive radio network

Cognitive radio (CR) network is considered a promising domain to enhance spectrum efficiency to access underutilised frequency bands. However, due to the influence of channel fading and shadowing, accuracy in primary user (PU) detection by CR gets hampered. This paper designs a joint optimisation technique for spectrum sensing in CR network to optimise energy, delay, and throughput with increased sensing accuracy. Initially, simple energy detection is exhibited for sensing the presence of PU in band. Further, the algorithm is developed to achieve an energy-throughput trade-off, and delay-throughput trade-off. Hence, the optimisation algorithm for detecting energy, reducing delay, and enhancing throughput are developed to optimise complete sensing performance. Furthermore, the joint optimisation model assists in acquiring trade-offs amongst energy, delay, and throughput. The assessment of the technique is performed using delay, energy, and throughput. Moreover, the software-defined radio (SDR) configuration is performed for validating the result.

Flexible Sub-bands F-OFDM Configured for Spectrum Efficiency Enhancement in 5G System

The new product of wireless communication systems, the Fifth generation (5G), promises higher data rates and Spectrum Efficiency (SE) enhancements to support the communication of heterogeneous services. The Filtered-OFDM (F-OFDM) technique was proposed as the strongest candidate waveform for the physical layer in 5G to fulfill these requirements. In F-OFDM, the whole band is split into narrow sub-bands, each filtered by a digital Finite Impulse Response (FIR) filter with different specifications to increase the spectrum utilization and allow for asynchronous transmission. This paper proposes a novel F-OFDM design waveform for the first time with four sub-bands in equal and unequal sub-band sizes of seven kinds of window sinc filters and a variety of numerology designs to observe SE enhancement using Matlab-Simulink Software. Simulation results show that F-OFDM can reduce Out-Of-Band Emission (OOBE) and achieve SE of about (5%-6%) higher than conventional OFDM for equal and unequal sized sub-bands, respectively, by optimizing the guard band between the designed sub-bands, which achieves 5G guard band requirements.

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.

Design and Analysis of MIMO F-OFDM Systems for 5G and Beyond Wireless Communications

F-OFDM (Filtered-OFDM) is a flexible waveform that has been considered suitable for 5G and beyond systems for its improved spectrum utilization, moderates PAPR, low OOB emission, multiple asynchronous sub-band transmission, and high robustness to frequency selectivity. It can attain a desirable balance between frequency and time localizations for narrow bandwidths. It is also MIMO friendly. In this paper, a comprehensive design and analysis have been made to evaluate the performance of MIMO (4×4) CP-OFDM and F-OFDM systems for message bits transmission using several digital modulation techniques (16-QAM, 16-PSK, 16-DPSK, 64-QAM, 64-PSK, and 64-DPSK), RA channel coding, different windowed (Hanning, Hamming, Blackman, Blackman-Harris, RRC) sinc FIR filters for length N = 513, and MMSE signal detection technique. From MATLAB based simulation results, it is observed that F-OFDM reduces spectrum leakage thus enhances spectrum efficiency than conventional CP-OFDM. F-OFDM based system offers lower BER (Bit Error Rate) performance than CP-OFDM based system.

NOMA-Based Integrated Satellite-Terrestrial Relay Networks Under Spectrum Sharing Environment

With the increasing requirements for efficient utilization of satellite resources, both non-orthogonal multiple access (NOMA) scheme and cognitive radio (CR) have been recognized as one of the promising solutions, particularly, for the enhancement of spectrum efficiency. This letter investigates the performance of NOMA-based integrated satellite-terrestrial relay network (ISTRN) in the presence of multiple primary users (PUs) under spectrum sharing environment. Specifically, we derive the closed-form expressions of outage probability (OP) and ergodic capacity (EC) of the considered system under the interference constraint imposed by multiple adjacent PUs. To get further insights, the asymptotic analysis for OP at high signal-to-noise ratios (SNRs) is also obtained. Numerical results are provided to verify our analysis and reveal the impacts of key parameters on system performance.

Game Theoretical Approaches for Cooperative UAV NOMA Networks

Wireless communication systems assisted by unmanned aerial vehicles (UAVs) can well extend the coverage of conventional communication networks and quickly provide service wherein the communication infrastructures are destroyed. However, radio resources are always limited and coupled with complex interference in the orthogonal multiple access framework. Thus, non-orthogonal multiple access (NOMA), which can enhance spectrum efficiency and inherently has capability to mitigate interference, is integrated with UAV communication networks in this article. We first propose a cooperative UAV NOMA network (CUNN) architecture and analyze its technical challenges. In addition, with the goal of cooperatively or competitively utilizing the limited resources effectively in a distributed manner, game theory shows its potential in addressing various technical challenges in wireless networks. Thus, we further survey game theoretical approaches for NOMA networks and UAV-based relay networks, and provide insights on how these game theoretical approaches can be adopted to solve technical challenges in CUNNs. Finally, aiming to achieve high spectrum efficiency and ensure fairness among user equipments, we propose a UAV-iUE (isolated user equipment) association, UAVs' position optimization, and power allocation algorithm in a dynamic cooperative game-theoretic framework. In the numerical results and discussions Section, the effectiveness of the proposed dynamic cooperative game-theoretic framework is shown through multiple simulations.

QoS-Guaranteed Resource Allocation for Full-Duplex Networks With M2M/H2H Co-Existence Under Imperfect CSI

To enhance spectrum efficiency for the future Internet-of-Things, in this paper, we investigate the joint subcarrier and power allocation problem for a full-duplex network with machine-to-machine nodes and cellular nodes. We aim to maximize the network spectral efficiency while achieving individual quality-of-service (QoS) requirements, considering imperfect and partial channel state information. The spectral efficiency maximization problem is formulated as a mixed-integer nonlinear programming problem and proved to be NP-hard. To make it more tractable, we first solve the coupling between subcarrier assignment and power allocation variables by replacing the product of two variables with one auxiliary variable. We then relax the binary subcarrier assignment variables to integer variables and introduce penalty terms to penalize the objective function. Majorization minimization method is adopted to further handle the coupling between uplink and downlink due to full-duplex transmission. We prove that the proposed joint resource allocation scheme converges to local optimal solution. Simulation results demonstrate the impact of channel estimation error on spectral efficiency and the superiority of the proposed algorithm.

Image-Driven Spatial Interpolation With Deep Learning for Radio Map Construction

Radio maps are a promising technology that can boost the capability of wireless networks by enhancing spectrum efficiency. Since spatial interpolation is a critical challenge to construct a precise radio map, the latest works have proposed deep learning (DL)-based interpolation methods. However, a DL model that achieves enough estimation accuracy for practical uses has not yet been established due to the complexity of radio propagation characteristics. Therefore, we propose a novel DL framework that transforms the spatial interpolation problem into a shadowing adjustment problem suitable for DL-based approaches. We evaluate the performance using real measurement data in urban and suburban areas to show that the proposed framework outperforms the state-of-the-art deep learning models.

I-Talk: Reliable and Practical Superimposed Signal Decoding Without Power Control

Internet-of-Things (IoT) is emerging, while the spectrum is at a premium. To enhance spectrum efficiency, a promising solution is Non-Orthogonal Multiple Access (NOMA) that enables users to communicate with the same resource at the same time, while decoding the superimposed signal at the receiver. Existing NOMA technologies, however, rely on strict power control to decode the superimposed signal, infeasible for heterogeneous and low-cost IoT devices. In contrast, we propose I-Talk, a new NOMA scheme that is designed for IoT and can decode the superimposed signals from two transmitters without power control. Importantly, considering the IoT systems in the wild, both the hardware imperfections and mobility are unavoidable, which can cause severe signal variations, resulting in an unreliable decoding performance. To solve this problem, we design a synthesis channel coefficient to track all signal offsets caused by the hardware imperfection. Meanwhile, we propose a diversity transmission and smart combining scheme to achieve high reliable decoding performance. To demonstrate the feasibility of this new NOMA approach in practical systems, we implement I-Talk with USRP devices and the experimental results illustrate that I-Talk achieves a one-order lower bit-error-rate and a 1.47× higher throughput gain than the state-of-the-art superimposed signal decoding scheme.

Secrecy Analysis for Full-Duplex Jamming-Aided Uplink NOMA System

Full duplex (FD) is one of the most attractive technologies in enhancing spectrum efficiency for potentially doubling the system throughput. In this work, we employ FD jamming to improve the secrecy performance of an uplink non-orthogonal multiple access (NOMA) system at the presence of one eavesdropper. We first characterize the individual secrecy performance in terms of effective secrecy throughput (EST), and derive its closed-form expression via secrecy outage probability (SOP). We then further investigate the problem of optimal power allocation to maximize overall secrecy performance. The solution to the optimization problem is figured out and demonstrated numerically with an appropriate case.

Enhancing Spectrum Efficiency for Multiple Users in Hybrid Satellite-Terrestrial Networks

In the paper, we present a study on the performance analysis of a non-orthogonal multiple access (NOMA) underlay cognitive hybrid satellite-terrestrial relaying network (CSTRN) and highlight the performance gaps between multiple users. The satellite source communicates with users by enabling cognitive radio scheme to forward signals to secondary destinations on the ground which belong to dedicated groups following the principle of NOMA. In this scenario, the secondary source acts a relay and employs Amplify and Forward (AF) mode to serve distant NOMA users under a given interference constraint. To characterize the transmission environment, the shadowed-Rician fading and Nakagami- $m$ fading models are widely adopted to the relevant hybrid channels. To provide detailed examination of the system performance metrics, we aim to derive closed-form formulas for the outage probability of the secondary destinations in the presence of the primary interference power constraint imposed by the adjacent primary satellite network. Finally, our simulation results showed that a greater number of antennas, better quality of wireless channels and power allocation factors exhibit the main effects on system performance.

Joint Beamforming and Artificial Noise Optimization for Secure Transmissions in MISO-NOMA Cognitive Radio System with SWIPT

The integration of non-orthogonal multiple access (NOMA) in cognitive radio (CR) networks has demonstrated how to enhance spectrum efficiency and achieve massive connectivity for future mobile networks. However, security is still a challenging issue due to the wireless transmission environment and the broadcast nature of NOMA. Thus, in this paper, we investigate a beamforming design with artificial noise (AN) to improve the security of a multi-user downlink, multiple-input single-output (MISO) NOMA-CR network with simultaneous wireless information and power transfer (SWIPT). To further support power-limited, battery-driven devices, energy-harvesting (EH) users are involved in the proposed network. Specifically, we investigate the optimal AN, power-splitting ratios, and transmission beamforming vectors for secondary users and EH users in order to minimize the transmission power of the secondary network, subject to the following constraints: a minimum signal-to-interference-plus-noise ratio at the secondary users, minimum harvested energy by secondary users and EH users, maximum power at the secondary transmitter, and maximum permissible interference with licensed users. The proposed solution for the challenging non-convex optimization problem is based on the semidefinite relaxation method. Numerical results show that the proposed scheme outperforms the conventional scheme without AN, the zero-forcing-based scheme and the space-division multiple-access-based method.

Midpoint Relay Selection Using Social Trust and Battery Level to Enhance Throughput in Cooperative Device-to-Device Communications.

Device-to-device communications in underlay mode has emerged as a promising way to enhance spectrum efficiency in cellular networks. Recently, relay selection in D2D communications underlaying cellular networks is gaining more research interest. In this paper, we propose two relay selection schemes for D2D communications underlaying cellular networks, Midpoint Relay Selection using Social Trust and Battery Level (MRS-ST-BL) and Midpoint Relay Selection using Social Distance and Battery Level (MRS-SD-BL). These proposed schemes utilize battery power level information of devices together with social trust information of users in the network for relay selection. For performance evaluation, initially we show that the throughput of state-of-the-art schemes Hybrid Relay Selection (HRS) and our previously proposed schemes Midpoint Relay Selection using Social Trust (MRS-ST) and Midpoint Relay Selection Using Social Distance (MRS-SD) decrease, when relays have varying battery power. Then, we compare the performance of our proposed schemes against existing schemes including HRS, MRS-ST and MRS-SD. The performance comparison is done at various social trust scenarios and device densities. We show that our proposed schemes can significantly improve the throughput of D2D communications, particularly when relays have different battery power levels in weak social trust scenarios. Finally, we show that the performance of our proposed scheme MRS-ST-BL varies with the change in battery power threshold.

User Access and Resource Allocation in Full-Duplex User-Centric Ultra-Dense Networks

User-centric ultra-dense network (UUDN) has become a promising paradigm with the advantages over traditional cell-centric structure with respect to spectrum and power usage. This paper introduces full duplex (FD) technology into UUDN and presents a joint scheme of user access, subchannel allocation and power control for FD UUDN. The scheme firstly judges the feasibility of the constraints of the transmit power and rate requirements. If they are feasible, the total network capacity is maximized under the transmit power constraints. Otherwise, the minimal total power of the network is found to satisfy the rate requirements. The sum rate maximization is solved by multiplicative linear fractional programming (MLFP) based power allocation (MAPEL) algorithm and particle swarm optimization (PSO) algorithm, respectively. The power minimization problem is transformed by averaging the total rate in each subchannel of the user, and then solved by time-sharing method. Simulation demonstrates the enhancement of spectrum efficiency and the reduction of consumed power for UUDN compared with cell-centric UDN. Moreover, the advantage of FD over half duplex (HD) is shown in terms of spectrum efficiency and power consumption.

A Unified Spectrum Formulation for OFDM, FBMC, and F-OFDM

Although orthogonal frequency division multiplexing (OFDM) has been standardized for 5G, filter bank multi-carrier (FBMC) and filtered orthogonal frequency division multiplexing (F-OFDM) remain competitive as candidates for future generations of wireless technologies beyond 5G, due to their reduced spectrum leakage and thus enhanced spectrum efficiency. In this article, we developed a unified spectrum expression for OFDM, FBMC, and F-OFDM, which provides comparative insights into those techniques. A representative sideband quantification is included at the end of this article.

72‐4: Spectrum Narrowing and Efficiency Enhancement of Quantum Dot Light‐Emitting Diodes by Microcavity

We have studied the spectrum narrowing of a microcavity quantum dot light‐emitting diodes (MQLEDs), and observed enhancement in external quantum efficiency and luminance. Our results show that the full width at half maximum (FWHM) of electroluminescent is reduced by one‐third using a distributed bragg reflector (DBR) and metal mirror to form a Fabry‐Perot cavity. The narrowed spectrum also contributes to an ultrawide color gamut. In addition, the resonant cavity improves the light coupling efficiency of the devices, which exhibits a twenty percent enhancement of the external quantum efficiency.

Spectrum efficiency in CRNs using hybrid dynamic channel reservation and enhanced dynamic spectrum access

Blocking of new arriving services and dropping of ongoing services are inherent problems in Cognitive Radio Networks (CRNs), which need to be addressed to enhance spectrum efficiency. In particular, Secondary Users (SUs) undergo service degradation in the face of Primary Users (PUs)’ arrivals. In this paper, we present a scheme called Efficient Spectrum Utilization (ESU) that reduces the dropping and blocking probabilities of existing and new services, respectively, to make efficient use of the available spectrum. The scheme divides the available spectrum into reserved and non-reserved bands. The reserved band is dynamically allocated a number of channels from the non-reserved band in order to accommodate those services which face interruptions while operating in the non-reserved band. The scheme renders dynamic access to the available spectrum and facilitates priority-based channel allocation and termination. SUs are divided into low and high priority levels depending on their Quality of Service (QoS) requirements. SUs with low priority level are granted direct access to both the bands to enhance channel utilization. SUs operating in the reserved band with high priority levels are granted uninterruptible status to ensure a certain level of service provisioning to SUs. The proposed ESU scheme is modeled using Continuous Time Markov Chain (CTMC) and mathematical expressions are derived for several QoS parameters. Performance of the proposed scheme is evaluated under various network conditions. Results demonstrate that ESU reasonably improves spectrum efficiency under channel failure in CRNs.

Modeling and Performance Analysis of Cognitive Radio Networks Using Stochastic Timed Colored Petri Nets

Cognitive radio (CR) is currently one of the most promising information transmission technologies to deal with the problem of spectrum scarcity and spectrum underutilization in wireless communications. CR networks aim to enhance spectrum efficiency to meet the ever-increasing demands of end users. The principle is to provide the opportunity for unlicensed users (secondary users, SUs) to temporarily and dynamically access the unused or sparsely used bandwidth while ensuring that it never interferes or degrades the performance of the incumbent license holders, commonly called primary users (PUs). This raises several challenges to be addressed in CR networks and performance of secondary users is one of the critical issues tackled in this paper. That is, we propose to devise CR networks as a retrial queueing system where PUs have preemptive priority over SUs. To calculate performance measures of the devised model under quite general assumptions about the model parameters, analytical methods are known to require hard calculations and the obtained results are generally not exploitable. For this reason, simulation modeling becomes the last resort to assess the dependability indicators. To this extend, we build the simulation model of the queueing system using Timed Stochastic Colored Petri Nets. Various useful results will be hence drawn while varying network conditions. Both exponential and Erlang distributions are considered for modeling service time of SUs. The obtained results with restrictive assumptions fit the analytical outcomes experienced for quite similar queuing models, which demonstrate the effectiveness of the proposed STCPN simulation model.