Spectrum-sharing Approach Research Articles

An IOV Spectrum Sharing Approach based on Multi-Agent Deep Reinforcement Learning

Highly dynamic Internet of Vehicles spectrum sharing can share spectrum owned by vehicle-to-infrastructure links through multiple workshop links to achieve efficient resource allocation. Aiming at the problem that the rapid variations in channel states in highly dynamic vehicular environments can make it challenging for base stations to gather and manage information about instantaneous channel states, we present a multi-agent deep reinforcement learning-based V2X spectrum access algorithm. The algorithm is designed to optimize the throughput of V2I user under V2V user delay and reliability constraints, and uses the experience gained from interacting with the communication environment to update the Q network to improve spectrum and power allocation strategies. Implicit collaborative agents are trained through an improved DQN model combined with dueling network architecture and long short-term memory network layers and public rewards. With lagged Q-learning and concurrent experience replay trajectories, the training process was stabilized and the non-stationarity problem caused by concurrent learning of multiple agents was resolved. Simulation results demonstrate that our presented algorithm achieves a mean successful payload delivery rate of 95.89%, which is 16.48% greater than that of the randomized baseline algorithm. Our algorithm obtains approximately the optimal value and shows performance close to the centralized brute force algorithm, which provides a better strategy for further minimizing the signaling overhead of the Internet of Vehicles communication system.

Privacy-Aware Double Auction With Time-Dependent Valuation for Blockchain-Based Dynamic Spectrum Sharing in IoT Systems

For future Internet of Things (IoT) systems, data-driven and dynamic spectrum-sharing schemes can significantly improve the spectrum utilization and efficiency. However, conventional centralized architecture of such dynamic IoT spectrum-sharing systems is often considered to be nontransparent, costly, and vulnerable to potential attacks and single-point failures. To address the aforementioned issues, a blockchain-based dynamic spectrum-sharing scheme has been proposed and investigated in this work, which aims at enhancing the system by providing desirable features, such as decentralization, transparency, immutability, and auditability. By considering the privacy and transaction dynamics issues when blockchain is integrated into spectrum-sharing systems, a privacy-preserving double auction mechanism based on differential privacy is developed for incentivizing spectrum sharing, where the time-varying valuations of the spectrum resources are also taken into consideration. In the proposed auction, a winner determination problem (WDP) is formulated to decide the winning bidders and spectrum allocation. A deep reinforcement learning (DRL)-based method is then proposed for efficiently solving the WDP. The proposed auction mechanism can be integrated with smart contracts on blockchain platforms. Furthermore, the computation of the DRL-based method for solving the WDP is designed as part of the consensus mechanism in the blockchain. Theoretical analysis show that the proposed privacy-aware double auction mechanism satisfies the properties of differential privacy, individual rationality, and truthfulness. Finally, simulation results are provided to validate the performance of the spectrum-sharing approach.

Interference-Avoid Based Spectrum Sharing Approach for Loosely-Coupled Cognitive Radio Networks

Cognitive radio (CR) network is a promising technology to solve the problem of spectrum scarcity arising from the growth of usage of wireless networks and mobile services. CR networks can find idle channels and access them opportunistically with spectrum sensing technology. In this paper, resource allocation with sensing-based interference recording is considered for several loosely-coupled cognitive radio networks, in which the base station controls the end-users’ (EUs) transmission by making channel allocation strategies based on recorded interference information. We proposed a method to record this information and an allocation strategy with low computational complexity, to increase the capacity of tasks with fixed data size in the system. Numerical results show the effectiveness of our model for recording the statistical behaviour of the cognitive network interference and allocating channels for higher system capacity.

Joint QoE-based user association and efficient cell–carrier distribution for enabling fully hybrid spectrum sharing approach in 5G mmWave cellular networks

Densifying the network by adding more minicell towers or relays throughout a hot spot area while extensively reusing the available spectrum is an essential choice to improve QoS. Unfortunately, this approach can be prohibitively costly. One possible solution to reduce the capital and operating expenditure in such overdensified networks is the adoption of the spectrum-sharing approach. However, both approaches would complicate the interference phenomenon either among inter- or intraoperators, which may cause serious performance degradation. In this paper, a fully hybrid spectrum-sharing (FHSS) approach aided by an efficient cell–carrier distribution was proposed with consideration to the interference dilemma. Moreover, an adaptive hybrid QoE-based mmWave user association (mUA) scheme was presented to assign a typical user to the serving mmWave base station (mBS), which offers the highest achievable data rate. The proposed FHSS approach (with the presented QoE-based mUA) was compared with recent works and with both FHSS approach using the conventional max-SINR-based mUA, which assigns a typical user to the tagged mBS carrying the highest signal-to-interference-plus noise ratio and the baseline scenario (licensed spectrum access). In particular, three spectrum access methods (licensed, semipooled, and fully pooled) were integrated in a hybrid manner to engage improved data rates to users. Numerical results show that the joint cell–carrier distribution and FHSS approach with QoE-based mUA outperform both baselines FHSS with the max-SINR mUA scheme and the licensed spectrum access. Furthermore, results demonstrate the effectiveness of the proposed approach in terms of both operators’ independence and fairness.

A survey of mmWave user association mechanisms and spectrum sharing approaches: an overview, open issues and challenges, future research trends

Fifth generation (5G) cellular networks promise to support multi-radio access technologies (multi-RATs) with low and high frequencies aiming at delivering good coverage, several gigabits data rate, and ultra-reliable services. In this context, user-association and resource allocation appear to be a huge challenge due to the variety of specifications and varied propagation environments. In this treatise, the focus is on the technical and administrative difficulties of the adoption of user association (UA) mechanism and spectrum sharing approach (SSA) in millimeter wave (mmWave) systems, for example, the technical design considerations and their underlying options, as well as their impact on users and network performance. In addition, details on the importance of the rules and regulations of SSA are presented. This study also identified a few possible design solutions and potential promising technologies in both UA and SSA. In the context of UA, several mechanisms are identified, such as backhaul-, caching-, and hybrid multi-criteria-aware UA to achieve seamless connectivity and to enhance the network utility. In the context of SSA, this study pinpoints varied subjects that need to be explored, such as joint efficient rules and regulations enactment, assessment of fairness and independence in multi-independent mobile network operators (multi-IMNOs) that support SSA, as well as the implementation of hybrid-SSA via Virtualized Cloud Radio Access Network. Finally, attention is drawn to several key conclusions to enable readers and interested researchers to learn about the most controversial points of mmWave 5G cellular networks.

Independence and Fairness Analysis of 5G mmWave Operators Utilizing Spectrum Sharing Approach

The spectrum sharing approach (SSA) has emerged as a cost-efficient solution for the enhancement of spectrum utilization to meet the stringent requirements of 5G systems. However, the realization of SSA in 5G mmWave cellular networks from technical and regulatory perspectives could be challenging. Therefore, in this paper, an analytical framework involving a flexible hybrid mmWave SSA is presented to assess the effectiveness of SSA and investigate its influence on network functionality in terms of independence and fairness among operators. Two mmWave frequencies (28 GHz and 73 GHz) are used with different spectrum bandwidths. Various access models have been presented for adoption by four independent mobile network operators that incorporate three types of spectrum allocation (exclusive, semipooled, and fully pooled access). Furthermore, an adaptive multi-state mmWave cell selection scheme is proposed to associate typical users with the tagged mmWave base stations that provide a great signal-to-interference plus noise ratio, thereby maintaining reliable connections and enriching user experience. Numerical results show that the proposed strategy achieves considerable improvement in terms of fairness and independence among operators, which paves the way for further research activities that would provide better insight and encourage mobile network operators to rely on SSA.

Multi-Resource Allocation: Analysis of a Paid Spectrum Sharing Approach Based on Fluid Models

Nowadays industrial and academic communities are focusing much of their efforts to define the main characteristics of 5G. Cognitive radio (CR), offering the possibility to significantly increase the spectrum efficiency, will play a key role in the whole range of Internet of Things communications (one of the use cases of 5G networks). While CR is one of the most discussed topics in contemporary spectrum management, there are still many issues and challenges to be solved, even more when we think about large networks. In this context, one of the main question that motivates this paper is: how to encourage the spectrum sharing behavior of primary users (PUs)? With this in mind, we study a paid-sharing approach where secondary users (SUs) pay for spectrum utilization. We assume a preemptive system where PUs have strict priority over SUs, and the affected SUs will then be reimbursed, implying some cost for the PUs service provider. This paper bears on the analysis of the behavior of the system, where the number of users is arbitrary large and an admission control policy over SUs is applied. We develop a computationally efficient methodology to find an accurate estimation of the optimal admission control boundary based on fluid limits.

A Spectrum-Sharing Approach in Heterogeneous Networks Based on Multi-Objective Optimization

A Spectrum-Sharing Approach in Heterogeneous Networks Based on Multi-Objective Optimization

A Scalable Spectrum-Sharing Mechanism for Local Area Network Deployment

Current wireless access networks are able to provide relatively low data rates when compared with wired access. To extend the access to high-data-rate services to wireless users, the International Telecommunication Union (ITU) established new requirements for future wireless communication technologies of up to 100 Mb/s under high-mobility conditions and 1 Gb/s in low mobility. The low mobility goal can only be achieved through the use of highly optimized local area access networks operating at low range and low transmission power. The efficient sharing of radio resources among local area cells will be very difficult to achieve with a traditional network planning/dimensioning approach due to their intrinsic uncoordinated deployment characteristic. Cognitive radio (CR)-based networking methodologies are considered as the most promising solutions for such radio-resource-sharing problems, also enabling unlicensed/open spectrum operations. In this paper, a game-theory-inspired scalable algorithm for intercell dynamic spectrum access (IC-DSA) is introduced to enable distributed resource allocation in CR environments. Here, the new CR-based cell is called ?cognitive cell (C-cell),? and it is the minimal entity that allocates a resource set. The simulation results demonstrate the effectiveness of the proposed spectrum-sharing approach. This solution achieves a better overall performance in several load and interference scenarios in terms of both outage and average capacity when compared with fixed-frequency-reuse cases.

Fundamental capacity limits of cognitive radio in fading environments with imperfect channel information

In this paper, we analyze the capacity gains of opportunistic spectrum-sharing channels in fading environments with imperfect channel information. In particular, we consider that a secondary user may access the spectrum allocated to a primary user as long as the interference power, inflicted at the primar's receiver as an effect of the transmission of the secondary user, remains below predefined power limits, average or peak, and investigate the capacity gains offered by this spectrum-sharing approach when only partial channel information of the link between the secondaryiquests transmitter and primary's receiver is available to the secondary user. Considering average received-power constraint, we derive the ergodic and outage capacities along with their optimum power allocation policies for Rayleigh flat-fading channels, and provide closedform expressions for these capacity metrics. We further assume that the interference power inflicted on the primaryiquests receiver should remain below a peak threshold. Introducing the concept of interference-outage, we derive lower bounds on the ergodic and outage capacities of the channel. In addition, we obtain closedform expressions for the expenditure-power required at the secondary transmitter to achieve the above-mentioned capacity metrics. Numerical simulations are conducted to corroborate our theoretical results.

Capacity and power allocation for spectrum-sharing communications in fading channels

This paper investigates the fundamental capacity limits of opportunistic spectrum-sharing channels in fading environments. The concept of opportunistic spectrum access is motivated by the frontier technology of cognitive radio which offers a tremendous potential to improve the utilization of the radio spectrum by implementing efficient sharing of the licensed spectrum. In this spectrum-sharing technology, a secondary user may utilize the primary user's licensed band as long as its interference to the primary receiver remains below a tolerable level. Herein, we consider that the secondary user's transmission has to adhere to limitations on the ensuing received power at the primary's receiver, and investigate the capacity gains offered by this spectrum-sharing approach in a Rayleigh fading environment. Specifically, we derive the fading channel capacity of a secondary user subject to both average and peak received-power constraints at the primary's receiver. In particular, considering flat Rayleigh fading, we derive the capacity and optimum power allocation scheme for three different capacity notions, namely, ergodic, outage, and minimum-rate, and provide closed-form expressions for these capacity metrics. Numerical simulations are conducted to corroborate our theoretical results.

On the Impact of Dynamic Spectrum Sharing Techniques on Legacy Radio Systems

The biggest challenge faced by dynamic spectrum sharing (SS) systems is the design of SS schemes that do not adversely impact existing legacy systems in the absence of perfect knowledge. We address this issue by developing a framework to evaluate the interference profile at a legacy receiver under different system scenarios which include the hidden node and imperfect-sensing problems. By analyzing the interference distributions and by comparing the two basic approaches to SS - interference-avoidance-based overlay and interference averaging-based underlay - we identify desirable characteristics for SS radio systems.We then leverage this knowledge to motivate the use of a hybrid SS approach that combines the benefits of the two basic approaches and substantially reduces the impact to the legacy system. The advantage provided by this approach is shown to increase with an increase in the bandwidth available to the SS system. In addition, the approach is more robust to imperfect information. The inclusion of log-normal shadowing is shown to further accentuate these performance trends.

Outage-constrained capacity of spectrum-sharing channels in fading environments

Cognitive radio technology has been recently proposed for sharing and utilising the spectrum in order to satisfy the increasing demands for spectrum access. In this radio technology, secondary users may be granted access to the spectrum bands occupied by a primary user as long as the interference power, inflicted on the primary receiver as an effect of the transmission of the secondary user, is deemed unharmful. In this paper the authors assume that the successful operation of the primary user requires a minimum rate to be guaranteed by its channel for a certain percentage of time and obtain the interference-power constraint that is required to be fulfilled by the secondary user. Considering the input transmit-power constraint, on average or peak power, for the secondary user, the authors investigate the capacity gains offered by this spectrum-sharing approach when only partial channel information of the link between the secondary's transmitter and primary's receiver is available to the former. In particular, the lower bounds on the capacity of a Rayleigh flat-fading channel with two different transmission techniques, namely channel inversion and optimum rate allocation with constant power transmission, are derived. Closed-form expressions for these capacity metrics are provided, and numerical simulations are conducted to corroborate the theoretical results.