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Near-Optimal Dynamic Spectrum Allocation in Cellular Networks
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In this paper, we address the spectrum allocation problem in cellular networks under the coordinated dynamic spectrum access (CDSA) model. In this model, a centralized spectrum broker owns a part of the spectrum and issues dynamic spectrum leases to competing base stations in the region it controls. We consider a dynamic auction based approach where the base stations bid for channels depending on their demands. The broker allocates channels to them with an objective to maximize the overall revenue generated subject to wireless interference in the network. This problem is known to be NP-hard and has been addressed before in limited context. We address this problem in a very generic context where (i) interference in the network is modeled using pairwise and physical interference models and (ii) base stations can bid for heterogeneous channels of different width using generic bidding functions. We propose efficient approximation algorithms that give near optimal solutions with provable analytical bounds. Detailed simulation studies using randomly generated and real base station networks show that our algorithms scale very well for large network sizes.
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... As stated above, achieving strategy-proof optimal allocation and computational feasibility in a mechanism is NP-Hard. In [20], the authors present a DSA mechanism in cellular networks which achieves near-optimal allocation for revenue maximization using greedy graph coloring approach. The authors in [15] studies real-time spectrum allocation mechanism. ...
... The authors in [15] studies real-time spectrum allocation mechanism. Though, the mechanisms proposed in [20], [15] are computationally feasible in terms of implementation, they are not guaranteed to be strategy-proof. In [21], the authors propose a mechanism which ensures a certain fair chance of spectrum allocation along with the maximization of social welfare. ...
... Most of the existing works is centered on designing a computationally feasible strategy-proof spectrum auction mechanism for non-cooperative base station participation in auctions. Moreover, [7], [11], [12], [20], [21], [24], [25], [27], [28] consider base stations with uniform channel demand. However, only few works [7], [11], [28] consider multiple channel demand across the BSs. ...
To address the exponentially increasing data rate demands of end users, necessitates efficient spectrum allocation among co-existing operators in licensed and unlicensed spectrum bands to cater to the temporal and spatial variations of traffic in the wireless network. In this paper, we address the spectrum allocation problem among non-cooperative operators via auctions. The classical Vickrey-Clarke-Groves (VCG) approach provides the framework for a strategy-proof and social welfare maximizing auction at high computational complexity, which makes it infeasible for practical implementation. We propose sealed bid auction mechanisms for spectrum allocation which are computationally tractable and hence applicable for allocating spectrum by performing auctions in short durations as per the dynamic load variations of the network. We establish that the proposed algorithm is strategy-proof for uniform demand. Furthermore, for non-uniform demand we propose an algorithm that satisfies weak strategy-proofness. We also consider non-linear increase in the marginal valuations with demand. Simulation results are presented to exhibit the performance comparison of the proposed algorithms with VCG and other existing mechanisms.
... Despite that dynamic CA has been studied in the context of spectrum sharing from various perspectives such as graph coloring [99][100][101][102] and game theory [103][104][105], the aforementioned challenges (i.e., channel and geographic contiguity, spatially varying channel availability, and coexistence awareness) differentiate the dynamic CA in the CBRS from previous work. In this work, we make the following specific contributions: ...
... However, the vast majority of existing works do not consider geographic and channel contiguity constraints and thus are not applicable to CA in the CBRS. In [101], Subramanian et. al. ...
... introduced the notion of channel graph to enforce channel contiguity, where each vertex is a channel consisting of several contiguous primitive channels and each edge indicates overlapping channels. In Section 5.5.2, we will show that our proposed algorithm outperforms the algorithm in [101] in terms of accommodating more users and meeting greater demand. ...
The exponential growth of mobile data services has translated into a proportionate surge in demand for greater wireless broadband capacity. Within today's xed spectrum allocation regime, exclusive spectrum access rights are granted to federal and commericial users, but a signicant portion of the licensed spectrum has been underutilized by primary users (PUs). To alleviate articial spectrum scarcity, spectrum sharing has been proposed to allow secondary users (SUs) to opportunistically access the locally unoccupied spectrum, called White Spaces (WS), so long as they do not cause harmful interference to PUs. To this end, the FCC is actively pursuing policy innovations to create shared spectrum, including WS in TV bands (TVWS) and the 3.5 GHz Citizens Broadcast Radio Service (CBRS) band, which often relies on a spectrum manager that manages the shared spectrum access, such as the database administrator (DBA) in TVWS and the Spectrum Access System (SAS) in CBRS. Our work begins by showing that the empirical DBA models for TV coverage estimation are locally inaccurate, since they do not explicitly account for local obstructions. Therefore, we propose augmenting the DBA approach with spatial-statistics-based radio mapping using Kriging and show that it achieves more accurate coverage boundary estimation, which leads to fewer missing WS opportunities (type-I errors) while keeping misclassications (type-II errors) under a certain limit. Scaling spatial-statistics-based radio mapping to larger areas inevitably meets cost limitations. An economically viable alternative is crowdsensing, that is, outsourcing sensing tasks to spatially distributed users with mobile devices that are outtted with spectrum sensors. In order to attract user participation for crowdsensing, we propose an auction-based incentive mechanism, in which each user submits a bid (the minimum acceptable payment) for providing spectrum data and receives a payment when selected. We show that the proposed scheme is truthful, computationally ecient, individually rational, and budget feasible. We also consider the design of a pricing-based incentive mechanism, in which the platform who constructs radio maps makes one-time oers (the incentive for participation) to selected users (either sequentially or in batches) and collects data from those who accept the offers. We formulate pricing mechanism design as expected utility maximization, where the expected utility captures the tradeo between radio mapping performance (location and data quality), crowdsensing cost, and uncertainty in oer outcomes (possible expiration and rejection). We show that the proposed user selection algorithm provides a provable performance guarantee and the proposed mechanism outperforms the baseline mechanisms. After WS opportunities are identied, it is crucial to eciently allocate resources (e.g., available channels) to SUs. To this end, we study SAS-assisted dynamic channel assignment in the CBRS. We propose a novel graph representation to capture spatially varying channel availability, channel contiguity, and coexistence opportunities, which allows us to employ or develop ecient algorithms with provable performance guarantees. As the last piece of this thesis, we study the problem of monitoring whether Wi-Fi and duty cycled LTE Unlicensed (LTE-U) are sharing channel access time in a fair manner. We propose a scheme that allows the spectrum manager to estimate the duty cycle of a target LTE-U system and detect duty cycling misbehaviors with a high probability of detection, while keeping the false alarm probability under a certain limit.
... However, the vast majority of existing works do not consider geographic and channel contiguity constraints and thus are not applicable to CA in the CBRS. In [12], Subramanian et. al. introduced the notion of channel graph to enforce channel contiguity, where each vertex is a channel consisting of several contiguous primitive channels and each edge indicates overlapping channels. ...
... al. introduced the notion of channel graph to enforce channel contiguity, where each vertex is a channel consisting of several contiguous primitive channels and each edge indicates overlapping channels. In Section VI-B, we will show that our proposed algorithm outperforms the algorithm in [12] in terms of accommodating more users and meeting greater demand. ...
... In this section, we evaluate the proposed algorithm (Max-Reward) based on GMWIS (Algorithm 2) for binary GAA CA and compare it against the Max-Revenue Algorithm (MRA) in [12]. Note that npSMC is not applicable, as it requires the same set of contiguous available channels at each node and cannot handle flexible demands. ...
The paradigm of shared spectrum allows secondary devices to opportunistically access spectrum bands underutilized by primary owners. Recently, the FCC has targeted the sharing of the 3.5 GHz (3550-3700 MHz) federal spectrum with commercial systems such as small cells. The rules require a Spectrum Access System (SAS) to accommodate three service tiers: 1) Incumbent Access, 2) Priority Access (PA), and 3) Generalized Authorized Access (GAA). In this work, we study the SAS-assisted dynamic channel assignment (CA) for PA and GAA tiers. We introduce the node-channel-pair conflict graph to capture pairwise interference, channel and geographic contiguity constraints, spatially varying channel availability, and coexistence awareness. The proposed graph representation allows us to formulate PA CA and GAA CA with binary conflicts as max-cardinality and maxreward CA, respectively. Approximate solutions can be found by a heuristic-based algorithm that searches for the maximum weighted independent set. We further formulate GAA CA with non-binary conflicts as max-utility CA. We show that the utility function is submodular, and the problem is an instance of matroid-constrained submodular maximization. A local-searchbased polynomial-time algorithm is proposed that provides a provable performance guarantee. Extensive simulations using a real-world Wi-Fi hotspot location dataset are performed to evaluate the proposed algorithms. Our results have demonstrated the advantages of the proposed graph representation and improved performance of the proposed algorithms over the baseline algorithms.
... As a result, for interference mitigation and efficient resource allocation in the wireless cellular network, there has been an ample body of research. [19][20][21][22][23][24] Across all these works, the common theme is that they aim to jointly allocate resources while employing efficient power control mechanism in the PHY layers to limit interference. However, resource allocation and joint power are difficult problems to solve optimally and most solutions use approximate algorithms. ...
... 25 Interference alignment is another approach that has been proposed in the literature for multiple antenna (MIMO) systems. 17,[20][21][22][23][24][25][26] The idea of interference alignment is to coordinate multiple transmitters so that their mutual interference aligns at the receivers, facilitating simple interference cancelation techniques. This potentially improves the spectral efficiency and leads to exploitation of maximum possible degree of freedom (DOF) of multiuser wireless systems. ...
Mobile applications and social networks tend to enhance the needs for high‐quality content access. To address the expeditious growing demand for data services in 5G cellular networks, it is important to develop distribution techniques and an efficient content caching, aiming to significantly reduce redundant data transmission and, thus, improve the efficiency of the networks. In modern communication systems, caching has emerged as a vital tool for reducing peak data rates. It is anticipated that energy harvesting and self‐powered small base stations are the fundamental part of next‐generation cellular networks. However, uncertainties in energy are the main reason to adopt energy efficient power control schemes to reduce SBS energy consumption and ensure the quality of services for users. Using the edge cooperative caching such as energy efficient design can also be achievable, which reduces the usage of the capacity limited SBSs backhaul and the energy consumption. To support the huge power demand of cellular network, renewable energy harvesting technologies can be leveraged. In addition to this, power supply to the infrastructures is the main challenge to the mobile network operators (MNOs) especially in terms of economic optimum, sustainability, and green energy in developing countries for the growth of cellular networks. Renewable energy–based solutions for MNOs not only reduce the overall carbon dioxide emissions but also provide numerous profits. To address the expeditious growing demand for data services in 5G cellular networks, it is important to develop distribution techniques and an efficient content caching, aiming to significantly reduce redundant data transmission and thus improve the efficiency of the networks. In modern communication systems Caching has emerged as a vital tool for reducing peak data rates. It is anticipated that energy harvesting and self‐powered small base stations are the fundamental part of next‐generation cellular networks.
... Determining the winning bids with maximum sum is an NP-hard problem [24]. For the single minded model, each bidder i is bidding for a fixed amount of items and does not take any part of it. ...
... However, since the Greedy algorithm does not worry about truthfulness, we set the payments to be the same as the winning bids. Note that this a very optimistic and very unrealistic assumption about Greedy's payments since it can be easily shown that, without enforcing truthfulness, the revenue of the mechanism can be severely damaged due to market manipulations of untruthful players [24]. Figures 5 and 6 show the revenue of the two algorithms under consideration. ...
In this paper, we consider the cooperative relay problem in an ad hoc cognitive radio (CR) network consisting of two types of CR nodes: continuous power nodes (CPN) and limited/intermittent power nodes (LPN). All CR nodes are associated with a Secondary Base Station (SBS). To improve energy efficiency and extend the lifetime of LPNs, we allow LPNs to cooperate with neighboring "idle" CPNs to deliver/relay their packets to the SBS while providing incentives to relay CPNs. A crucial challenge in enabling such type of cooperative relay lies in resolving the competition between LPNs on the potential relay opportunities. To regulate such a competitive environment, we develop an auction-based market model consisting of a set of brokers (idle CPNs) and a set of available frequency channels. The brokers iteratively issue short-term dynamic spectrum leases of these channels to competing LPNs. The SBS receives the LPNs' bids and computes the output of the auction such that the maximum social-welfare (SW) is achieved by effectively allocating the available channels to the CR nodes. Computing a solution with maximum SW is, in general, NP-hard (even for one broker), but can be solved optimally using a pseudo polynomial time algorithm. Thus, we devise a polynomial time auction mechanism with near-optimal SW. Our mechanism enforces the very valuable property of strategy-proofness to mitigate the market manipulation problem resulting from untruthful behavior of the bidders (enforcing truthful bidders behavior). Simulation results are provided, which verify the effectiveness of our mechanism and demonstrate the significant gain achieved over a reference greedy solution.
... Determining the winning bids with maximum sum is an NP-hard problem [24]. For the single minded model, each bidder i is bidding for a fixed amount of items and does not take any part of it. ...
... However, since the Greedy algorithm does not worry about truthfulness, we set the payments to be the same as the winning bids. Note that this a very optimistic and very unrealistic assumption about Greedy's payments since it can be easily shown that, without enforcing truthfulness, the revenue of the mechanism can be severely damaged due to market manipulations of untruthful players [24]. Figures 5 and 6 show the revenue of the two algorithms under consideration. ...
... To address the interference issue in spectrum allocation, auction based power allocation mechanism has been proposed in [9], which fail to be incentive compatible. In [10], authors proposed algorithm based on greedy graph coloring approach for spectrum allocation that maximizes the revenue of the auction. ...
... Make p i * ← σ c i * and Make X i * ← 1. 10: ...
To address the demand of exponentially increasing end users efficient use of limited spectrum is a necessity. For this, spectrum allocation among co-existing operators in licensed and unlicensed spectrum band is required to cater to the temporal and spatial traffic variations in the wireless network. In this paper, we consider multiple operator spectrum allocation problem via auctions. The classical Vickrey-Clarke-Grooves (VCG) approach provides a strategy-proof and social welfare maximizing auction at the cost of high computational complexity which makes it intractable for practical implementation. We propose a sealed bid auction for spectrum allocation, which is computationally tractable and can hence be applied as per the dynamic load variations of the network. We show that the proposed algorithm is strategy-proof. Simulation results are presented to exhibit the performance comparison of the proposed algorithm and the VCG mechanism.
The exponentially increasing demand for data neces- sitates efficient spectrum allocation among operators in wireless networks. In this paper, we address the spectrum allocation problem among non-cooperative operators via auctions. The classical Vickrey-Clarke-Groves (VCG) approach provides the framework for a strategy-proof and social welfare maximizing auction. However, the VCG mechanism has high computational complexity, which makes it infeasible for practical implementa- tion. In this work, we propose sealed bid auction mechanisms for spectrum allocation, which are computationally tractable. These can be used for spectrum allocation by performing auctions at shorter intervals to cater to the dynamic load variation in the network. We establish that the proposed algorithm is strategy- proof for the uniform demand scenario. Furthermore, for non- uniform demand, we propose an algorithm that satisfies weak strategy-proofness. Here, we also consider non-linear increase in the marginal valuations with demand. Simulation results are also presented to exhibit the performance comparison of the proposed algorithms with VCG and other existing mechanisms.
Dynamic spectrum access, enabled by cognitive radio technologies, has become a promising approach to improve efficiency in spectrum utilization, and the spectrum auction is one approach in which unlicensed wireless users lease some unused bands from spectrum license holders. However, spectrum auctions are different from traditional auctions studied by economists, because spectrum resources are interference-limited rather than quantity-limited, and it is possible to award one band to multiple secondary users with negligible mutual interference. Due to its special feature, the multi-winner auction is a new concept posing new challenges in the existing auction mechanisms such as the Vickery-Clarke-Groves (VCG) mechanism. Although widely employed in other auctions, the VCG mechanism does have serious drawbacks when applied to the multi-winner auction, such as unsatisfactory revenue and vulnerability to collusive attacks. Therefore, in this paper, we propose a multi-winner spectrum auction framework, and develop suitable mechanisms for this kind of auction. In specific, the mechanism awards the bands in such a way that the spectrum efficiency is maximized, and determines prices based on the Nash bargaining solution to improve revenue and prevent collusion. We further analyze that secondary users do not have incentives to manipulate information about mutual interference which is essential to the auction. Finally, simulation results are presented to evaluate our proposed auction mechanisms.
In this work we analyze the complexity of local broadcasting in the physical interference model. We present two distrib- uted randomized algorithms: one that assumes that each node knows how many nodes there are in its geographical proximity, and another, which makes no assumptions about topology knowledge. We show that, if the transmission prob- ability of each node meets certain characteristics, the analy- sis can be decoupled from the global nature of the physical interference model, and each node performs a successful lo- cal broadcast in time proportional to the number of neigh- bors in its physical proximity. We also provide worst-case optimality guarantees for both algorithms and demonstrate their behavior in average scenarios through simulations.
Market-driven dynamic spectrum auctions can drastically improve the spectrum availability for wireless networks strug- gling to obtain additional spectrum. However, they face sig- nificant challenges due to the fear of market manipulation. A truthful or strategy-proof spectrum auction eliminates the fear by enforcing players to bid their true valuations of the spectrum. Hence bidders can avoid the expensive overhead of strategizing over others and the auctioneer can maximize its revenue by assigning spectrum to bidders who value it the most. Conventional truthful designs, however, either fail or become computationally intractable when applied to spectrum auctions. In this paper, we propose VERITAS, a truthful and computationally-efficient spectrum auction to support an eBay-like dynamic spectrum market. VERITAS makes an important contribution of maintaining truthful- ness while maximizing spectrum utilization. We show ana- lytically that VERITAS is truthful, efficient, and has a poly- nomial complexity of O(n3k) when n bidders compete for k spectrum bands. Simulation results show that VERITAS outperforms the extensions of conventional truthful designs by up to 200% in spectrum utilization. Finally, VERITAS supports diverse bidding formats and enables the auctioneer to reconfigure allocations for multiple market objectives.
The past decade has seen many advances in physical layer wireless communication theory and their implementation in wireless systems. This textbook takes a unified view of the fundamentals of wireless communication and explains the web of concepts underpinning these advances at a level accessible to an audience with a basic background in probability and digital communication. Topics covered include MIMO (multi-input, multi-output) communication, space-time coding, opportunistic communication, OFDM and CDMA. The concepts are illustrated using many examples from real wireless systems such as GSM, IS-95 (CDMA), IS-856 (1 x EV-DO), Flash OFDM and UWB (ultra-wideband). Particular emphasis is placed on the interplay between concepts and their implementation in real systems. An abundant supply of exercises and figures reinforce the material in the text. This book is intended for use on graduate courses in electrical and computer engineering and will also be of great interest to practising engineers.
How much traffic can wireless networks carry? Consider n nodes located in a disk of area A sq. meters, each capable of transmitting at a data rate of W bits/sec. Under a protocol based model for successful receptions, the total network can carry only Θ (W√An) bit-meters/sec, where 1 bit carried a distance of 1 meter is counted as 1 bit-meter. This is the best possible even assuming the nodes locations, traffic patterns, and the range/power of each transmission, are all optimally chosen. If the node locations and their destinations are randomly chosen, and all transmissions employ the same power/range, then each node only obtains a throughput of Θ (W√nlogn) bits/sec, if the network is optimally operated. Similar results hold for a physical SIR based model
The past decade has seen many advances in physical-layer wireless communication theory and their implementation in wireless systems. This textbook takes a unified view of the fundamentals of wireless communication and explains the web of concepts underpinning these advances at a level accessible to an audience with a basic background in probability and digital communication. Topics covered include MIMO (multiple input multiple output) communication, space-time coding, opportunistic communication, OFDM and CDMA. The concepts are illustrated using many examples from wireless systems such as GSM, IS-95 (CDMA), IS-856 (1 × EV-DO), Flash OFDM and ArrayComm SDMA systems. Particular emphasis is placed on the interplay between concepts and their implementation in systems. An abundant supply of exercises and figures reinforce the material in the text. This book is intended for use on
We design truthful double spectrum auctions where multiple parties can trade spectrum based on their individual needs. Open, market-based spectrum trading motivates existing spectrum owners (as sellers) to lease their selected idle spectrum to new spectrum users, and provides new users (as buyers) the spectrum they desperately need. The most significant challenge is how to make the auction economic-robust (truthful in particular) while enabling spectrum reuse to improve spectrum utilization. Unfortunately, existing designs either do not consider spectrum reuse or become untruthful when applied to double spectrum auctions. We address this challenge by proposing TRUST, a general framework for truthful double spectrum auctions. TRUST takes as input any reusability-driven spectrum allocation algorithm, and applies a novel winner determination and pricing mechanism to achieve truthfulness and other economic properties while significantly improving spectrum utilization. To our best knowledge, TRUST is the first solution for truthful double spectrum auctions that enable spectrum reuse. Our results show that economic factors introduce a tradeoff between spectrum efficiency and economic robustness. TRUST makes an important contribution on enabling spectrum reuse to minimize such tradeoff.
We propose resource allocation algorithms based on the auction method for uplink OFDMA cellular networks. We consider cellular systems that employ the traditional static frequency reuse as well as the next-generation systems that aim to achieve a universal frequency reuse via base-station coordination. Our algorithms are designed for finite input alphabets and also account for non-ideal practical outer codes, and they can be implemented in a distributed manner, when applied for multi-cell resource allocation. The proposed algorithms have a complexity of O(N) per user per iteration, where N denotes the number of subcarriers in the system, and are also well suited for parallel implementations. We also address power and bandwidth constraints that are motivated by practical concerns. The proposed algorithms exhibit very low complexity and simulation results demonstrate that they offer near-optimal performance.
A number of studies have shown the abundance of unused spectrum in the TV bands. This is in stark contrast to the overcrowding of wireless devices in the ISM bands. A recent trend to alleviate this disparity is the design of Cog- nitive Radios, which constantly sense the spectrum and op- portunistically utilize unused frequencies in the TV bands. In this paper, we introduce the concept of a time-spectrum block to model spectrum reservation, and use it to present a theoretical formalization of the spectrum allocation prob- lem in cognitive radio networks. We present a centralized and a distributed protocol for spectrum allocation and show that these protocols are close to optimal in most scenarios. We have implemented the distributed protocol in QualNet and show that our analysis closely matches the simulation results.
The coexistence and resource sharing between a primary network utilizing cognitive relays and a secondary network are investigated. Two multiple access protocols are proposed to coordinate idle time slots sharing between the two networks in a TDMA setting. While relays in the primary network are using these free time slots to help users in the primary network forward their unsuccessfully transmitted packets, users of the secondary network use these time slots to transmit their own packets. The diversity-multiplexing sort of tradeoff imposed by this resource sharing problem and optimum resource allocation strategy are studied through the characterization of the maximum stable throughput region of both networks.