Spectrum Allocation Efficiency Research Articles

Base Station Switching and Resource Allocation for 5G Heterogenous Networks

Enhanced 4th Generation Wireless Network (4G) is called 5th Generation Wireless Network (5G) as it helps in increasing the data rate, capacity and therefore energy efficiency and spectral efficiency of 5G network, in 5G massive MIMO, multiple numbers of antennas are used to transmit the signal with same timefrequency to maximise the number of users, who can communicate with less number of channels. Energy conception is the most dangerous issue in all the generations of wireless networks such as traditional firstgeneration to fifth-generation because of interference, eco signals, fading, packet loss, wastage of bandwidth, remaining energy and security like malicious attacks, blocking whole attacks and wormhole attacks. This efficient research work focused energy-efficient resource allocation scheme based on the shortest job first scheduling algorithm in wireless network (SJF) for the downlink orthogonal frequency division multiple accesses (OFDMA) heterogeneous networks (HetNets) developed. To maximize the spectrum allocation efficiency for the fifth generation (5G) mobile networks, frequency reuse-1 is employed. Thus, advanced inter-cell interference coordination techniques are required to mitigate the inter-cell interference for 5G HetNets. In this paper, the energy-efficient optimization problem based on coordinated scheduling is formulated, which is a shortest path problem and link breakage is intractable to solve directly. The above proposed model was analysed using different parameters energy, bandwidth, Quality of Service (QoS) and interference.

On the Optimal Duration of Spectrum Leases in Exclusive License Markets With Stochastic Demand

This paper addresses the following question which is of interest in designing efficient exclusive-use spectrum licenses sold through spectrum auctions. Given a system model in which customer demand, revenue, and bids of wireless operators are characterized by stochastic processes and an operator is interested in joining the market only if its expected revenue is above a threshold and the lease duration is below a threshold, what is the optimal lease duration which maximizes the net customer demand served by the wireless operators? Increasing or decreasing lease duration has many competing effects; while shorter lease duration may increase the efficiency of spectrum allocation, longer lease duration may increase market competition by incentivizing more operators to enter the market. We formulate this problem as a two-stage Stackelberg game consisting of the regulator and the wireless operators and design efficient algorithms to find the Stackelberg equilibrium of the entire game. These algorithms can also be used to find the Stackelberg equilibrium under some generalizations of our model. Using these algorithms, we obtain important numerical results and insights that characterize how the optimal lease duration varies with respect to market parameters in order to maximize the spectrum utilization. A few of our numerical results are non-intuitive as they suggest that increasing market competition may not necessarily improve spectrum utilization. To the best of our knowledge, this paper presents the first mathematical approach to optimize the lease duration of spectrum licenses.

Binary Quantum Elite Particle Swarm Optimization Algorithm for Spectrum Allocation in Cognitive Wireless Medical Sensor Network

Cognitive wireless medical sensor network (CWMSN) is a new development direction of the wireless sensor network (WSN) in recent years. The requirements of CWMSN are multi-faceted such as optimized utilization of resources, energy efficiency and channel sharing. However, CWMSN also faces the problem of limited energy and spectrum. For this reason, this paper proposes a spectrum allocation model. Moreover, a new binary quantum-behaved elite particle swarm optimization algorithm (BQEPSO) based on the combination of quantum operator, elite operator and binary particle swarm optimization (BPSO) is proposed to solve the spectrum allocation problem in CWMSN. The algorithm can enable the conflict-free use of spectrum resources in CWMSN and maximize the efficiency of spectrum allocation. The BQEPSO is compared with the genetic algorithm (GA) and traditional particle swarm optimization (PSO) under the same experimental conditions. The simulation results indicate that the performance of BQEPSO is better than the other two algorithms. And BQEPSO can maintain the total throughput of the CWMSN. What’s more, BQEPSO has a high network reward and throughput.

Towards Flexible and Truthful Incentive for Multichannel Allocation in DSA

Due to its potential of increasing spectrum utilization, dynamic spectrum access (DSA) is a promising platform to solve the so-called spectrum shortage problem, caused by a huge proliferation of wireless applications and services. Because of good allocation efficiency and fairness, auction based mechanisms have been extensively studied in DSA, in which truthfulness is a critical property to guarantee that each bidder can obtain her maximal utility by bidding with her true valuation of bidding spectrum. However, existing spectrum auction mechanisms on homogenous channels strictly require bidders to bid one channel or multiple channels with continuous demands, and does not consider the noncontinuous demands for channels. In this paper, we propose THIMBLE, the first TrutHful Incentive Mechanism for flexiBle muLtichannEl allocation by considering bidders’ continuous/noncontinuous demands for channels and spatial reusability. Specifically, bidders using the same channel without interference are formulated to a group, and a group bid recalculation method is presented for noncontinuous group bids. Next, a winner selection and charging method based on group bids is designed to achieve truthfulness. Extensive simulation results show that THIMBLE achieves not only truthfulness in continuous and noncontinuous channel demand cases, but also as good spectrum allocation efficiency as existing spectrum auction mechanisms.

Economic efficiency of spectrum allocation

Spectrum demand is rapidly expanding, driven by the developments of incumbent radio systems, as well as with the requirements of new technologies and market players to get spectrum access. In this regard, one of the fundamental functions of the state spectrum regulator is to create an enabling administrative and legal environment to ensure efficient spectrum use and to mitigate scarcity of this valuable natural resource. This paper analyses the economic value of spectrum use and suggests an extension of the spectrum's traditional technical boundaries, in order to take into consideration energy, environmental, sanitary and bio-geotechnical limits. The study reviews the phenomena of increasing transaction costs and negative externalities of spectrum access requiring economic criteria and assessment to achieve optimum resource allocation with a spectrum's demand growth. Results develop an input-output matrix as an allocation instrument to achieve spectrum efficiency and optimum equilibrium based on analysis of the economic effects from different band utilization scenarios, supplemented by currently used technical criteria. Practical application of proposed economic methods should improve the existing spectrum management system.

Spectrum Allocation by Sealed Bid Game Theory

Wireless communication subscribers are increasing day by day specially in fifth generation (5G) wireless communication where multiple number of users (Multiple Input Multiple Output or MIMO) can be served in a specific time. The heavy data usage is also enhanced with the increasing the number of subscribers, this data transfer speed depends on the amount of spectrum allocation to the specific subscriber. Thus, spectrum allocation is a major criterion for wireless communication performance improvement. The spectrum allocation efficiency can be observed by Game Theory, which is a popular decision maker of modern era. Sealed Bid Game theory is one of the popular segment of the game theory. The spectrum allocation can be done by using Sealed Bid Game theory and spectrum equilibrium can be observed by using different sub division of Sealed Bid Game theory.

<inline-formula> <tex-math notation="LaTeX">$PROST$ </tex-math> </inline-formula>: Privacy-Preserving and Truthful Online Double Auction for Spectrum Allocation

Spectrum auction is an effective way to redistribute scarce spectrum resources. However, most spectrum auction designs only target at economic robustness, while neglecting the inherent privacy leakage problem. Existing secure spectrum auction mechanisms fail to provide adequate security, and they all neglect the online fashion of spectrum request arrival. In this paper, for the first time, we propose a Privacy-pReserving and truthful Online double auction mechanism for Spectrum allocaTion in wireless networks, PROST . Compared with the state-of-the-art solutions, PROST provides a comprehensive and strong protection for users’ sensitive information, especially for location privacy and time dynamics. PROST is constructed based on our carefully designed security building blocks, which support various arithmetics over encrypted real numbers, and they are also well applicable in other spectrum auctions. Besides, we improve on the existing online spectrum auction mechanisms by designing a novel privacy-preserving buyer grouping protocol for spectrum reuse. We not only theoretically prove that PROST can realize an all-round security against semi-honest adversaries but also extensively evaluate its performance. Experimental results validate that PROST achieves nice spectrum allocation efficiency with light computation and communication costs.

A KNN Learning Algorithm for Collusion-Resistant Spectrum Auction in Small Cell Networks

Existing spectrum auction algorithms rarely consider the collusion-resistant, which decreases the spectrum allocation efficiency. In this paper, we propose a collusion-resistant spectrum auction algorithm based on K-Nearest Neighbor (KNN) learning in small cell networks. The algorithm can satisfy the increasing requirements of broadband services, improve the utilization of spectrum and also enhance the power-transmitting efficiency in small cells. Considering the interference among small cells, the KNN algorithm is used to classify all the small cells according to the small cells’ geographic locations and interference radius, which can improve the collusion-resistance ability of spectrum auction and improve the spectrum allocation efficiency. Simulation results are presented to verify the effectiveness of the proposed algorithm.

A multi-greedy spectrum auction algorithm for cognitive small cell networks

Cognitive small cell networks consisting of macro- and small cells are foreseen as a candidate solution to meet ever increasing requirements of broadband services and new applications. However, the traditional fixed spectrum allocation policy makes available spectrum resources for small cells insufficient. Therefore, an efficient spectrum allocation method is urgently needed that allows a large number of small cells to share spectrum resources with macro-cells. In this article, a real-time spectrum auction model is presented which aims at assigning the scarce spectrum resources to small cells quickly. The co-win situation is constructed, and the trade-off between spectrum utilization and revenues is controlled. Such a problem is formulated as an NP-hard optimization problem for which a low-complexity multi-greedy algorithm is proposed to obtain prices and spectrum allocations. The proposed algorithm can achieve conflict-free spectrum allocations that maximize the utility and spectrum allocation efficiency. Compared with the Vickrey–Clarke–Groves algorithm, simulation results show the higher utility and spectrum allocation efficiency of the proposed algorithm.

Auction-based spectrum allocation for CoMP systems utilizing hybrid division duplex

The coordinated multi-point (CoMP) transmission is a well-recognized promising technique for achieving high spectral efficiency. In this paper, we study the performance of the spectrum allocation and the system utility of the CoMP systems. First, we combine the hybrid division duplex (HDD) with a CoMP system to form a CoMP–HDD system, for the purpose of guaranteeing the quality demand of the channel state information (CSI) feedback. Second, in order to improve the system utility and the spectrum allocation efficiency of the CoMP–HDD system, we utilize the auction theory for the spectrum allocation. A system utility maximization problem is formulated as an NP-hard problem. Finally, we propose a multi-band multi-winner (MBMW) greedy algorithm to optimize the system utility and the spectrum allocation efficiency. Our simulation results demonstrate the effectiveness of the proposed algorithm.

Spectrum Auction for Differential Secondary Wireless Service Provisioning With Time-Dependent Valuation Information

In this paper, we propose a spectrum auction mechanism for secondary spectrum access in cognitive radio networks. Different from existing works in the literature, the time-dependent buyer valuation information is employed in the proposed mechanism so that the primary spectrum owner (PO) can determine more favorable spectrum allocations and pricing functions in order to maximize the expected auction revenue. In addition, to exploit the temporal spectrum reusability, the proposed mechanism allows each secondary wireless user to declare its specific time preferences, including service starting time, delay tolerance, and service length. By further considering the heterogeneities in secondary wireless service provisioning, the proposed mechanism is able to support heterogeneous forms (continuous or disjointed spectrum usages) of secondary spectrum requests. Specifically, at the beginning of the auction frame, secondary wireless users report their different spectrum usage requests along with the bidding prices, while the PO decides a single-step spectrum allocation and calculates the payment for each winner based on not only the received bids but also the known time-dependent valuation information. Theoretical analyses and simulation results show that the proposed auction mechanism can satisfy all desired economic properties, and can improve the spectrum allocation efficiency and auction revenue compared with counterparts.

An efficient spectrum assignment algorithm based on variable-grouping mechanism for flex-grid optical networks

Flex-grid optical networks (FONs) employ dynamic routing and spectrum assignment (RSA) algorithms to support diverse services with heterogeneous bit-rates. Although these RSA algorithms can increase the flexibility and efficiency of spectrum allocation, they may also possibly induce spectrum fragments when allocating spectrum to accommodate different service requests. The generated spectrum fragments may exhaust the available spectrum resources and degrade networking performances. Therefore, many schemes referred as defragmentation algorithms have been proposed to reduce spectrum fragments at the cost of traffic disruption or extra components, which are usually required to handle the fragmented spectrum via resource re-optimization. Although some grouping RSA algorithms have been proposed to prevent the generation of spectrum fragments with no traffic disruption or extra components, the pre-divided fixed spectrum groups reduce the flexibility in a dynamic spectrum assignment and thus degrade the blocking performance of the network. In this paper, we propose a RSA algorithm based on variable-grouping mechanism, namely Minimized Variable Grouping (MVG) RSA algorithm, which can not only efficiently restrain the generation of spectrum fragments, but also improve the blocking performance compared to the typical ungrouped and the conventional grouping RSA algorithms. By employing variable grouping mechanism, the proposed algorithm sorts services into different kinds according to their bandwidth requirements and then divides the spectrum resources into several variable groups according to the kinds of services. And the generation of the spectrum fragments is restricted in the spectrum intervals between two adjacent groups. In this way, the proposed algorithm can dramatically restrain the generation of fragments. In addition, the proposed algorithm can reduce the blocking probability by minimizing the grouped spectrum resources to maximize the remained vacant spectrum resources in the spectrum intervals between two adjacent groups for future service requests and thus helps improve the blocking performance. The simulation results show that the proposed MVG RSA algorithm can dramatically reduce the fragments with no traffic disruption while exhibiting a low blocking probability.

Evolutionarily stable opportunistic spectrum access in cognitive radio networks

In order to fully utilise limited spectrum resources of multiple channels and multiple radios in cognitive radio networks, the authors propose a potential game model for opportunistic spectrum access based on both accurate and inaccurate spectrum state estimation with considering the interference constraints of licensed users. Three algorithms are proposed to achieve equilibrium of the proposed game. First, assuming spectrum sensing results are accurate, a joint strategy fictitious play-based channel selection algorithm with incomplete information is presented, and it can achieve a pure Nash equilibrium (NE) of the proposed game. Second, in order to make the outcomes of game robust, an evolutionary spectrum access mechanism with complete information is introduced by using evolutionary game theory based on inaccurate spectrum state estimation so that evolutionary stable strategy (ESS) can be achieved. Finally, with incomplete network information, a distributed learning algorithm is proposed to achieve a mixed NE, which is proved to be an ESS. Simulation results show that these algorithms can significantly improve spectrum allocation efficiency while reducing mutual collision.

A General Privacy-Preserving Auction Mechanism for Secondary Spectrum Markets

Auctions are among the best-known market-based tools to solve the problem of dynamic spectrum redistribution. In recent years, a good number of strategy-proof auction mechanisms have been proposed to improve spectrum utilization and to prevent market manipulation. However, the issue of privacy preservation in spectrum auctions remains open. On the one hand, truthful bidding reveals bidders' private valuations of the spectrum. On the other hand, coverage/interference areas of the bidders may be revealed to determine conflicts. In this paper, we present PISA, which is a PrIvacy preserving and Strategy-proof Auction mechanism for spectrum allocation. PISA provides protection for both bid privacy and coverage/interference area privacy leveraging a privacy-preserving integer comparison protocol, which is well applicable in other contexts. We not only theoretically prove the privacy-preserving properties of PISA, but also extensively evaluate its performance. Evaluation results show that PISA achieves good spectrum allocation efficiency with light computation and communication overheads.

Towards Privacy Preservation in Strategy-Proof Spectrum Auction Mechanisms for Noncooperative Wireless Networks

The problem of dynamic spectrum redistribution has been extensively studied in recent years. Auctions are believed to be among the most effective tools to solve this problem. A great number of strategy-proof auction mechanisms have been proposed to improve spectrum allocation efficiency by stimulating bidders to truthfully reveal their valuations of spectrum, which are the private information of bidders. However, none of these approaches protects bidders' privacy. In this paper, we present PRIDE, which is a PRIvacy-preserving anD stratEgy-proof spectrum auction mechanism. PRIDE guarantees $k$ -anonymity for both single- and multiple-channel auctions. Furthermore, we enhance PRIDE to provide $\ell $ -diversity, which is an even stronger privacy protection than $k$ -anonymity. We not only rigorously prove the economic and privacy-preserving properties of PRIDE, but also extensively evaluate its performance. Our evaluation results show that PRIDE achieves good spectrum redistribution efficiency and fairness with low overhead.

Increasing the Efficiency of Spectrum Allocation

Over the past 80 years, the Federal Communications Commission has been responsible for the allocation of non-governmental use of the radio frequency spectrum. Over that time, here have been significant changes in spectrum use that have been driven by changes in demand and technology. The technical, regulatory, and business obstacles in past reallocations shed light on some of the FCC’s implementation decisions for its upcoming two-sided auction.