5G Revolution

No. 35
November 2020

The Mitchell Forum

The Coming 5G Evolution in Network Centric
Warfare: The Sensor Saturation Theory

By Lt Col Anthony Tingle, USA retired

About the Forum Abstract

The Forum presents innovative concepts and The technological advances of 5G networking necessitate
thought-provoking insight from aerospace relooking at current philosophies on battlespace data gathering.
experts here in the United States and across Thousands of miniature interconnected sensors could provide new
the globe. As a means to afford publishing fidelity on the battlespace. This sensor saturation could provide
opportunities for thoughtful perspectives, Mitchell a counterintuitive solution to the growing problem of wasted
Institute’s Forum provides high visibility to writing intelligence data collection. Through saturation the network is
efforts spanning issues from technology and strengthened, although each individual sensor is devalued, and
operational concepts to defense policy and the metadata becomes more valuable than the actual data. With
strategy. emerging technologies, analysts can approach data holistically,
reducing their reliance on alerts to enemy activities and positions
The views expressed in this series are those in the operating environment. This paper explains how new 5G
of the authors alone, and do not necessarily technology will transform intelligence collection and provides a new
represent the views of the Mitchell Institute for perspective on battlespace data.
Aerospace Studies.
F-35As at Hill AFB,
Utah, where they are
developing 5G dynamic
spectrum sharing
capabilities between
airborne radar systems
and 5G cellular systems
in the 3,100-3,450 MHz
band.

U.S. Air Force Photo

Introduction advantages in information warfare. Recent
The U.S. government now has the commercial advances in networking and
data analysis have spurred the U.S. military
ability to deliver munitions so precisely that to consider how these technologies will lead
it is using explosive-free Hellfire missiles to future battlespace dominance.
with sharp blades to kill a specific passenger
inside a vehicle without causing collateral Fifth generation (5G) networking
damage.1 As the physical means to destroy technology stands to revolutionize battlespace
our enemies becomes ever more automatic, sensing and the way militaries approach data.
the identification, tracking, and targeting Rapid growth of networking technologies
of these malcontents become the critical is driven by factors such as powerful and
components of the kill chain. The quest for small microelectronics, automated data
battlespace omniscience is not new; warriors manipulation and artificial intelligence,
have been attempting to “know the enemy” and advanced wireless connectivity. 5G
long before Sun Tzu ever immortalized the networking technologies such as these
idea in the Art of War. will converge to enable future capabilities
and presents a new theory of information
Prompted by the digital revolution and dominance based on these projections.
corresponding advances in data transfer,
manipulation, and storage, information The Evolution of NCW
took a new form, and a new imperative, in In looking at the application of
the realm of warfare. The term Network
Centric Warfare (NCW) began to circulate technology to warfare, it is necessary to ask
in earnest in the late 1990s as the U.S. two questions. First, what has changed?
military sought the same synergies found Second, why is this change significant? The
in commercial digital information sharing.2 short answer to the first question is that the
NCW became the cornerstone of military technology of network operations, including
information infrastructure development. the handling of data on those networks,
is approaching a critical moment in its
Since its inception, the adoption and evolution. Specifically, 5G networking and
application of NCW throughout the U.S. its corresponding sensors are here, and like
military has been both rewarding and the commercial networking revolution of
challenging. The services have embraced the late 1990s, they will undoubtedly change
and adopted the concept unevenly. The the nature of the civilian communications
Air Force adopted it early with successes industry. The answer to the second question
in multiple conflicts including Operation on the significance 5G is, at its core, that
Allied Force and Operation Iraqi Freedom.3 these networking technologies hold the
Although the Army continues to struggle opportunity to change the way we conduct
with the complexities of developing an military intelligence and targeting.
information strategy for land forces, the
military continues to evolve its information 5G networking, like many modern
prowess.4 innovations, is a confluence of multiple
technologies. It uses miniature cell “towers”
Today the more encompassing that consume less energy, and it exploits the
concept of information warfare dominates advantages of beam forming to send signals
the discussion on military operations and only where necessary. It makes novel use of
technology acquisitions. As during the early the electromagnetic spectrum, particularly
days of NCW, technological developments in high and low frequencies. 5G networks
in the civilian sector signal military

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will also handle extreme amounts of traffic Two Applicable Theories
using massive multiple-input multiple- Before delving into the possible
output (massive MIMO) architecture.
It will also use different communication military uses of 5G networking, it is useful
protocols to allow machines and nodes to to review two theories that have influenced
easily connect to each other and eventually network development. These theories
the “combat cloud.”5 The network will have primarily attempt to explain information
lower power-requirements, lower latency transfer and the value of these networks.
(essentially the time to send information), It is this previous theoretical work that
and larger bandwidth. underpins future theories that will guide the
development of the next evolution of NCW.
These projections of 5G networking
foretell future military capabilities and Claude Shannon’s Mathematical Theory of
applications. For example, advances in Communication
reducing the size of radio components, such as
in radio-frequency microelectromechanical At the dawn of digital communication,
systems, should allow for much smaller and MIT’s Claude Shannon developed the most
more numerous sensors on the battlespace.6 influential theory regarding the amount
In the future, each person, vehicle, drone, of information that can be transferred
or robotic entity on the battlespace would electronically. His theory starts by
effectively have sensors and communication describing information in terms of discrete
equipment, and they would be connected binary digits, also known as bits, in the
to all the other sensors.7 Additionally, the form of 1s and 0s. He then expressed the
reduced size and cost of 5G sensors could number of bits (the signal) that could flow
increase in the number of simple sensors between destinations as the size of the river,
across the battlespace. These small, low- or bandwidth. Finally, he theorized that this
power sensors could be delivered through process could be muddied by outside factors,
airborne means into a conflict zone.8 Each or noise.10 In other words, interference
of these nodes will be connected to each reduces the transfer of information across
other and simultaneously send data to the a signal, and the higher the ratio of signal
combat cloud.9 strength to interference, the more data that
can be transferred. It will be important
The future of the networked to refer back to Shannon’s theory when
battlespace is a combination of thousands of discussing the amount of information that
sensors. These communication technologies future networks provide, as this paper will
will allow networks with endless nodes, each later discuss the amount of noise that is
sending data to multiple vectors, effectively actually created in current military systems
blanketing an area of operations with data by the signal itself.
gathering on a scale familiar to internet-
based firms like Google, Facebook, or Metcalfe’s Law
Amazon that depend on immense amounts In the earliest days of the internet,
of information. Similar to the information
revolution of the 1990s, 5G military it became obvious that the rapid
technology must follow close on the heels of connectivity and information flow that
commercial advancements. digital communications provided could
revolutionize military operations, as it was
beginning to do with commerce. In an
attempt to explain the value that networks

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provide, early NCW advocates relied on Current Analysis of Battlespace Data
a rather simple theorem called Metcalfe’s Between 1965 and 1972 the U.S. flew
Law.11
871 unsuccessful sorties against the Thanh
Figure 1: Metcalf’s Law. The value of the network increases exponentially with the number of Hoa Bridge in Vietnam; only after the
additional nodes (N2). introduction later that year of laser-guided
bombs was the bridge destroyed.14 Other
Metcalfe’s Law states that the value of conflicts, such as the first Gulf War and
a network increases exponentially with the Bosnia in the 1990s, showed that destroying
increase in the number of interconnected the target is no longer the imperative to
nodes. The simplicity of the theorem allows military success—finding the right target
for only limited network discussions, as is what is paramount. Battlespace data is
many of the theorem’s shortcomings are now the most important component in
immediately obvious. First, the value of defeating an enemy, and the first step in
some nodes is inherently greater than developing a theory for the next evolution
others, especially nodes that provide greater of military sensing is observing the way
information. For example, in a missile early the military uses data in the battlespace.
warning network composed of land- and In its simplest form, data is used to locate,
ship-based radar, the weaker ship-based identify, and track the enemy.
radar may be of less value in terms of total
detection capability. Additionally, the smaller An intuitive characteristic of
the network, the more valuable the addition intelligence is that, at each level of war, the
of another node is to the overall power of fidelity of intelligence becomes more acute.
the network. In very large networks, like For example, at the strategic level, large
the type represented by the interconnected number of troop movements at a border
users on Facebook, it is difficult to believe would be significant, whereas the location
that the addition of one more user represents and timing of individual vehicles along the
an exponential increase in the value of the border would simply confound the analysis.
website. Additional theories have attempted At the same time, at the tactical level of war,
to augment Metcalfe’s, such as Zelf’s Law, the location and vector of individual vehicles
which states the value of each additional is of paramount importance. Throughout
node in the network is less than the previous the levels of war, intelligence analysis
node.12 But with all its shortcomings, purposefully gravitates toward aggregation.
Metcalfe’s Law remains germane to network At each progressively higher level (e.g.,
discussions due primarily to its simplicity from squadron to wing to numbered air
(it is still used today to discuss large force to joint air operations centers) analysts
interconnected environments such as the attempt to parse lower-level reports to get
Bitcoin phenomenon).13 a consolidated picture of the operating
environment.

In reviewing the uses of data in the
battlespace, it is also useful to note the
inherently predictive nature of intelligence.
Intelligence analysts not only describe the
battlespace, but attempt to predict enemy
capability, intent, and future actions. In
many ways, these functions are similar to
the scientific method in terms of producing

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conclusions or causality. Social scientists The Sensor Saturation Theory of
have rightly pointed out that making such Battlespace Data
assessments and reaching such conclusions
“cannot be reduced either to strictly logical The underlying assumption necessary
inference (deduction) or to empirical for a new theory of battlespace data
generalization (induction). Scientific inference collection is that existing or near-future
is not only about applying formal logic; it also technologies will revolutionize battlespace
involves reasoning, creativity, the ability to sensing. Specifically, these transformational
abstract, and theoretical language in order to technologies include the aforementioned 5G
see meanings and structures in the seemingly networking that, when you apply Moore’s
unambiguous and flat empirical reality.”15 The Law, enables the continued decline of cost
point here is that data from the battlespace is and size of advanced electronic sensors
used to make statements about reality. These and communication equipment, general
statements are essentially an inference from advances in data processing and storage, and
a perceived or real sample of the population the realization of advanced data analytics,
of interest, the battlespace. including artificial intelligence and machine-
learning. The confluence of these technologies
Currently, making battlespace inferences should allow for a massive network of small
is complicated by a flood of data. With the and inexpensive low-power sensors with
explosion of available sensor technologies, a range of collection abilities including
analysts are faced with an inability to use electro-optical, sonic, and thermal. These
all the data they collect.16 In this way, the sensors could be emplaced or air-dropped
signal begins to become the noise—a view by the thousands into an operation and
shared and espoused by “the father of could supplement the ever-expanding list
information theory” Claude Shannon, who of networked sensor sources including
first introduced theories of using raw data collection platforms, drones, and humans.
to represent actual information at MIT’s
Lincoln Laboratory. The more dire problem By effectively saturating the operational
is that analysts are forced to try to decide environment with sensors, we can produce a
which sensors provide them data that is the blanket of data collection. Because this data
most valuable, and what information is most collection will approach a more complete
useful. They decide which supporting data is picture of the conflict zone, analysts and
necessary to make predictions. In effect, they operators will no longer search for the
are predicting what supporting data they need enemy as much as remove benign data. In
to make predictions. In this way, battlespace other words, instead of searching for the
intelligence becomes a system of probabilities glint of the needle in the haystack, analysts
in series and makes for an ever-destabilized will simply remove the hay. In effect,
intelligence cycle. battlespace collection becomes the inverse
of present-day collection methods that
Here is where the future of battlespace look for abnormalities to reveal themselves,
networking gets interesting. The solution to relying more on analysis and correlations to
this deluge of data may not be better, more a “baseline” of the battlespace.
powerful sensors, nor the ability select the
most appropriate and accurate sensors at a Impact on Prediction
given time and place. The solution to too The application of this theory has two
many sensors may be more sensors.
major ramifications. First, rather obviously,
is that this sensor saturation will both

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reduce the necessity for and increase the spirits,” or the human emotional factor in the
accuracy of battlespace predication. It stands trading of stock prices.17 Additionally, other
to reason that with greater knowledge of the unavailable information contributes to stock
battlespace, the location and description of price movements: unpredictable industry
nefarious actors will be easier to discern. expansions, regulatory decisions, and natural
Additionally, any knowledge gaps will disasters, for example. Generally, however,
be more readily filled with bolstered the greater amount of specific information
predictions. This new network will increase influencing a stock sector (e.g., corn crop
our certainty of known enemies and help yield), the greater probability of success.
predict enemy actions.
Now, let us compare the military data
In discussing the validity of the problem to that of stock price fluctuation.
predictive value of more sensors, it is useful In the absence of more complex political-
to compare battlespace prediction with an military issues, the central objective function
equally valued arena of prediction such of military data collection is to identify and
as the stock market. In financial markets, locate specific entities across the battlespace–a
both data and analysts are legion. In the very specific objective with a well-defined end
models used for the stock market, the goal state, similar to stock picking. Yet, unlike the
is to predict price movements of stocks large number of stock information inputs,
or indices. In this regard, the objective the sensor inputs more directly contribute
function for stock prediction (the future to the objective. These sensors discover the
stock price) is explicitly well-defined. identity and location of the target at a specific
Knowledge is power and more information time. In the absence of battlespace deception,
is usually better, but large amounts of data detection and identification of a target are the
have not allowed anyone to predict stock primary considerations in the objective of the
price movements with any regularity. Stock data collection.
picking remains a “random walk.” Why?
The bottom line of this reasoning is
First, the inputs (or sensors) of stock that if financial analysts have been unable
picking are not all-inclusively telling of to predict stock prices given the amount
the objective function. In other words, the of information, analysis, and raw resources
sensor inputs do not directly predict price available, then how will militaries be able
movements. The specific inputs also do to predict enemy actions, movements, or
not account for the additional inputs of intents? Given enough sensors and the proper
market fluctuation. Let’s take the price of “infostructure,” battlespace intelligence will
corn futures, for example. Sensor inputs transform from a system that detects sensor
to the price of corn futures could include inputs to one that detects environmental
imagery on the condition of local and global abnormalities, develops useful correlations
corn fields, as well as applicable weather in the data, and provides a holistic analysis
predictions. Given the basic principle of of the operating environment.
supply and demand, if total knowledge was The Value of Individual Sensors in the
known about the future global corn-crop Network
yield, and the total future demand for corn,
analysts could still not completely determine The U.S. military seemingly has a
the future price. Perhaps the most influential surplus of battlespace data such that the
reason for this predictive shortcoming is inclusion of more data may mean more
what John Maynard Keynes called “animal distraction, creating more of a detriment

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to the intelligence community. In Claude the entire system increases exponentially,
Shannon terms of communication theory, as predicted by Metcalfe. Yet, as we reach
the amount of information transferred the fidelity of modern televisions with
is reduced by an increase in the data and effectively thousands of pixels, the value of
a corresponding increase in the noise of each individual pixel is reduced. In terms
the system. As Henrik Jeldtoft Jensen, a of discerning the actual picture, the value
professor of mathematical physics states: of one of these pixels effectively goes to
zero—one pixel barely contributes to the
Understanding the behaviour overall picture.
of a complex system necessitates
a simultaneous understanding of Likewise, in extremely large
the environment of the system. battlespace data collection networks, the
In model studies, one assumes value of the average individual sensor
often that the surroundings can approaches zero. In these types of networks,
be represented by one or the the “message internals,” or the actual data
other type of “noise,” but this that the average sensor is transmitting, is
is just a trick that allows one to of ever-decreasing value. Conversely, the
proceed with the analysis without “message externals,” or those parts of the
understanding the full system message that describe the message itself
under consideration. It is very such as date, time, and location of sensor,
important to appreciate that the become more important. The network
“drive” or the “noise” are equally becomes Boolean, with each sensor simply
crucial to the understanding, as is on or off (detecting or idle).
the analysis of the “system” itself.18
What this sensor saturation theory
So if the system itself begins to describes for future battlespace sensing is a
become the noise, then the information in television picture with thousands of pixels
the system is reduced, and so is the value of (sensors). Each of these sensors is simply on
the network. or off—transmitting message externals—at
a given time. It is the activation pattern of
At this point, it is necessary to focus these sensors that allow for detection—by
on the addendum to Metcalfe’s Law called removing the hay to find the needle—or
Zelf’s Law, also known as the “long tail” predictive analysis. The predictive analysis
theory of the value of the lower-tiered on these thousands of data points is similar
contributors to the network. Zelf’s Law to the big data analysis that Amazon.
posits that each additional node on a com does on its customers. By discerning
network decreases in relative value.19 In patterns and correlations in their data,
terms of the battlespace sensor mosaic, Amazon can predict when and what type
an analogy for Zelf’s Law is the television of product their customers will need, often
pixel. In the extreme case of a one-pixel before the customer knows what they
network, that one pixel would be extremely need.20
valuable, perhaps indicating on or off, day
or night. As we add pixels to this imaginary In figure 2, the power and the value
battlespace TV, each additional pixel helps of each node closely follows Metcalfe’s law
describe and form the picture. The value of during the early growth of the network. As
the network becomes more saturated with
sensors, the value of each sensor begins
to decrease. The power also stagnates due

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Figure 2. The contribution
of individual sensors to
the overall intelligence
collection network.

to the burden on the overall intelligence bonus of less overall actual bits transmitted
collection network created by the ever- per sensor. The military will no longer rely
greater number of sensors. Then, at the on complex data from individual sensors,
inflection point—marked by the asterisk— rather the large sensor network completes
we see another exponential leap in the power the picture of the battlespace like the many
of the network as sensor count reaches full pixels of a television.
saturation. This is the theoretical point
where there are so many sensors covering Second, artificial intelligence should be
such a density of the battlespace that the able to refine network results and contribute
analysis precludes sensor internals in favor to overall intelligence gathering. Artificial
of sensor externals. Concurrently, at a intelligence (AI) can better optimize the
certain point, the value of each individual extremely large networks of the future by
sensor approaches zero. manipulating connections to an otherwise
unmanageable number of sensor inputs and
Discussion maximize efficiency and collection. Although
5G networking technology could less important in future networks because
message externals are extremely simple, AI
enable a torrent of new battlespace can also smooth data melding by recognizing
capabilities. First, 5G inherently produces different forms of data and converting them
more coordinated and succinct data. to useful information. Lastly, it will be able to
Something very interesting happens make predictions based on big data analysis
when theorizing a message externals-only of the network data.
network. One of the fundamental data
fusion problems, configuring the data to As previously mentioned, aggregated
be compatible across a network, becomes battlespace intelligence is composed of data
less formidable as 5G networking uses a from lower echelons, with the finest data
standardized protocol (IP).21 Additionally, comprising the “bit” of intelligence. Until
the data that comprise the message externals now, militaries have lacked complete fidelity
are minute compared to the internals. Thus, across the battlespace, relying instead on
this future network may have the added consolidating spikes of intelligence. Analysts
evaluate each data source relative to other

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sources of information. Militaries have failed provide a counterintuitive solution to the
to approach intelligence collection in terms growing problem of wasted intelligence
of the absolute aggregate: in other words, data collection. By flooding the battlespace
having near-complete intelligence. Having a with sensors, the network is strengthened
more detailed picture of the battlespace will although each individual sensor is devalued;
require intelligence entities to change their the message externals become more valuable
perspective from seeking items of interest than the internals. With these emerging
(e.g., persons of interest, enemy vehicles, technologies, analysts will approach data
nefarious patterns of life) to monitoring the holistically, reducing the need for analysts
entire environment and effectively removing to rely on intelligence spikes in the operating
the impertinent data. In other words, environment.
instead of looking for the enemy needle in
a haystack, we are removing the hay, leaving Moving ahead, the problem is twofold.
only the bad actors. This is essentially the First, the military will very likely lag
inverse of the way we approach intelligence behind the commercial sector in developing
today. sufficient “infostructure” to take advantage
of massive sensor data, including shortfalls
Lastly, and most obviously, militaries in data storage and AI computational
must develop new combat networks that power. Second, military organizations lack
emphasize mobility. 5G cell towers are much necessary and sufficient theories on large
smaller than previous generations and should data, AI learning, and prediction models.
allow for vehicles, robots, and humans The military and intelligence communities
in the battlespace to carry small, mobile can begin remedying the later problem today
repeater stations.22 Militaries will need to by accelerating testing and acceptance of
develop capabilities and tactics, techniques, universal models. Doing so will ultimately
and procedures to mitigate the inability of allow proper and efficient expenditure of the
millimeter wave frequencies to penetrate national defense budget.
walls and other structures. The development
of combat employment of 5G capabilities Much like in civilian markets, the
should be ongoing and open to new insights earlier the U.S. military prepares for and acts
as more and more capabilities are fielded and on this networking eventuality, the greater its
saturation becomes ubiquitous. future advantages over its rivals. Success will
require a holistic approach focused not only
Conclusion on acquisitions and research and
Up to this point it has been unnecessary, development, but also systemic changes,
including those in doctrine, organization,
and possibly ridiculous, to speak in terms and tactics. An underlying theory of data
of data collection and analysis in terms collection and analysis that accounts for
of a complete mosaic of data covering the future technologies will guide the
entire battlespace. The current and future development of the next evolution in NCW.
technological advances of 5G networking may
necessitate re-looking current philosophies
on battlespace intelligence. Thousands of
miniature interconnected sensors could
provide new fidelity on the targeting cycle.
Additionally, this large network may

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Endnotes 10 Claude Elwood Shannon, “A Mathematical Theory of
Communication,” Bell System Technical Journal 27,
1 Gordon Lubold and Warren P. Strobel, “Secret U.S. no. 3, 1948.
Missile Aims to Kill Only Terrorists, Not Nearby
Civilians,” The Wall Street Journal, May 9, 2019. 11 Alberts, Garstka, and Stein, Network Centric
Warfare.
2 David S. Alberts, John J. Garstka, and Frederick
P. Stein, Network Centric Warfare: Developing and 12 Bob Briscoe, Andrew Odlyzko, and Benjamin Tilly,
Leveraging Information Superiority, 2nd edition “Metcalfe’s Law Is Wrong,” IEEE Spectrum, July 1,
(Washington, DC: DOD, C4ISR Cooperative 2006.
Research Program, February 2000).
13 Spencer Wheatley et al., “Are Bitcoin Bubbles
3 Clay Wilson, Network Centric Operations: Background Predictable? Combining a Generalized Metcalfe’s
and Oversight Issues for Congress (Washington, DC: Law and the LPPLS Model,” SSRN Electronic
Congressional Research Service, 2007). Journal, March 2018.

4 Loren Thompson, “5 Reasons the Army’s New 14 David A. Deptula and Douglas A. Birkey, Resolving
Battlefield Networking Strategy Won’t Work,” America’s Defense Strategy-Resource Mismatch: The
Forbes, November 20, 2017. Case for Cost-Per-Effect Analysis (Arlington, VA:
Mitchell Institute, 2020).
5 Vincent W.S. Wong, Robert Schober, Derrick Wing
Kwan Ng, and Li-Chun Wang, eds., Key Technologies 15 Berth Danermark, Mats Ekstrom, and Liselotte
for 5G Wireless Systems (Cambridge, UK: Cambridge Jakobsen, Explaining Society: An Introduction to
University Press, 2017); and David A. Deptula, Critical Realism in the Social Sciences (New York:
Evolving Technologies and Warfare in the 21st Century: Routledge, 2005), 113.
Introducing the “Combat Cloud” (Arlington, VA:
Mitchell Institute, 2016). 16 Isaac Porche et al., Data Flood: Helping the Navy
Address the Rising Tide of Sensor Information (Santa
6 Stoyan Nihtianov and Antonio Luque, Smart Monica, CA: Rand Corporation, 2014).
Sensors and MEMS: Intelligent Sensing Devices and
Microsystems for Industrial Applications (Cambridge, 17 John Maynard Keynes, The General Theory of
UK: Woodhead Publishing, 2018). Employment, Interest, and Money (San Diego, CA:
Houghton Mifflin Harcourt, 1964).
7 Amélia Ramos, Tiago Varum, and João Matos,
“Compact Multilayer Yagi-Uda Based Antenna for 18 James Moffat, Complexity Theory and Network Centric
IoT/5G Sensors,” Sensors 18, no. 9, 2018. Warfare (Darby, PA: DIANE Publishing, 2010), xiii.

8 Yoshiaki Taniguchi, Tomoya Kitani, and Kenji 19 Briscoe, Odlyzko, and Tilly, “Metcalfe’s Law Is
Leibnitz, “A Uniform Airdrop Deployment Method Wrong.”
for Large-Scale Wireless Sensor Networks,”
International Journal of Sensor Networks 9, no. 3–4, 20 Thomas H. Davenport, “Competing on Analytics,”
2011. Harvard Business Review 84, no. 1, 2006.

9 Ali Kashif Bashir et al., “An Optimal Multitier 21 Martin Liggins II, David Hall, and James Llinas,
Resource Allocation of Cloud RAN in 5G Using Handbook of Multisensor Data Fusion: Theory and
Machine Learning,” Transactions on Emerging Practice, Second Edition (Boca Raton, FL: CRC
Telecommunications Technologies, May 2019. Press, 2017).

22 Allan Holmes, “5G Cell Service Is Coming. Who
Decides Where It Goes?” The New York Times,
March 2, 2018.

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About The Mitchell Institute About the Author

The Mitchell Institute educates the general public about Anthony Tingle is a retired U.S. Army Lieutenant Colonel,
aerospace power’s contribution to America’s global interests, formerly the Concepts Evaluation Branch Chief at U.S. Army
informs policy and budget deliberations, and cultivates the Space and Missile Defense Command. He holds a PhD in
next generation of thought leaders to exploit the advantages public policy form George Mason University, an M.Eng and
of operating in air, space, and cyberspace. an MBA from the University of Colorado, Colorado Springs,
and a B.S. in systems engineering from West Point. He writes
Forum Submissions and Downloads on research, development, and the application of technology
within the Department of Defense. The views expressed are
For more information about submitting papers or ideas to the those of the author and do not reflect the official policy or
Forum, or for media inquiries, email our publications team at position of the Department of Defense or the U.S. Government.
[email protected]

Copies of Forum papers can be downloaded under the
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https://www.mitchellaerospacepower.org

Mitchell Forum 11