Centrally Controlled Dynamic Spectrum Access forMANETs

(Invited Paper)

Jeffrey Boksiner, Yuriy Posherstnik, Bryan MaySpace and Terrestrial Communications Directorate (S&TCD)

US Army RDECOM CERDEC, Aberdeen Proving Ground, MD, USA

Mark SaltzmanCommunications, Networks & Electronics Division

Scientific Research Corporation, Aberdeen, MD

Sherin KamalSAIC Inc. VA

Abstract—In this paper, we describe an approach to ad-dress increased demand for spectrum access associated withwidespread deployment of Mobile Adhoc Networks (MANETs)in a military environment. Our solution is an approach thatwe call “MANET Real-Time Frequency Management” (MRFM)that uses centralized control to achieve deconfliction with thebackground Electromagnetic Environment (EME) and amongthe mobile MANETs. Our approach automates frequency reuseamong MANETs and automates MANET spectrum sharing withbackground systems using a centralized reasoner and controlmechanism. Our system, which runs as an external application,collects MANET radio state information in real time, appliesspectrum policies, performs spectrum deconfliction and controlsthe frequencies used by the MANET remotely. Our approach doesnot require any modifications to the radio physical, media accessor link layer protocols (the “waveform”). The use of our systemprovides an expedient approach to enable Dynamic SpectrumAccess (DSA) capabilities to MANET radios that currently donot have such capabilities without requiring modifications tothe radio waveform or the radio itself. To validate the MRFMconcept, we implemented MRFM in a prototype system that wassuccessfully demonstrated in several tests.

I. INTRODUCTION

Department of Defense (DoD) policy for the the use of

the electromagnetic spectrum [1] lists several core principles.

These principles include the following:

• Ensure the U.S. warfighter has sufficient spectrum access

to support military capabilities.

• Use the spectrum as efficiently and effectively as practical

to provide the greatest overall benefit to warfighting

capability.

• Pursue spectrum-efficient technologies to support the

increasing warfighter demand for spectrum access and

encourage development of spectrum-dependent systems

that can operate in diverse electromagnetic environments

(EMEs).

Within the context of Army network modernization, key

application of these principles concerns spectrum efficiency

and effectiveness of Mobile Adhoc Networks (MANETs). To

facilitate spectrum access improvement in the near term, it

is desirable to introduce spectrum technology improvements

without waveform modifications, as defined by the DoD

waveform policy [2], or radio hardware changes.

In this paper, we describe one approach to address increased

demand for spectrum access associated with widespread de-

ployment of MANETs in a military environment. Our ap-

proach automates frequency reuse among MANETs and au-

tomates MANET spectrum sharing with background systems

using a centralized reasoner and control mechanism. Our sys-

tem, which runs as an external application, collects MANET

radio state information in real time, applies spectrum policies,

performs spectrum deconfliction and controls the frequencies

used by the MANET remotely. Our approach does not require

any modifications to the radio physical, media access or

link layer protocols (the “waveform”) or radio hardware. The

use of our system provides an expedient approach to enable

Dynamic Spectrum Access (DSA) capabilities to MANET

radios that currently do not have such capabilities without

requiring waveform modifications.

A. MANET Spectrum Considerations

Widespread deployment of any broadband service requires

highly efficient use of spectrum. The most important el-

ements of this efficient spectrum use is spatial frequency

reuse. Just like commercial services, widespread deployment

of MANETs in the military environment to provide voice,

data and situational awareness will require frequency reuse,

however military MANETs face unique spectrum challenges.

• Heterogeneity. Unlike the majority of commercial net-

works that operate on an exclusive use model over a given

geographical area, a variety of military systems must

share the same spectrum within an operating area. This

means that frequencies assigned to MANETs must be

deconflicted against all other military and civilian joint,

coalition and neutral systems (receivers and transmitters)

operating in the environment. The collection of these

background systems generally constitute the EME.

• Mobility. The defining feature of MANETs is mobil-

ity and ad-hoc topology. Unlike commercial networks,

MANETs have no fixed infrastructure (base stations,

2013 IEEE Military Communications Conference

978-0-7695-5124-1/13 $31.00 © 2013 IEEE

DOI 10.1109/MILCOM.2013.115

641

access points, etc.) to anchor the reuse patterns. Also, mil-

itary MANETs are organized hierarchically to correspond

to the organization of the military units. A particular

MANET moves along with the unit it supports. Although

movements are based on maneuver plans, the movement

of MANET nodes are subject to military contingencies

and are not fully predictable.

The combination of the need to locally deconflict against the

background EME and to support frequency reuse for mobile

networks with no fixed infrastructure presents a formidable

challenge to MANET spectrum management. One solution

is to assign frequencies to each MANET using pre-mission

spectrum planning tools, such as the Coalition Joint Spectrum

Management Planning Tool (CJSMPT) [3], While effective,

this approach is suboptimal, since the spectrum plan must

allow for a variety of contingencies and various deviations

from the maneuver plans. Another approach is Policy-Based

Radio (PBR) with sensing-based Dynamic Spectrum Access.

While sensing-based DSA should provide efficient spectrum

use, it’s implementation requires considerable change to the

radio protocols and the supporting spectrum management

infrastructure. Our goal is to enable PBR and DSA features in

current non-DSA MANET networks without modifying the in-

trinsic MANET protocols. Our solution described in this paper

is an approach that we call “MANET Real-Time Frequency

Management” (MRFM) that uses centralized control to achieve

deconfliction with the background EME and among the mobile

MANETs. In this paper we describe MRFM and a system we

have developed to implement and demonstrate MRFM.

B. Organization

The remainder of the paper is organized as follows:

• Sec II describes the basic principles and the algorithms

of MRFM.

• Sec III provides the MRFM system description.

• Sec IV describes the results of MRFM implementation

and demonstration.

• Sec V is the conclusion section.

II. MRFM PRINCIPLES AND ALGORITHMS

We assume that a number of MANET networks are required

to operate within a commanders Area of Interest (AoI). Also,

we assume that an enterprise frequency management process

exists that assigns frequencies to fixed and mobile emitters

and that these assignments and the appropriate equipment

characteristics are stored in a spectrum database, such as

the Spectrum Knowledge Repository (SKR) that is contained

within CJSMPT mentioned in refsec:challenges. This assump-

tion is consistent with the architecture proposed for policy-

based spectrum management [4]. The MANETs are allotted a

number of frequencies in the AoI such that

• The number of MANETs exceeds the number of allotted

frequencies requiring frequency reuse, and

• One or more MANET AoI-wide frequencies overlap

frequencies assigned to background systems requiring

local EME deconfliction.

Fundamentally, MRFM operation consists of the following

two steps:

1) Development of the digital spectrum policy for the

MANET AoI, and

2) Execution of the spectrum policy and a simultaneous

real-time frequency deconfliction among MANETs

The advantage of developing the spectrum policy first is that

the process of reasoning against this policy, which consists

of a policy query, is considerably faster that computation

of the interference between MANET and background EME.

However, the conversion of the background EME into policy

introduces a slight loss of fidelity, so that in cases where the

background EME is small, it is advantageous to skip the policy

step and perform all deconfliction in real-time.

A. Interference Determination

The spectrum policies and the real-time deconfliction are

based on evaluation the interference equation, which represents

the link budget equation applied to the interfering signal. The

equation using dB units is

PRFI = PTD − Ll, (1a)

Ll = LO + LS(p)−GTD(φ, θ)−GRP (φ, θ), (1b)

where

PRFI is the received power of the potential interferer,

PTD is the transmitter power of the potential transmitter,

Ll is the total loss ,

GTD is the directional antenna gain of the interferer,

GRP is the directional antenna gain of the receiver,

LS is the propagation loss that is exceeded for a percent-

age of time (probability) p, and

LO represents the sum of other possible losses, such as

line loss, cross-polarization loss, etc.

To evaluate interference over a given frequency range we

need to determine the interference power that propagates to

the receiver detector PI by subtracting the losses due to the

receiver filters. We calculate this extra loss using Frequency

Dependent Rejection (FDR) as follows [5]:

PI = PRFI − FDR(Δf). (2)

FDR represents the power loss due to receiver filtering and is

given by

FDR(Δf) =

∫∞−∞ df S(f)

∫∞−∞ df S(f)R(f+Δf)

, (3)

where

S(f) is the transmitter power spectral density assuming

the signal is uninterrupted,

R(f) is the receiver selectivity with the receiver tuned to

the transmitter frequency, and

Δf is the frequency separation between the interferer and

victim.

We evaluate the presence of interference by comparing PI to

an interference threshold, known as the Interference Protection

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Criterion (IPC) α. Unacceptable interference is deemed to

occur if PI > α. The most reliable way to determine the IPC

is by direct laboratory measurement. An alternative is to use

a signal-to-interference (SIR) or interference-to-noise (INR)

criterion defined by

α = N + INR, (4)

where N is the noise power at the receiver detector. Typically,

it is common to use INR = −6 dB.

The preceding analysis technique assumes that the inter-

ference determination is determined by considering a single

dominant interferer. This is reasonable on heuristic grounds

since each MANET operates on time-division basis, so we

expect that the single dominant interference event will control

interference determination. The survey of interference analysis

techniques in ref [6] observes that the literature has shown that

the “single dominant interferer” approach is effective approach

under a high (∼ 4) path loss exponent. Since a high path loss

exponent is generally associated with ground networks, and

the overall number of networks is relatively small, we expect

that our approach provides a sound solution.

B. Digital Spectrum Policies

Spectrum policies represent a variety of rules that control

how a DSA system uses spectrum. In MRFM, we primarily

develop spatial policies. Spatial policies define spatial restric-

tions on the use of frequencies by the MANET. The restrictions

are based on the protection of the background receivers from

interference by the MANET and protection of the MANET

nodes from interference by the background emitters. The

restrictions are defined for co-channel and adjacent channel

operation. The concept of the spatial policy is similar to the

protection areas commonly used in spectrum management.

1) Fixed Systems: Calculation of a protection policy for

fixed background systems is straight-forward. Since we know

the relevant technical parameters of each receiver from the

spectrum database, it is possible to calculate a detailed pro-

tection contour using eq. 1. In general, the protection contour

may be disconnected due to terrain effects. Since determining

location with respect to an arbitrary contour is computationally

expensive, the exact contour may be replaced with simpler

shapes that envelop the actual contours. Queries with respect to

a rectangle or a circle are simpler and can be used to represent

the contours. Fig. 1 shows the notional representation of exact

and simplified protection contours.

The dimensions of the protection contour are a function of

frequency separation between the receiver and the interferer.

2) Mobile Systems: The extension to the case of mobile

background systems is also straight-forward if their Area of

Operation (AoO) is in the spectrum database. We suggest three

basic approaches:

• Monte-Carlo simulation that calculate interference from

a random sample of locations. This is the most thorough

approach, but is also the most resource and time intensive.

• An approach that calculates the protection contour from

the boundary of the AoO. This is a conservative approach,

Fig. 1. Illustration of the concept of spatial prohibitive policy. Solid linesrepresent exact contours for prohibitive policy for co-channel (CC) systems,while the dashed line represent the contour for an adjacent channel system.DSA systems operating inside the contour apply the prohibitive policy andare not allowed to operate at the frequencies specified by the policy.

since most of the time, the mobile nodes are inside

the boundary. Also, this approach may miss interference

regions from points at high elevation inside the AoO.

• A hybrid approach that calculates the protection contour

on the basis of points at the boundary and high-elevation

points inside the AoO. This approach is less intensive

than full Monte-Carlo simulation. We selected this ap-

proach for our systems.

C. Deconfliction

Once the policies are established, the remaining key al-

gorithm concerns deconfliction of the MANET frequencies.

There are two steps to the deconfliction algorithm:

1) Computing the adjacency matrix that indicates what nets

can interfere with one another, and

2) Frequency selection using a graph coloring algorithm.

We describe these two steps in the following.1) Adjacency Matrix: The adjacency matrix is the graph-

theoretic representation of interference relationship among

nets. If each network is represented by a vertex, the adja-

cency matrix identifies the edges between the vertexes, where

each edge indicates a potential of the interference between

the networks. When two networks have potential for mutual

interference we call such networks coupled.

We compute the adjacency matrix by evaluating the interfer-

ence equation described in Sec. II-A between each node in one

MANET against every other node in all other MANETs. Also

we treat all relevant background systems as additional vertexes

in the adjacency matrix. We evaluate the coupling between

MANET nets and background systems either by evaluating

interference directly or by checking if any MANET network

members are within the prohibited policy contour associated

with the background system.

Fig. 2 shows an example of an adjacency matrix. In our

format, the matrix is formatted to contain 2 digit integers

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Fig. 2. An example of an adjacency matrix. The matrix is formatted to contain2 digit integers indicating the maximum interference dB above threshold thatany given node in a subnet was calculated to receive from a transmittingsubnet. The background systems are denoted in the matrix with a capital F.

indicating the maximum interference dB above threshold that

any given node in a subnet was calculated to receive from

a transmitting subnet. Any number in the matrix above 0

indicates the subnets are coupled, and will interfere with

each other on a given frequency. The matrix also contains

information regarding background systems (fixed frequency),

to ensure the background emitters are protected and their

frequencies do not get reused if an MRFM subnet would be

coupled to the background emitter. The fixed frequencies are

denoted in the matrix with a capital F.2) Frequency Selection: The Frequency Selection Algo-

rithm (FSA) is based on the well-known equivalence between

the problem of assigning non-interfering frequencies and ver-

tex graph coloring [7]–[10]. Our algorithm uses the sequential

graph coloring algorithm [10]. While, this algorithm is known

not to be optimum, it is simple and executes quickly.

In some cases, there may not be enough available fre-

quencies to ensure deconfliction between all the subnets. If

the case occurs, the FSA will start to decouple subnets to

gain assignable frequencies. The decoupling will be based

on the adjacency matrix from SAM, with the lowest priority

subnet being decoupled first. The lowest priority subnet will

always be decoupled first with the next subnet that contains the

lowest calculated interference above threshold. This ensures

the algorithm always provides a solution, and the subnets

always have a frequency assignment. However, in a scenario

where the spectrum requirement at a given time is greater than

the available spectrum, subnets may experience interference.

Once additional spectrum becomes available again, SAM will

produce a new adjacency matrix and the FSA will reassign

frequencies to ensure deconfliction on a non-interference basis.

III. MRFM SYSTEM DESCRIPTION

The MRFM system consists of the following components:

• Spectrum Database

• MANET Electromagnetic Environment Map (MEEM)

• Mission Thread Template (MTT)

• Electromagnetic (EM) Proxy

• Spectrum Analysis Module (SAM)

• Reasoner

• Communications Server

• Graphical User Interface (GUI)

Fig. 3. An example of graph coloring on an adjacency matrix. Each vertexrepresent a MANET network and edges represent possible interference. Dif-ferent vertex colors correspond to different frequencies separated sufficientlyto avoid adjacent channel interference.

Fig. 4. The MRFM system description.

• Radio Control Toolbox Module (RCTM).

The following sections describe each of these components.

Fig. 4 shows the MRFM system as we implemented it for our

demonstration.

A. Mission Thread Template (MTT)

The MTT requires the user to gather the requirements and

specifications about the non-DSA subnets being controlled by

the MRFM. This information includes: Network ID, Radio

ID, Transmit Power, frequency pool, net force structure, and

equipment characteristics. The MTT is provided as an input

to the Proxy, which then queries the Spectrum Database based

on the data provided by the MTT. The MTT is also provided

as input to the GUI to enable the visualization of the available

frequency pool and the net force structure.

The mission scenario AoI is contained within the MTT. The

MTT also contains the pieces of equipment to be used, and the

net force structure to identify which piece of equipment is in

which net. The user loads the MTT using the GUI, which

provides all that information to the 3D GUI visualizer, as

well as to the Proxy. The GUI displays the frequency pool, as

well as the real-time location and operating frequency of all

subnets. The Proxy uses the AoI coordinates provided in the

MTT to query the spectrum database, gather the background

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emitter records, and to obtain equipment characteristics for the

systems operational within the AoI. The Proxy then formats

the database query results into a standardized XML format

which can then be read by SAM.

B. Spectrum Database

A spectrum database is a relational collection of information

necessary to perform spectrum analysis calculations and fre-

quency deconfliction. The database must contain information

such as the required transmitter and receiver characteristics

of any system that has received a frequency assignment. The

database provides information through the Proxy to be used

as input by the Spectrum Analysis Module.

C. MANET Electromagnetic Environment Map (MEEM)

The MEEM is an entity containing all the relevant radio

information that may be used by one or more of the system

components within the MRFM. The MEEM includes infor-

mation such as: Lat/Long of each node in each subnet, the

frequency setting of each node in each subnet, and the radio

state of each node in each subnet. The MEEM is implemented

as a local multicast group, enabling any of the components to

join the group and subscribe to receive updates in real time.

The interface is defined using XML messages.

D. EM Proxy

The EM Proxy is the central interface between the different

components of the MRFM. The Proxy queries the spectrum

database to obtain background spectrum assignments for the

AoI for a given mission scenario. The database query also

contains equipment characteristics, to provide information

such as TX power, receiver sensitivity, transmitter emission

masks, receiver selectivity curve, etc. Once the Proxy receives

the results from the database query, it must transform it into

an XML format that is understood by SAM.

In addition, the Proxy also provides information to the

GUI to enable visualization of real-time movement, operating

frequency, and radio status.

E. Spectrum Analysis Module (SAM)

SAM is the computational brain of the MRFM system. SAM

implements the interference analysis, including FDR, propaga-

tion analysis, and policy generation described in Sec. II-A and

II-B. SAM is capable of generating spatial digital spectrum

policy in machine-readable OWL format [11], [12], where the

operational frequencies of the background nets are prohibited

from use by any other nets within the protective contour. SAM

is also capable of producing protective grids, as shown in Fig.

3. Finally, SAM computes the adjacency matrix based on net

to net interference calculations.

F. Reasoner

The Reasoner receives Position Location Information (PLI)

from each MANET node (accessed through the MEEM), as

well as the adjacency matrix created by SAM. The FSA,

contained within the Reasoner, uses the matrix as an input, and

identifies the optimum frequency reuse for the given locations

(a) (b)

Fig. 5. Illustration of notional protection contours for a passive receiver.Solid lines represent exact contours that would be calculated at a particularfrequency for a particular probability of interference.

of each MANET node at a given time. Once all acceptable

frequencies are assigned, the Reasoner provides a list of each

subnet with its proper corresponding frequency assignment to

the Communications Server.

While the module is referred to as a Reasoner, it may not

necessarily be doing any reasoning on digital policies or other

cognitive reasoning, as a Computer Science definition would

imply. The functionality of the Reasoner depends on the mode

of operation for SAM, as well as on the native capabilities of

the radio hardware being used.

G. Communication Server

The MRFM relies on the Simple Network Management

Protocol (SNMP), an Internet-standard protocol for managing

devices on an IP network to enable control of the communi-

cation systems from the Communications Server.

The Communications Server provides the interface between

the software and the MRFM-enabled network. The Server

receives the PLI, decodes the PLI, converts it to degrees lati-

tude and longitude, and provides the locations to the MEEM.

Once SAM calculates an adjacency matrix, the Reasoner de-

termines which frequency preset must be used on each subnet.

The Communications Server then sends out an SNMP “set”

command to the local multicast group. A similar component,

RCTM, also exists on each End User Device (EUD) attached

to every MRFM radio node. When the Communications Server

sends out the multicast SNMP command, each RCTM running

on the EUD in that group receives the command, and executes

the frequency preset change on the respective local radio node.

H. Graphical User Interface (GUI)

The GUI serves the function of providing an interface

and visualization of the operational scenario for the user.

The GUI consists of the NASA World Wind 3D mapping

and visualization suite. The GUI also uses the MEEM to

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Fig. 6. The screen capture of the MRFM user interface.

obtain the PLI for all nodes, with each PLI then displayed

on the map. Background emitters, which are queried from the

spectrum database by the Proxy and provided to the GUI, are

also displayed using the military standard icons MIL-STD-

2525C [13]. The MTT provides the list of available frequency

channels from the frequency pool, which is then displayed in

a table. The table also indicates which net is operating on

which frequency. This information is not vital, but is useful

in providing situational awareness for the user. Fig. 6 shows

a screen capture of the user interface.

I. Radio Control Toolbox Module (RCTM)

The RCTM is a key component of the MRFM, allowing for

the real-time frequency management of the MRFM-enabled

radio nodes. The RCTM resides on an Android-based device or

within the operating system of the radio, if available. The mod-

ule is responsible for polling and aggregating PLI data from all

the radio nodes. The polling is to ensure connectivity between

the Communications Server and the RCTM. The aggregate PLI

is used within the MRFM to discover the network hierarchy,

since it provides additional information such as node identifier

and minimizes the network overhead by reducing the amount

of messages passed between the Communications Server and

each radio node’s RCTM. The PLI is crucial information for

SAM, because the spectrum analysis calculations are based

on each node n real-time location. The RCTM also receives

frequency change commands from the Communications Server

and executes those changes on the local radio nodes.

IV. IMPLEMENTATION AND DEMONSTRATION

We implemented the MRFM in a demonstration system. The

hardware used for implementation included one laptop running

the software, several Android devices, and several radios. The

spectrum database used for the implementation was the SKR

contained within CJSMPT mentioned in Sec I-A.

The implementation of the RTFM was performed in sev-

eral phases. The first phase was a proof of concept, where

one MANET subnet was deconflicted with many background

emitters, and a grid-based digital spectrum policy was used

by the RCTM to ensure non-interference during real-time

frequency management of other MANET systems. The proof

of concept was successfully demonstrated at a series of field

experiments. The second phase was a developmental product

where multiple subnets are deconflicted with each other, as

well as with background emitters. The deconfliction ensures

non-interference, while the frequency selection algorithm pro-

vides greatly increased spectral efficiency and spectrum reuse.

This capability was also successfully demonstrated in several

outdoor tests.

V. CONCLUSION

We have developed a novel approach for providing DSA

capabilities to non-DSA MANETs through centralized control.

While the initial application of this technology is to improve

effectiveness of the MANET spectrum use, this capability can

be extended to support other applications, such as spectrum

sharing between military and commercial communication sys-

tems. Centralized MANET control could facilitate MANET

operation as either a primary or secondary user in bands

shared with commercial wireless systems. We believe that the

use of centralized control offers many possibilities for future

MANET capabilities and research.

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