Co-operative use of licensed spectrum by unlicensed devices: the concept of Bandwidth

Scavenging Milos Tesanovic, Paul Bucknell, Hind Chebbo

Fujitsu Laboratories of Europe Ltd. Hayes, United Kingdom

e-mail: milos.tesanovic@uk.fujitsu.com

Abstract—To mitigate the spectrum depletion due to the unprecedented wireless traffic growth, FCC has freed up large amounts of UHF spectrum and made them available to license-exempt devices. The European Commission has adopted a similar stance by pledging to "reuse spectrum and create a single market out of it". The EC has gone as far as to call the radio spectrum the "economic oxygen". The approach whereby license-exempt (or unlicensed) devices are allowed (under certain, often very stringent, conditions) to access unused areas of the airwaves or gaps that exist in bands that have been reserved for TV broadcasts (so-called TV White Spaces), is being trialed in the US as well as the UK and the rest of Europe, with Japan preparing its own TVWS roll-out timeline. TV White Space spectrum is an attractive alternative to expensive auctioned spectrum, for applications including e.g. small cells.

In this paper we discuss an evolutionary approach looking beyond the current/emerging TV White Space concepts, for which we adopt the term Bandwidth Scavenging and which has the potential to: serve Primary User (PU) systems other than DTT; enable more dynamic spectrum sharing than the TVWS systems by providing incentives for the PU systems; allow Secondary Users (SUs) to serve as relays for PU traffic. We examine co-operation between the incumbents and SUs and demonstrate the trade-offs possible using a MATLAB simulator. We then highlight some of the changes needed in existing communication systems for the observed benefits to become a reality. We additionally discuss various models of spectrum sharing and changes needed in current spectrum legislation to support the proposed approach to collaboration.

Keywords—co-operative spectrum sharing; spectrum management; TV White Spaces; co-existence of primary and secondary networks; co-existence metrics; spectrum policies

I. INTRODUCTION AND BACKGROUND The “spectrum crunch” in the mobile industry has

resulted in a projected spectrum deficit in the US, expected to occur as early as 2013 [1]. Regulatory bodies around the world, including FCC, Ofcom, and the European Commission, have been rapidly freeing up large amounts of UHF spectrum. In addition, spectrum sharing (in its many

forms [2]) is strongly encouraged, with EC going as far as stating that “radio spectrum is economic oxygen” [2].

Arguably the first successful demonstration of mass spectrum sharing between licensees and license-exempt devices are the emerging TV White Space (TVWS) systems, where the licensees (incumbents, or primary users—PUs) are DTT (Digital Terrestrial Television) systems [3]. In this paper we offer a promising enhancement of existing and emerging TVWS systems and their extension to PU networks other than DTT. Much like TVWS systems, our work adopts the top-down approach to spectrum sharing, whereby the incumbents are fully protected and secondary users (SUs) require a grant to access the incumbents’ portion of spectrum. However, we extend this concept by assuming the PUs have a say in which of the SUs get to use their spectrum, based on the resulting benefits to PUs. In order to position our work, in the next Section we first give a brief overview of spectrum sharing techniques.

II. SPECTRUM SHARING: STATE-OF-THE-ART TECHNOLOGIES AND OUR FOCUS

Generally speaking there are three broad models [4] for allowing SUs to access white spaces in the PU band (process known as Dynamic Spectrum Access, or DSA): the interweave model (SU cannot access a licensed band as long as a PU is active in that band), the underlay model (SU is allowed access regardless of whether PU is active in a band but with certain power restrictions) and the overlay model (SUs are allowed to transmit simultaneously with PUs so long as there is no performance degradation for said PUs). The interweave model is arguably the best-studied and the most conservative [4], whilst the overlay model, also known as Opportunistic Spectrum Access (OSA), has been receiving steadily increasing attention [4]-[6].

We will show in our approach that it is possible to further enhance the interweave approach (such as TVWS) with some of the overlay model ideas for co-operation, most notably the concept described in [6] of selecting SUs based on the benefit to the PU system. Bandwidth Scavenging (BWS) is a term used in literature [7], [8] to essentially denote OSA, and which we examine in the context of co-

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operative use of licensed spectrum by ‘unlicensed’ (or license-exempt) devices, all with a view to enabling increased sharing of ‘idle’ spectrum between SUs and incumbent (PU) devices with the PUs’ benefit in mind. Specific to our case, this benefit is a combination of appropriately modeled monetary gain and coverage enhancement.

Out of DSA techniques described above, co-operation is the most promising in terms of business incentives to PUs; these can potentially be very significant as PUs will in future be able to rely on a myriad of widely deployed Internet of Things / Machine-to-Machine devices which can offer either monetary and/or coverage compensation at no cost to PUs. Co-operation is also the most efficient in terms of spectrum utilization. Additionally, co-operation reduces overhead of spectrum sensing and is therefore more energy efficient. It is however more complex and has standards impact—more about this in Section V.

There have been several studies looking at optimizing PU benefits arising from PU/SU co-operation. In [9], SU selection optimization aiming to maximize the PU rewards is described, with the focus therein being solely on monetary gain. This concept of “spectrum rental” of PU usage gaps is extended in [10], where the authors presented a co-operative scheme for internetwork spectrum sharing among multiple SU systems, which takes into account the price and spectrum efficiency as the design criteria. The focus in [10] is the performance of SU systems, with the gain to the PU system being again purely monetary. Additionally, neither [9] nor [10] focus on identifying which of the existing and emerging systems the model applies to. Potential deployment scenarios are postulated in [11], where an analytical model for the quality of coexistence is described; it is ensured that no harmful interference is caused to PU systems, but without offering any additional benefits to PU systems.

III. PROPOSED APPROACH: SYSTEM DESCRIPTION AND SIMULATION SET-UP

BWS is about the mechanics of how we do co-operation, and the benefits to the PU system; this paper’s main focus is on the latter. A high-level diagram highlighting the main concepts is given in Fig. 1. We assume that the negotiations between PU and SU systems is aided by a “spectrum broker”—in our case, an extension of the TVWS database concept. It is additionally envisaged that the access of SU devices to PU bands could be enabled via over-the-air control information. However and as explained in Section II, the implementation details are not the subject of this paper, but rather the potential benefits (including design of suitable metrics) and potentially novel spectrum sharing use cases. In this paper we do not design protocols for the exchange of information between PU and SU systems or propose a specific implementation of the spectrum broker; we assume these are in place and study the potential benefits on a simple but illustrative co-operation model. Some relevant protocol design issues are addressed in [6] and [12].

To demonstrate the potential benefits, an SNR distribution for the PU system is assumed across a grid of 50x100 pixels, split into blocks of 10x10 pixels. Rician

fading is assumed, with the R parameter being constant within a 10x10 block while varying independently from one block to the next. This enables us to model hot-spots and coverage holes in a simple and effective way, and to demonstrate effects of co-operative spectrum sharing on the PU system capacity, both visually and quantitatively.

Figure 1. The concept of adapted BWS.

It is assumed that a portion of the original bandwidth, as determined by the variable parameter γ, is kept for exclusive use of the PU system. The remainder of the system bandwidth is for the use of SU devices; part of it, however, will on occasions be used to relay PU traffic. This is done in a location- and time-specific manner, as determined by the parameter α, adding a novel element to the selection process of [9]-[11]. The bandwidth usage schematic is given in Fig. 2, while PU system parameters are summarized in Table I.

It is further assumed that a total of 10 master SU devices (or APs) are randomly dropped across the PU grid. They can serve as relays for PU traffic, and when they do, the assumptions on the transmit SNR and power loss are given in Table II. The power loss is inversely proportional to the square of the distance. Table II additionally details the values of α used in the simulations, as well as two basic metrics: the monetary gain and the capacity gain. The capacity gain is relatively straightforward to define: it is the ratio between the PU devices’ SNR increase due to SU APs relaying PU traffic, and the total capacity in the same pixel region when there is no co-operation.

Figure 2. PU-SU bandwidth sharing parameters.

TABLE I. PU SYSTEM PARAMETERS.

Parameter ValueSize of grid 5×10 blocks of 10×10 pixelsSNR distribution Rician fading within a block;

independent among blocks Value of R parameter Random between 1 and 10Values of γ [0, 0.2, 0.4, 0.6, 0.8, 0.9, 0.95, 1]

TABLE II. SU SYSTEM PARAMETERS.

Parameter ValueNumber of SU master devices L 10 Distribution of SU master devices Random across the entire PU gridTransmit SNR for SU APs when acting as relays for PU traffic

50dB

Power loss -5, -11, -17, -23 [dB]Values of parameter α [0.1, 0.2, 0.3, 0.4, 0.5, 0.6]“Monetary” gain to PU system Capacity gain from a single SU AP

The monetary gain, on the other hand, is not as easy to

define. “Monetary” should be understood here in a very broad sense: it may indeed be the monetary recompense the SU system gives to the PU system in exchange for using some of its spectrum. Whatever the physical manifestation of the gain to the PU system may be, it stands to reason that it should decrease as both γ and α increase. The metric that we use for this “monetary” gain (which we initially outlined in [13]) is given in Table II; other metrics commonly used can be found in [10], [14]. Value for α is then chosen that maximizes the overall co-existence metric, which is in our case a weighted sum of the capacity and monetary gains:

IV. RESULTS Fig. 3 shows the PU system capacity (assuming a 5MHz

bandwidth and SNR values based on parameters from Table I), with (a) depicting the baseline case (without co-operation with the SU system), while (b) and (c) show the PU system capacity for two different values of γ. It is clear that capacity in proximity of SU APs (locations of which are shown with a star marker) significantly improves when spectrum sharing is deployed. It is however equally apparent that the achievable capacity drops in other areas of the grid as a percentage of the bandwidth is relinquished, which is to be expected. It is noted that such sharing of spectrum would be enabled only if the PU system can accept the latter situation whilst the SU APs are active.

A spatially averaged result is shown in Fig. 4, for two different values of weighting parameters. As can be seen from Fig. 3, areas around many of the SU APs benefit from co-operation while others experience a capacity drop. Fig. 4 nonetheless shows that the average overall capacity for selected operating parameters is higher than when there is no co-operation (as shown by the dotted red line, y=x), effectively increasing spectrum utilization. The operating point on the curve will depend heavily on the current traffic load and the value spectrum sharing brings to the PU system, epitomized by the metric used, ours being only one example.

Please note that the non-zero capacity of the PU system, observed even for γ=0, is due to the assumption that the SU devices are still relaying some PU traffic. This is not impossible, but it is unlikely that the PU system would give up all of its bandwidth as long as there is some PU data to be transmitted.

V. REMARKS ON CO-OPERATIVE SPECTRUM SHARING Spectrum sharing entails a number of aspects: system

performance; gains to PU system; protocols, signaling and infrastructure required to enable the co-operation; spectrum legislation; and business use cases. This paper has so far only covered the first two points (with the focus of system performance analysis being on quantifying the PU rather than the SU system performance). In this Section we shall touch upon some of the other issues.

In Table III we summarise a number of existing PU/SU scenarios and indicate where we feel BWS is applicable. We also propose potentially novel uses of spectrum sharing principles in emerging applications, such as Small Cell, D2D and Machine-Type Communications (MTC) applications, and put BWS forward as an applicable sharing technology.

When considering the practicalities of co-operation, an important consideration is the ease of sharing information between the PU and SU systems. If a single entity can control the sharing of spectrum (which could result from PU and SU systems being run by the same operator), then this can simplify the process of allowing an SU system to access PU resources. When this is not the case, then the use of standardised spectrum sharing protocols could be used to allow sharing without allowing direct overall control. When a central entity is used which can co-ordinate available spectrum between the PU system and the SU system, standardised sharing protocols may still be required in the case where interoperability between different vendors is a requirement for a cost-competitive supply chain. We highlight here two emerging scenarios, based on cases 9 and 10 we identified in Table III:

1. “Regular” LTE-A Macrocell Radio Access as PU user and MTC or Device-to-Device (D2D) or LTE-A Small Cell (outdoor and indoor) radio access links as SU users; and

2. LTE-A backhaul links as PU user and MTC or D2D or LTE-A Small Cell (outdoor and indoor) radio access links as SU users

In these scenarios spectrum sharing is performed between conventional cellular users of licensed spectrum and users who do not require the full functionality that the PU system offers.

The high-level concepts of our BWS are RAT-agnostic, meaning that our models of co-operation and the key performance indicators (KPIs) for “quality of co-existence” are applicable to a wide range of scenarios. This being said, the specifics of the PU-SU information exchange are RAT-specific.

αγ /)1(_ 2−=gainMon

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SNRgainCap

)1(log

)1(log)1(_

2

__2αγ

)__(1_ 21 gainMonwgainCapwL

gainOverall ⋅+⋅=

PU system capacity in Mbps and SU locations: no co-operation

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Figure 3. PU system capacity: (a) no co-operation; (b) γ=0.6; (c) γ=0.8.

(a) (b) Figure 4. PU system capacity and overall gain: (a) w1=2, w2=1; (b) w1=1, w2=2.

TABLE III. COMMON AND PROPOSED SPECTRUM SHARING USE CASES AND BWS APPLICABILITY.

Scenarios 1 2 3 4 5 6 7 8 9 10PU Cellular

Operator A Cellular Operator

A

Broadcast (DTT)

Broadcast (DTT)

Unlicensed Unlicensed Protected Protected Cellular Operator

Cellular Operator backhaul

linkSU Cellular

Operator B Unlicensed Cellular

Operator Unlicensed Cellular

Operator Unlicensed Cellular

Operator Unlicensed MTC /

D2D / Small Cell

MTC / D2D /

Small Cell Specs for sharing?

3GPP None None (TVWS?)

TVWS None IEEE Not allowed

Not allowed

3GPP

BWS? Yes Yes Yes Yes Yes

VI. CONCLUSIONS Spectrum scarcity poses a real danger to evolution and

expansion of wireless networks and applications, and spectrum sharing is encouraged by FCC, Ofcom and EC as the way forward. White Spaces technology is being tested for unlicensed access to the TV spectrum; however, existing and emerging solutions offer no incentive to the incumbents. Additionally, dynamic spectrum allocation is currently not supported, which becomes an issue if the PU system is e.g. a cellular system, with often rapidly varying load. As a solution, we propose BWS integrated with co-operation between the incumbents and SUs and demonstrate some trade-offs possible. Standardization of spectrum sharing for the co-operation between PU and SU systems will be required for many of the possible BWS scenarios. The identification of these scenarios is an important step and we have highlighted some key use-cases in this paper. Additionally, the key legislative obstacle—the ban to share licensed spectrum once it has been granted for exclusive use—would need to be revisited.

Our adapted BWS concept builds upon the existing co-operation models and is conceived as an evolutionary approach beyond the current/emerging White Space concepts. It is more dynamic than TVWS (this being due to the static nature of the DTT network planning) and hence enables a more efficient use of scarce spectrum. Unlike TVWS, BWS allows prompts/triggers from SUs, which in turns enables the PU system to decide which devices get to share its spectrum based on the resulting benefits.

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September 2012 (last accessed May 2013) [3] http://stakeholders.ofcom.org.uk/spectrum/tv-white-spaces/

(last accessed May 2013)

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[10] P. Si, H. Ji, F. R. Yu, and V. C. M. Leung, “Optimal Cooperative Internetwork Spectrum Sharing for Cognitive Radio Systems With Spectrum Pooling”, IEEE Transactions on Vehicular Technology, vol. 59, no. 4, pp. 1760-1768, May 2010.

[11] C. Sun, G. P. Villardi, Z. Lan, Y. D. Alemseged, H. N. Tran, and H. Harada, “Optimizing Coexistence Performance of Secondary User Networks under Primary User Constraints for Dynamic Spectrum Access”, IEEE Transactions on Vehicular Technology, vol. 61, no. 8, pp. 3665-3676, October 2012.

[12] X. Zhou, Z. Yan, Q. Zhang, and D. Wu, “A Cell Based Dynamic Spectrum Access Scheme”, The 2nd IEEE International Conference on Information Management and Engineering (ICIME), pp. 155-157, April 2010.

[13] M. Tesanovic, “Co-operative use of licensed spectrum by unlicensed devices”, invited talk at the 3rd IoT Forum, Bled, Slovenia, November 2012 (http://iot-forum.eu/events/iot-international-forum-event-3/presentations/technology/02_tesanovic, last accessed May 2013)

[14] Y. Yi, J. E. Zhang, Q. Zhang, and T. Jiang, “Spectrum Leasing to Multiple Cooperating Secondary Cellular Networks”, IEEE International Conference on Communications (ICC), Kyoto, Japan, June 2011.