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Spectrum Sharing
[Insert early in the document]
Spectrum sharing amongst wireless systems is the root challenge of much of today’s
unlicensed or lightly licensed spectrum regulation.Devising techniques to be
successful in this environment under all conditions is challenging, because no one
user can directly influence the operation of other users; preemptive
communications are, by definition, infeasible. Therefore technologists and
regulators are challenged to derive technologies and set rules that allow both
equitable sharing of spectrum and maximization of spectrum efficiency.
Principles for shared spectrum operation are:
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Any guarantee of latency data bandwidth or coverage explicitly requires a
guarantee of spectrum.
Therefore, successful shared spectrum applications must tolerate variable
power,bandwidth or Duty Cycle resuting in variable latency,data
bandwidth or coverage.
Latency, data bandwidth or coverage may be traded for robustness.
Therefore, if low latency high data bandwidth or large coverage is required,
reliability will be degraded.
NOTE: Covered by section 2.4 and metrics section
[Insert in front of FH section]
Frequency Hopping technology provides equitable spectrum sharing, high spectrum
efficiency, robust performance in contended spectra, and are ‘friendly’ co-spectrum
users for applications and devices that occupy a single channel if particular
conditions, such as the abundance of LBT+AFA systems are met.
NOTE: ok but put in FHSS proposal
[Insert in front of Aloha/LDC section]
Unsynchronized transmissions from a device (e.g., those initiated without
synchronization withanother device) will ‘collide’ and presumably mutually disrupt
reception with a probability related to the combined channel access times of all
nodes. Realizing that even the slightest overlap of a packet can disrupt reception
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SPECTRUM SHARING – CRIB NOTES
the first improvement to truly ‘pure’ channel access is to ‘slot’ the timings of the
transmissions so that the transmissions either miss each other entirely or overlap
completely. The maximum channel throughput in these scenarios is shown in
Figure 1 – Throughput in ALOHA channels1
Figure 1 - Throughput in ALOHA channels
While the maximum capacity of the contended channel in pure ALOHA is just 17%
(slotted ALOHA doubles this to ~34%) this is acceptable for many applications and
these protocols are widely used where synchronization is difficult or the applied
traffic load is of low duty cycle (LDC).
NOTE: Diagram unreadable similar text already in the report, do not include.
[Insert in head of LBT section]
In some cases an improvement over the blind transmissions of the ALOHA protocol
is to simply listen before talking (LBT). In LBT, the device checks to see if the
channel is occupied prior to transmitting. If there is another signal on the channel it
may make sense to delay transmission until it is complete. This certainly is the case
when an immediate reply is expected – for it would collide with the existing signal.
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From Kleinrock and Tobagi : Packet switching in Radio Channels. - 1975
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LBT is especially useful in implementations where all devices can ‘hear’ each other
e.g. Ethernet or WiFior as mentioned, may be adopted by a device to ‘best choose
the time to transmit’ based upon what it can receive.
By randomly delaying a transmission after sensing a clear channel a very large
number of co-spectrum devices may be accommodated and channel throughput can
approach an idealized 100% for scenarios where all devices hear each other.Here the
devices are trading delay for channel efficiency.
Figure 22 illustrates the beneficial effects on channel capacity as each device
voluntarily decreases its duty cycle by lowering its own probability of transmission.
This is another case where simple LDC increases channel efficiency – at the cost of
higher individual latency. In latency tolerant applications – e.g. sensor data
collection, persistent alarms, etc. – this is proven spectrum contention mitigation.
Figure 2 - Channel throughput in p-persistent CSMA
In many other situations, particularly complex real-world scenarios, LBT can easily
reduce channel spectral efficiency by unnecessarily preventing applications from
working. This occurs when co-spectrum devices cannot ‘hear’ each other. One may be
transmitting and not be heard – but the ensuing transmission collides with the
unheard transmission at the intended recipient of the original transmission. Both
transmissions are lost.
2also
from Kleinrock and Tobagi : Packet switching in Radio Channels. - 1975
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SPECTRUM SHARING – CRIB NOTES
NOTE: Covered by hidden nodes. Consider to include missing parts in the hidden
node annes if needed. Diagram unreadable and no math explanation
[Insert in tail of LBT section]
Disadvantages of LBT
1) LBT precludes a class of devices that could co-exist quite well with more able bidirectional devicesfrom available and useable spectrum: Transmit-only devices.
2) LBT rewards (in fact, encourages) ‘poor’ receivers; “If I do not hear the onchannel energy, I can transmit.” Worse, if the sensitivity of a deployed receiver
suffers, that node will transmit excessively (because it hears nothing on channel)
while simultaneously being a poorly receiving neighbor. This is one positive
feedback mechanism that drives LBT SRDs toward worse performance.
This is correct but fully covered by setting a LBT threshold as discussed in the
hidden node section
3) LBT does not explicitly throttle the duty cycle of active and knowledgeable
nodes; this creates a ‘winner takes all’ situation where the node that most
recently transmitted can exploit its information about the channel to access it
preferentially (and unfairly) as compared to others without this current
information.
This is correct but covered by the LDC discussion of defining DC patterns instead
of a DC figure
This effect is especially deleterious to power challenged (battery and energy
scavenging) devices whose receiver is ‘off’ for large percentages of the time. When
these devices ‘come up’ and listen for channel access, they are at the mercy of
statistical luck. The active node, on the other hand, knows exactly when the channel
was last occupied and can perfectly time its next transmission. LBT rules will allow
this node to ‘legally’ dominate the channel.
Note that in this simplistic case it is not spectrum efficiency that suffers, it is
egalitarian access. Viewed from the perspective of the battery-operated device, LBT
rules advantage continuously powered devices unfairly.
4) LBT also causes spectrum inefficiency when it stops transmission preemptively
when they would succeed without interfering with any others. This is the classic
‘exposed terminal’ problem and cannot be ignored because any scenario will
have far more interferers within range than possible communicative candidates.
5) LBT also fails in the reverse scenario, which we will call the ‘airport scenario’ –
illustrated in the next figure. Spectral efficiency suffers because the energy
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threshold for LBT hold off does not consider how micro-cellularization3 (the true
driver of spectral efficiency) can allow substantial frequency reuse at received
energy levels far in excess of LBT thresholds in regulations today.
The following figure illustrates this more clearly than words alone. In this
scenario the airport (which could be any business) ‘floods’ the terminal space
with WiFi energy in the shared spectrum from multiple Access Points (APs).
This raises the noise floor to (say) -80dBm throughout the terminal space. WiFi
users have a receiver BW matching the transmitted BW of 20MHz and thus
operate well within the area of coverage.
WiFi
coverage
WiFi AP
WiFi user
D
headset user
C
##
headset user
B
headset user
A
Transiting within the terminal are numerous wireless headset users – say Bluetooth.
Each has a low-powered headset  handset combination that is streaming audio
information. Note that the interference radius of the wireless headset for ‘headset
3Cellularization and microcellularization (and femtocellularization) are the true drivers of spectral
efficiency and have been for the last several decades. One can see that for a given area, the smaller
the cell-size (or, more appropriately, the moreright sized it is for the application and its users) the
higher the spectral re-use and thus areal spectral efficiency. The true societal figure of merit is closer
to:kbps/kHz/km2/k£.
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SPECTRUM SHARING – CRIB NOTES
use A’ is small. It is a low powered device that is not particularly optimized for
range; it only must reach the handset that is likely carried on or very near the user.
As things operate today, all will be fine. The sheer proximity of the headset to the
handset provides signals that are locally very loud. These headset-handset signals
will drown out the undesired WiFi signal; the headset works. Note that the range of
this very local very low power signal is such that it does not interfere with other
users. This is spectral re-use at its best; no user is shut down unnecessarily and all
are successfully sharing the spectrum.
On the other hand, both the headset and handset have good receivers. If operating
by LBT rules, they must have a good receiver. This receiver will receive the cospectrum WiFi signal within the intended area of coverage of the WiFi unit. It may
be received weakly4 but headset user A is within the coverage area of the WiFi AP so
the signal will be strong enough to silence the LBT headset or handset. The headset
does NOT work.
Note headset Users B and C. We have all experienced the case where two headset
users walk into close proximity of each other while both are using wireless
headsets. Clearly they are well within the ‘interference radius’ of each other. In fact,
they are well within the communication radii. Yet both headsets continue to
operate. This is because the headset  handset communication uses Frequency
Hopping Spread Spectrum technology where each of these low-power transceivers
changes its channel of operation at a rapid rate so that the channels it uses are not
synchronized with other links. Headset user B does neither hears nor interferes with
headset user C.
As a last note on this figure, WiFi user D – as well as the WiFi AP itself - is unaware
of these myriad co-spectrum users. The several co-spectrum headset-handset users
impacted her in no way. The spectrum was re-used seamlessly leading to very high
spectral efficiency. This massive spectral efficiency would be lost in the LBT case –
all handset-headset users would be continuously interrupted and forced to wait for
a gap in the WiFi communication – a gap that might never come.
Many (all ?) of these remarks are covered in the hidden node discussion, do not
write additional text on this in different places in the document.
[Insert into section on Adaptive Frequency Agility]
In many cases when a system detects unacceptable performance degradation it can
choose a channel with less contention and move. Note that what is considered
unacceptable performance degradation will vary from application to application and
4For the purposes of discussion this could be -90dBm – six orders of magnitude below one microwatt
but still above the EN 300 200 LBT criteria.
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from instance to instance and may include latency, failed transmissions or
unpredictability.
The process is often simply that the ‘controller’ of the group of communicating
devices checks other available channels for traffic and then commands its attached
devices to move. This technique is used in several protocols and has the advantage
that it may be implemented ‘at the app layer’ – requiring no sophisticated timing.
Naturally this is only useful if only a subset of the devices on the crowded channel
move; if they all moved they would just be taking the unacceptable contention to
another channel.
Note further that a practical danger of this technique if that if half the devices move
to another channel, contention would be halved, but contact with the departing
devices would be lost.
NOTE: Its very specific to assume a controller, in most afa applications there is no
controller. Controlled systems may create a distributed hidden node situation. You
reallydon’t want to start a discussion on this therefore don’t include this text.