Improve Spectrum Efficiency Research Articles

Resource management scheme for full-duplex device-to-device vehicular communication using hypergraph clustering and interference limited area theory

In cellular vehicle-to-everything systems, the rapid movement of vehicles leads to the network topology instability of device-to-device (D2D) links. The frequent reconfiguration of network topology increases the complexity of the same frequency interference problem and the amount of signaling overhead for the management of network topology, which result in the waste of the computation ability and bandwidth resources of the base station (BS). In this paper, we establish a full-duplex device-to-device (FD-D2D) vehicular communication model with cluster as the core and propose a resource management scheme for FD-D2D vehicular communication by using hypergraph clustering and interference limited area theory. In the proposed scheme, the degree of link dependence and the computation ability of vehicle users are utilized to improve the cluster survival time and reduce the BS overhead. Meanwhile, dynamic power control and sharing area mapping are used to assist the BS in allocating resources, reduce the co-frequency interference between vehicular device-to-device (V-D2D) links and between V-D2D links and cellular links that reuse the same frequency, and improve spectrum efficiency. Real-time traffic flow data are generated by the traffic simulation modeling software VISSIM to verify the proposed resource management scheme. Simulation results show that the network topology management workload of the BS is reduced by at least 50%. Relative to that in traditional cellular D2D vehicle communication, the average frequency of spectrum sharing in FD-D2D communication increases by more than 0.5 times, and the spectrum efficiency increases by 10%.

A Survey and Quantitative Evaluation of Integrated Circuit-Based Antenna Interfaces and Self-Interference Cancellers for Full-Duplex

Full-duplex (FD) wireless - simultaneous transmission and reception on the same frequency - is a promising technique that can significantly improve spectrum efficiency and reduce communication latency in future wireless networks. To enable FD operation, the powerful self-interference (SI) signal leaking from the transmitter (TX) into the receiver (RX) needs to be suppressed and canceled to an extreme degree at the antenna interface as well as in the RF/analog and digital domains. Various approaches to achieve TX-RX isolation at the antenna interface and SI cancellation (SIC) in the RF/analog and digital domains have been demonstrated, with a focus on using bench-top off-the-shelf components. Recent advances in integrated circuit (IC) implementations of various types of shared antenna interfaces and cancellers in the RF and/or analog baseband (BB) domains have further pushed the frontier of realizing FD wireless in small-form-factor/hand-held devices. Moreover, it is still important to fundamentally study the SIC performance that can be achieved by different types of cancellers. In this paper, we present a first-of-its-kind comprehensive overview on the implementation and comparison of various state-of-the-art integrated shared antenna interfaces and SI cancellers in both the RF and analog BB domains. We define two figures of merit (FOM) for the IC-based shared antenna interfaces and SI cancellers, which capture various design considerations and performance tradeoffs including the achievable isolation/SIC, bandwidth, noise figure degradation, TX/SI power handling, and power consumption. In particular, we focus on two types of integrated shared antenna interfaces including electrical-balance duplexers and circulators. We also discuss two types of SI cancellers based on the time-domain and frequency-domain approaches, which respectively employ parallel delay lines and bandpass filters to emulate the SI channel. Based on realistic measurements, we perform extensive numerical evaluations to illustrate and compare the achievable RF SIC performance in different scenarios, as well as discuss various design tradeoffs. Finally, we provide an overview of the IC-based implementations and performance evaluations of both types of cancellers based on our recent work.

Classification of Spectrum Scheduling Using Conditional Probability and Decision Tree Supervised Learning Approach

Spectrum Scheduling is an efficient scheme of improving spectrum utilization for faster communications, higher definition media (HDM) and data transmission. Radio spectrum is very limited in supply resulting in enormous problems related to scarcity. It owes the physical support for wireless communication, both fixed applications and mobile broadband. Basically, effective use of the spectrum depends on the channel settings, sensing performance, detection of spectrum prospect as well as effective transmission of both Primary Users (PUs) and Secondary Users (SUs) packets at a specific time slot. In order to improve spectrum utilization this paper adopted quantitative method which employs Probability Theorem to identify the probabilities of both primary Users (PUs) and secondary users (SUs) in the spectrum datasets allocation and further used conditional probability to compare two Frequency Bands i.e., High Frequency (HF) and Very High Frequency (VHF). The result indicates available spectrum holes (SH) left unutilized in the Secondary User (SU) resulting in the need for spectrum scheduling for the SU. The procedure makes the secondary users occupy a probability of 0.002mhz compared to the primary users on 0.00004mhz utilization. This further indicates that some spectrum holes were left unutilized by the license users (Primary Users). However, spectrum allocation is one of the major issues of improving spectrum efficiency and has become a considerable tool in cognitive wireless networks (CWN). Consequently, the goal of spectrum allocation is to assign leisure spectrum resources efficiently to achieve the optimal Quality of Service (QOS and cognitive user requirements of wireless network. Again, classification of spectrum allocation was carried out through difference methods. Firstly, we employ a probability theorem to identify the probability of both Primary Users (PUs) and Secondary Users (SUs) in the allocated spectrum data sets. Secondly, conditional probability was used to compare two frequency band based on primary and secondary allocation policies designed to identify the specific allocation of each band. Thirdly, Machine Learning (ML) Algorithm based on Decision Tree - Supervised Learning (DTSL) approach was adopted to classified our data sets. The result yielded 68% which correctly classified instances based on the total records of sixty-nine (69) data sets. Research findings demonstrate a highly optimized spectrum scheduling for efficient networks service provisions.

Uplink SCMA Codebook Reuse Transmission and Reception Scheme

Sparse code multiple access (SCMA) is a new non-orthogonal multiple access scheme suitable for 5G communication, which can effectively improve spectrum efficiency and support massive connections. Multiple users in the SCMA system realize the sharing of the same time-frequency resources by mapping data into codewords of a special code book (Code Book, CB). A typical SCMA system increases the spectrum utilization to 150%. In order to further improve the system spectrum utilization and increase the number of user connections, this paper proposes an uplink SCMA codebook reuse transmission and reception scheme (CB-Reuse-SCMA), which reuse a codebook to multiple users. The base station allocates <i>β</i> users to each codebook at the same time, so that <i>β</i> users use the same codebook to transmit uplink information. On the receiver of the base station, an improved Logarithmic Message Passing Algorithm (Log-MPA) is designed for multi-user detection, so that the base station can correctly detect the data of <i>β</i> users who reuse the same codebook. Simulation results show that at the time <i>β</i> = 2, the proposed scheme increased the spectrum utilization to 300%; at the time <i>β</i> = 3, the proposed scheme increased the spectrum utilization to 450%. Compared with the traditional SCMA scheme where the user has an exclusive codebook, the proposed scheme improves the spectrum utilization to <i>β</i> × 150% through codebook reuse at the expense of a small amount of SNR gain, which improves the throughput and user connection by <i>β</i> times number.

Decentralized Blockchain-Based Dynamic Spectrum Acquisition for Wireless Downlink Communications

Wireless network virtualization is a promising solution to improve spectrum efficiency. For a wireless downlink communication system with multiple mobile virtual network operators (MVNOs), we propose a decentralized blockchain-based dynamic spectrum acquisition scheme. Our proposed scheme aims to minimize the sum transmit power at all MVNOs while satisfying the average data transmission rate thresholds. For each MVNO, the required wireless spectrum to provide customized services to the mobile users (MUs) is predicted using the half-range Gauss-Hermite quadrature. Based on the predicted values, all the MVNOs carry out a blockchain-based distributed alternative direction method of multipliers to obtain the global optimal solution to the aforementioned sum transmit power minimization problem. To examine the effectiveness of our proposed scheme, with known system parameters, we also theoretically derive the semi-closed-form solution to the actually required sum transmit power minimization problem subject to data transmission rate constraints. Simulation results illustrate that our proposed dynamic spectrum acquisition scheme achieves almost the same minimum sum power as the non-causal scheme, which assumes the number of active MUs in all cells and all the channels are known non-causally for the optimal dynamic spectrum allocation.

A Time-Varying Chaotic Multitone Communication Method Based on OFDM for Low Detection Probability of Eavesdroppers

Due to the rapid development of modern communication technology and the substantial improvement of the processing capacity of communication equipment, it has become a challenging and meaningful research direction to realize the covert transmission of information by ensuring the low probability of detection (LPD) performance of the communication signals. The disadvantage of traditional fixed-parameter signal in LPD gradually appears. The paper proposes a time-varying chaotic multitone communication method to accomplish the LPD for the eavesdroppers. The method gets rid of the conventional LPD communication method whose performance improvement is exchanged at the expense of its reliability loss or sacrificing more resources. Based on the original chaotic multitone (CMT) communication method, the time-varying parameter is introduced to improve the randomness of the waveform and thus reduce the detection probability of eavesdroppers to the single tones in the multitone group (MTG). Meanwhile, to improve spectrum efficiency and reduce system complexity, the corresponding communication system model is designed based on orthogonal frequency division multiplexing (OFDM) technology. After given the corresponding detection and demodulation scheme based on the diversity and combination, the influence of time-varying parameters on the reliability for the cooperative receiver is analyzed. The LPD contribution of this method is evaluated by analyzing the detection probability of the eavesdropper. The experimental results show that the proposed method not only maintains the original reliability but also reduces the detection probability of eavesdroppers under the constant false alarm probability detection scheme.

Towards Enhancing Spectrum Sensing: Signal Classification Using Autoencoders

The demand for technologies relying on the radio spectrum, such as mobile communications and IoT, has been growing exponentially. As a consequence, providing access to the radio spectrum is becoming increasingly more important. The ever-growing wireless traffic and the increasing scarcity of available spectrum warrants efficient management of the radio spectrum. At the same time, machine learning (ML) is becoming ubiquitous and has found applications in many fields for its ability to identify patterns and assist with decision-making processes. Recently, machine learning algorithms have been used to address challenges in the wireless communications domain, such as radio spectrum sensing, and have shown better performance than traditional sensing methods, such as energy detection. Spectrum sensing, a method for detecting and identifying different wireless signals being transmitted in the same band of the radio spectrum, is crucial for improving dynamic spectrum sharing, which has the potential to enhance sharing and coexistence of different wireless technologies in the same frequency band and ultimately improve spectrum efficiency. To this end, this research evaluates different types of autoencoders, such as deep, variational and Long Short-Term Memory (LSTM) autoencoders, to identify and differentiate between LTE and Wi-Fi transmissions. The goal is to investigate the performance of the different types of autoencoders on an I/Q dataset consisting of LTE and a combination of Wi-Fi signals (IEEE 802.11ax and IEEE 802.11ac) for the classification task in terms of complexity, precision, and recall to identify the best algorithm. Our models have achieved up to 99.9% precision and 88.1% recall for this classification task. Additionally, with a shortest training time of approximately 47 seconds, the models are suitable for online learning and deployment in a dynamic RF environment.

Channel Status Prediction using Auto-regressive and Auto-regressive Integrated Predictors over WLAN Channel

Recently, due to the increase of huge number of wireless devices such as smartphones or sensors, mobile wireless traffic is dramatically expanding each year. Cognitive radio (CR) system has been attracted attention to improve frequency usage efficiency. CR system is a technology that enables to select multiple radio systems, grasps the congestion status of communication and selects the optimum radio system. Till now, there are many researches considering the prediction of channel occupancy ratio (COR: the ration between busy duration length to resolution period T). If the start and end points of busy/idle duration from the sensing channel spectrum can be correctly predicted, it will largely benefit the wireless system design and spectrum efficiency (SE) improvement. In this paper, we will consider such research based on auto-regressive (AR) and auto-regressive integrated (ARI) models using traffic data captured from the wireless channel near a railway station. The major idea is that the busy/idle duration length can be calculated from COR value when the resolution period T is short. The results confirm that our proposal can improve the prediction accuracy.

Shaped offset 8PSK and coded shaped offset 8PSK with improved spectrum efficiency for satellite communication

Shaped offset 8PSK and coded shaped offset 8PSK with improved spectrum efficiency for satellite communication

An Integrated Fuzzy-based Admission Control System (IFACS) for 5G Wireless Networks: Its implementation and performance evaluation

The Fifth Generation (5G) network is expected to be flexible to satisfy user requirements and the Software-Defined Network (SDN) with Network Slicing is a good approach for admission control. There are different challenges of 5G networks such as: improved spectrum efficiency, reduced latency, low consumption, high data rate, capacity and throughput improvement. To deal with these challenges, we propose an Integrated Fuzzy-based Admission Control System (IFACS) for 5G Wireless Networks. We consider 4 input parameters: Quality of Service (QoS), Slice Priority (SP), User Request Delay Time (URDT) and Slice Overloading Cost (SOC). From simulation results, we conclude that the considered parameters have different effects on the acceptance decision. When QoS, SP, URDT parameters are increased, the AD value is increased. But, when the SOC parameter is increased, the AD value is decreased. When the QoS increases 20%, the AD is increased 20% when SP value is 0.5, SOC value is 0.3 and the URDT value is 0.5. But, when the SOC value changes 40%, the AD is decreased by 20% when the URDT value is 0.5.

Energy-efficient relay selection and power allocation for multi-source multicast network-coded D2D communications

Device-to-device (D2D) communication improves spectrum efficiency (SE) and increases system capacity. Heterogeneous networks comprise macrocell and several small cells, such as picocells and femtocells, where femtocells are more efficient. In cooperative communications, one or several additional nodes help to send data from source to destination to improve the quality of service (QoS). Network coding (NC) in cooperative networks can extend data rate and coverage area of D2D communication. The purpose of this article is to minimize power consumption of transmitting nodes during network-coded cooperative D2D transmission to reduce the interference on co-channel transmissions. In this study, we consider cooperative multicast D2D communication with NC, where femtocell base stations (FBSs) are used as relay. We propose a method based on energy efficiency (EE) maximization for relay selection and power allocation for multi-source network-coded cooperative D2D communication in heterogeneous cellular networks. We present a solution to the proposed method and evaluate its performance. The results show that the introduced method significantly improves the SE and EE compared to the coordinated multi-point (CoMP) transmission, multi-source direct D2D communication (D-D2D), and other works.

Capacity Analysis of an AF Relay Cooperative NOMA System Using MRC

Non-orthogonal multiple access (NOMA) is widely studied in both academia and industry due to its high spectral efficiency over orthogonal multiple access (OMA). To effectively improve spectrum efficiency, an amplify-and-forward (AF) cooperative NOMA system is proposed as well as a novel detection scheme is proposed, in which we first perform successive interference cancellation (SIC) twice at U1 for the two signals received from two time slots to remove interference from symbol 2, then two new signals apply max ratio combining (MRC). In addition, a closed-form upper bound approximation for the ergodic capacity of our proposed system is derived. Monte-Carlo simulations and numerical analysis illustrate that our proposed system has better ergodic capacity performance than the conventional cooperative NOMA system with decode-forward (DF) relay, the conventional cooperative NOMA system with AF relay and the proposed AF cooperative NOMA system in [16]. In addition, we can see that ergodic capacity of all NOMA cooperative systems increase with the increase of transmit SNR. Finally, simulations display that power allocation coefficients have little effect on ergodic capacity of all NOMA cooperative systems. This is due to this fact that ergodic capacity of two symbols can be complementary with changing of power allocation coefficients.

Spectrum Activity Surveillance: Modeling and Analysis From Perspectives of Surveillance Coverage and Culprit Detection

Spectrum activity surveillance (SAS) is essential to dynamic spectrum access (DSA)-enabled systems with a two-fold impact: it is a primitive mechanism to collect usage data for spectrum efficiency improvement; it is also a prime widget to collect misuse forensics of unauthorized or malicious users. While realizing SAS for DSA-enabled systems appears to be intuitive and trivial, it is, however, a challenging yet open problem. On one hand, a large-scale SAS function is costly to implement in practice; on the other hand, it is not clear how to characterize the efficacy and performance of monitor deployment strategies. To address such challenges, we introduce a three-factor space, composed of spectrum, time, and geographic region, over which the SAS problem is formulated by a two-step solution: 3D-tessellation for sweep (monitoring) coverage and graph walk for detecting spectrum culprits, that is, devices responsible for unauthorized spectrum occupancy. In particular, our system model transforms SAS from a globally collective activity to localized (even distributed) actions, and strategy objectives from qualitative attributes to quantitative measures. With this model, we design low-cost deterministic strategies for dedicated monitors, which outperform strategies found by genetic algorithms, and performance-guaranteed random strategies for crowd-source monitors, which can detect adversarial spectrum culprits in bounded time.

Secure Resource Allocation for Polarization-Based Non-Linear Energy Harvesting Over 5G Cooperative CRNs

We address secure resource allocation for energy harvesting (EH) based 5G cooperative cognitive radio networks (CRNs). To improve spectrum efficiency and the physical layer security, the size-limited secondary users (SUs) are equipped with orthogonally dual-polarized antennas (ODPAs). In particular, we propose, develop, and analyze an efficient resource allocation scheme under a realistic and non-linear EH model, which can capture the non-linear characteristics of the end-to-end wireless power transfer (WPT) for radio frequency based EH circuits. Our obtained numerical results validate that a substantial performance gain can be obtained by employing the non-linear EH model and equipping SUs with ODPAs.

On the Multiplexing of Data and Metadata for Ultra-Reliable Low-Latency Communications in 5G

This paper addresses the problem of downlink radio resource management for ultra-reliable low-latency communications (URLLC) in fifth generation (5G) systems. To support low-latency communications, we study performance of two multiplexing schemes namely in-resource control signalling and joint encoding of data and metadata . In the former, the metadata and data are separately encoded and the metadata is sent at the beginning of transmission time prior to the data. Thus, it benefits from a low-complexity receiver structure to decode the data block. The latter takes advantages of transmitting a larger blocklength to enhance the reliability and improve spectrum efficiency by jointly encoding data and metadata as a single codeword. Dealing with small URLLC payloads, the overhead and error of sending metadata are not negligible and have a significant impact on the system performance in terms of resource usage the reliability of transmission. For each scheme, we derive expressions for the outage probability and resource usage by taking into account impacts of the finite blocklength payloads, overhead and error of sending metadata, and probability of error in uplink feedback channel. We propose a novel framework for joint data and metadata link adaptation to minimize the average number of allocated resources, while ensuring the stringent URLLC quality of service requirements. An optimization problem is formulated for each scheme that is mixed-integer non-convex problem, difficult to solve in polynomial time. Solutions based on successive convex optimization are proposed. Numerical evaluations show that the proposed algorithms perform close to the optimal solution and demonstrate remarkable gains of up to $\mathbf {27\%}$ improvement in resource usage. Finally, we present sensitivity analysis of the results for various network parameters.

Green Communications for Future Vehicular Networks: Data Compression Approaches, Opportunities, and Challenges

Cellular vehicular networks constitute an important part of future vehicular communication systems. However, they pose challenges to fulfill vehicles with demands for the transmission rates of various network services while achieving satisfactory costs and energy consumption. The cloud radio access network architecture is considered as a green wireless access network framework that reduces the deployment costs of base stations while achieving resource sharing and dynamic scheduling to lower energy consumption, and thus will greatly improve spectrum efficiency. in this article, we first propose a cloud vehicular radio access network (C-VRAN) architecture to enable rapid network innovation for green vehicular communications. Specifically, we propose a vehicular network framework consisting of centralized processing, collaborative radio, real-time cloud computing, and data compression functions. Then, the design and the potential benefits of C-VRAN are presented in detail. Moreover, an effective data compression approach for the proposed architecture is proposed to meet low-distortion compression for cellular vehicular network data, thereby improving fiber resource utilization. Finally, we briefly discuss key challenges and solutions for future green vehicular communications.

Resource Allocation in Buffer-Aided Cooperative Non-Orthogonal Multiple Access Systems

Cooperative non-orthogonal multiple access (C-NOMA) and buffering are promising techniques to improve spectrum efficiency in the next generation of wireless networks. In this article, a buffer-aided cooperative NOMA network with direct links is studied. The throughput maximization problem is firstly formulated under the assumption of fixed power allocation and optimally solved by designing a mode selection policy. In order to further improve system throughput, the problem is extended into the case that power allocation and mode selection are jointly optimized. An optimal solution is obtained, while a sub-optimal one is also provided in order to decrease the implementation complexity. Furthermore, considering the case where the buffer has finite size and the users are delay-sensitive, a throughput-delay aware strategy is also presented. Moreover, it is shown that the proposed schemes outperform the baseline one in terms of throughput. Finally, simulations demonstrate that the sub-optimal solution achieves similar performance to the optimal one, while significantly reduces the implementation complexity.

Receive Spatial Modulation Aided Simultaneous Wireless Information and Power Transfer With Finite Alphabet

As the number of communication devices rapidly grows, limited radio resources hardly accommodate the every-increasing tele-traffic. As a remedy, spatial modulation (SM) is capable of modulating additional information onto the index of transmit or receive antennas, which results in substantial improvement of spectrum efficiency. Moreover, radio frequency (RF) signal based simultaneous wireless information and power transfer (SWIPT) has attracted tremendous research interest, in order to relieve the energy-thirst of massively deployed low-power communication devices. In this paper, a receive spatial modulation (RSM) aided SWIPT system with finite alphabets is studied, in which three different transmission schemes are proposed, namely the general scheme, the superimposed scheme and the distinct scheme. Furthermore, the performance of these transmission schemes in the RSM aided SWIPT system is theoretically analysed. The energy harvested by the receiver is then maximised by jointly optimising the transmit power of the information signal and the covariance matrix of the energy signal as well as the power splitting ratio, while satisfying the quality of service of the wireless information transfer. At last, simulation results validate our theoretical analysis, while they also demonstrate that the distinct scheme has the best SWIPT performance among these three transmission schemes.

Enhancing earth-to-satellite FSO system spectrum efficiency with adaptive M-ary PSK and SIMO in presence of scintillation and beam wander

In this paper, the performance of the free-space optical (FSO) system from ground-to-satellite is analyzed considering the combined effect of atmospheric turbulence and beam wandering employing M-ary phase-shift keying (MPSK). Key parameters of the vertical connection, such as satellite altitude, zenith angle, and beam size, are investigated. In order to improve the spectrum efficiency, an adaptive transmission approach is applied to ensure efficient channel capacity usage. The procedure depends on changing the modulation order of the MPSK scheme according to the instantaneous channel state and the acceptable bit error rate. Furthermore, a single-input multiple-output (SIMO) system with maximal ratio combining (MRC) diversity is used to mitigate the effects of atmospheric turbulence and beam wandering. Closed-form and asymptotic expressions are presented for the average bit error rate (BER) for a single-input single-output (SISO) and SIMO techniques. Moreover, closed-form expression is deducted for the upper bound bandwidth efficiency. The accuracy of the derived closed-form and asymptotic expressions are verified by adopting appropriate simulation cases and parameters. The results show that the optimal value of the beam size ratio (BSZ) is 1.6. Also, the results prove that the adaptive technique improves spectrum efficiency by more four times the non-adaptive method at the same BER threshold of 10-2. By using a 1×4 SIMO system, the same adapted spectrum efficiency is achieved with a reduction of 4 dB in SNR versus 1×2 SIMO system and 8 dB in SNR versus SISO system. A 1×4 SIMO system achieves a threshold bit error rate of 5 dB reduction in SNR compared to a 1×2 SIMO system and a 10 dB reduction in SNR compared to SISO system.

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.