Subject: [NEXTEL-1] Re: [WFHSG] RE: Consensus Plan aka "SCAM PLAN"

From: [email-masked]
Date: Fri, 13 Feb 2004 17:17:54 -0500

see my comments below-

"Buchanan, David" wrote:

> I can understand disagreement over the best way to solve this but to be
> constructive it should be conducted more professionally than is set our
> below in the reply.  Appendix F has a good definition of interference.  The
> public safety community that negotiated Appendix F,  did not define it as
> "any degradation to any receiver is the fault of the
> Transmitter" .   There are reasonable signal levels the public safety system
> must meet to be protected and require any of the cellular providers to
> correct if it should occur after re-banding.  Alan is quite correct in his
> statements.

What happened to the BER measurement reference that Berine proposed for Appendix
"F" several months ago? Is there another revision I missed? This was a step in
the right direction.  Using analog measurement techniques in a digital world is
one problem with appendix "F".

++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++

 Including BER% measured values .

If the system is digital, both (C+I+N) RSSI and BER% can simultaneously be
captured.  This then provides addition data as to what the median C/(I+N) really
is.  This is more complex.  Different receivers of the same model and
manufacturer may have slightly different characteristics.

The static BER% of the test receiver can be measured using normal test
equipment.  The difference between the static C/N and faded C/N for the
necessary faded BER% can be used.  For example, if the 5% static BER is -120 dBm
and the 2% static BER% is 2.2 dB higher (-117.8 dBm) then the C/N for 2% static
BER is 2.2 dB greater than the value in TSB88A, Table A-1.  If the modulation is
C4FM that would be 7.6 dB + 2.2 dB = 9.8 dB.  The value of faded 2% BER is 17.7
dB, 7.9 dB above the static value.  Thus the C for 17.7 dB requires a desired of
-117.8 dBm + 7.9 = -109.9 dBm.

If the criterion is a 20 dB C/(I+N) The 1% faded BER can be used for C4FM.

The process of determining if 1% BER can be achieved in the local area will
determine if the desired C/(I+N) is being achieved.

This test provides a better understanding of the interference mechanism.  If
(C+I+N) is large, but the BER% increases, the (I+N) component is increasing.

++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++

>
>
> At the risk of inflaming some on this list serve, I must say the virulent
> opposition to the "Consensus Plan"  including the constant reference to
> Scam Plan"  does not help the debate or the Public Safety community to solve
> this issue.

Nextel's Plan is a "SCAM"

Nextel is the primary cause of Public Safety interference and their self serving
solution is a joke. It's like if someone robbed a bank and then said they would
return the money for a reward. Allowing Nextel to benefit from problems THEY
have caused will not be Tolorated by the wireless industry. Public Safety has
fallen into the "Booby-Trap" and of course the industry is going to "React".
The "Industry" will tie the "Scam Plan" up in court for years and the
interference will continue.

Nextel and the FCC have been presented with various solutions from SouthernLinc
and others to resolve the interference WITHOUT REBANDING. The "SCAM PLAN" only
benefits Nextel, not Public Safety, Private Wireless or the public. The unproven
plan will not eliminate interference to  Public Safety as Nextel says. There has
been no proof submitted that rebanding will work.
What Nextel has not said is their new Software S.R. 11 now has specific
interference management tools to regulate BR power and other algorithms. This
solution has NOT been addresessed by the "Plan".

What we do know in the iDEN industry is that there are alternatives that do
work. that include but are not limited to:

   * Optimization
   * Forward Power Control
   * Diversity
   * Spatial Diversity
   * Interference rejection techniques
   * Adaptive equalization techniques
   * Antenna Management
   * Balanced Path

Here is the supporting documentation:

------------------------------------------------------------------------
On Interference Rejection in Wireless
Multichannel Systems
Goran Klang
2003
TRITA{S3{SB{0328
ISSN 1103{8039
ISRN KTH/SB/R - - 03/28 - - SE
Signal Processing
Department of Signals, Sensors and Systems
Royal Institute of Technology
Stockholm, Sweden

"combinations of diversity and interference rejection techniques are usually
considered to make a
receiver robust against interference.  Whereas diversity methods aim at
optimizing the reception of
the desired user's signal, interference rejection techniques incorporate known
or assumed
characteristics of the interference into the optimization."

<SNIP>

Interference Rejection

In most cellular systems the service and capacity demands are far from
uniformly distributed. Neither over the geographical service area nor in
time. To match such local variations, cellular network architectures employing
cells with di_erent reuse distances, coverage areas, and number
of assigned physical channels per cell are often used in practice. From
a downlink communication perspective, i.e., in communication scenarios
where signals are conveyed from a network access point to a mobile
terminal, this poses no problem as long as the physical channel reuse
distances are su_ciently large since the level of cochannel interference in
the di_erent cells will then be low, cf. Figure 1.1a. For the uplink case
however, i.e., communication from a mobile terminal to a network access
point, the situation is di_erent. As mobiles on the rim of large cells must
transmit with high output power in order to be detected by their assigned
1.2 Interference Rejection 5
c) d) b) a)

Figure 1.1: Examples of interference scenarios in cellular systems. a) Downlink
communication with sparse
physical channel reuse: no or small cochannel interference problems. b) Uplink
communication in small cell
close to large cell, c) downlink communication with dense physical channel
reuse, d) uplink communication
with dense physical channel reuse: severe cochannel interference problems may
occur.  network receivers,
network receivers operating in small cells close to large cells may experience
severe cochannel interference,
cf. Figure 1.1b. Similar, considering short physical channel reuse distances,
strong interference may occur in
both links as the coverage areas of di_erent cells using the same set of
physical channels may partly or in the
worst case scenarios even completely overlap, cf. Figure 1.1c{d. Thus, in order
to achieve both e_cient
spectrum utilization and avoid local capacity shortages due to the emergence of
cochannel interference e.g., in
scenarios as the one discussed above, it is of fundamental importance that the
generation of interference from
the transmitters is minimized but even more important that the receivers are
inherently robust to interference.

1.2.1 Interference Rejection Techniques

Much of the original interest in interference rejection and the use of
techniques for mitigating the impact of
interference has its roots in military applications. Primarily to protect
signals of interest from being intentionally
or unintentionally jammed, but also to _nd e_ective methods 6 1 Introduction to
achieve jamming. However,
concurrent with the rapid growth seen in mobile communications that has lead to
capacity problems in many
networks, the interest for using interference rejection techniques in
nonmilitary applications has gradually
increased.

Di_erent combinations of diversity and interference rejection techniques are
usually considered to make a
receiver robust against interference.  Whereas diversity methods aim at
optimizing the reception of the desired
user's signal, interference rejection techniques incorporate known or assumed
characteristics of the
interference into the optimization. Although it is often of subordinate
importance what type of diversity that is
exploited from an interference rejection point-of-view, in the literature,
interference rejection algorithms are often
classi_ed according to whether they exploit spatial diversity at the receiver or
not. That is, whether the
algorithm is a single or multi-antenna technique.  Interference rejection
techniques for single antenna receivers
have for practical reasons attracted much attention in the literature. Although
optimal detection in the presence
of cochannel interferers in general requires joint multiuser detection [Van76,
Ver86, Wal95], many suboptimal
detectors based on interference rejection have been proposed as a response to
the fact that many receivers
lack both su_cient information and computational complexity in order to
implement an optimal detector. In for
example [NV91, NAZ93, PF94, LFS95, YFS97] di_erent adaptive equalization
techniques are discussed for
handling both adjacent as well as cochannel interference. For signals having
constant modulus and signals
with known envelope, examples of adaptive _lters trying to achieve interference
rejection by restoring the
envelope of the signal can be found in [TA83, TL85b, TL85a, MRHA91, FTT97,
JSE+98].  A third approach is to
consider neural networks based _lters [Hay96].  In [CM92, CK92, Arn93, HSD97,
XLY01] the use of radial
basis function networks are addressed and in [Bi92, SS94] feed-forward networks
with back propagation are
considered. Techniques exploiting periodic structures in the signals, such as
cyclostationarity, are discussed
e.g., in [RH90, Gar93, RYH95].

For additional references, the interested reader is referred to e.g. [LR97].
Due to the trends toward less expensive hardware and communication
using wavelengths in the order of centimeters rather than meters, the use
of multi-antenna receivers has become increasingly popular during the
last decade as a viable approach to achieve diversity in many practical
applications. Not only in the network access points of a system but also in
the terminals. Using multiple sensors, linear combinations can be formed
1.3 Parameter Estimation 7

by the receiver to help improve the estimate of the signal transmitted.  An
operation known as spatial _ltering
or beamforming [MM80, VB88, KV96, God97, Win98, Tso99, BO01, Tre02]. In contrast
to the use of only one
receive antenna, having access to observations collected in the spatial domain,
both spatial and
spatio-temporal processing approaches can be considered to improve the
interference robustness of a receiver.
Depending on the known or assumed characteristics and properties of the
interfering signals many di_erent
detection schemes have been proposed.  In [ME86, VPPF94, BJ95, KH96, DP97,
Kar98, MB98] the
cochannel signals are modeled as temporally white but spatially correlated
Gaussian noise in order to arrive at
a maximum likelihood sequence estimator (MLSE) [Pro95] for the signal of
interest. The Gaussian assumption
is also considered in [Slo96, LCP97, AO98b, AO98a, Ast99, BMC99] to take the
presence of both spatial and
temporal correlations in the cochannel interference into account.

As a complement to the use of diversity at the receivers, exploiting spatial
diversity at the transmitters
combined with coding| commonly referred to as transmit diversity|has been
proposed as a viable method to
help improve the performance of receivers operating in fading environments
[Wit91, SW93, TSC98, Ala98,
TJC99]. However, in considering transmit diversity schemes based on space-time
codes [TSC98, Ala98,
TJC99], new dimensions to the interference rejection problem are added. Since
transmitters employing
space-time codes periodically transmit temporally correlated sequences in
parallel to providing diversity at the
receivers, cochannel interference observed from such transmitters will typically
be cyclostationary. A fact that,
if not taken into account, may severely degrade the performance of conventional
interference rejection methods
[KO03]. Di_erent approaches to handle cochannel interference due to space-time
block codes may be found in
e.g.,[NS99, NSC00, KN00, LSL02, LLC02].

Parameter Estimation

(Optimize, Optimize, Optimize, Interferemce away)

Signal processing algorithms in general and interference rejection algorithms
in particular are inherently model based. A fundamental problem
of many applications is however that the exact parameter values of these
models will not be a priori available. Instead they need to be estimated
prior to applying the signal processing algorithm. To handle this problem,
most wireless communication systems have known training data period-
ically inserted into the transmission protocol to support synchronization
and parameter estimation. As the throughput over a given communication
link is often _x, in practice, the number of training symbols sent at
each occasion is usually determined by a tradeo_ between the minimum
required estimate accuracy and the maximum acceptable level of system
overhead.

For receivers to be robust against interference, they need accurate
models describing the fundamental characteristics of the interfering signal.
As the characteristics of the physical propagation channel and the
interference scenario may change, the available models need to be continuously
re-estimated. Hence, the receivers ability to support e_cient
spectrum utilization in a wireless system will in practice strongly depend
on the accuracy of their di_erent signal and model parameter estimates.
To maximize spectrum e_ciency and minimize system overhead, it is
thus of major importance that the estimators providing these estimates
are e_cient in their use of the available training data. That is, that the
estimators take advantage of all known structures present in the underlying
physical problem in order to improve the accuracy of the estimates.
Estimators designed to meet this requirement are usually refereed to as
structured estimators.

1.3.1 Blind Parameter Estimation Techniques

For interference rejection purposes, having access to models describing
the propagation channels of the interfering users is often very useful. Despite
the fact that most cochannel interference in cellular networks is
generated by transmitters incorporating training data into their transmission
protocols, as it is often too complicated to keep all receivers
in a network updated about the training sequences used by all active
transmitters, the receivers must in general resort to blind or semi-blind
parameter estimation techniques to gain this information.
Blind parameter estimation amounts to retrieving parameter estimates
from the outputs of a system where no explicit knowledge
about the system input data is available. For channel identi_cation,
this was _rst shown possible by Sato [Sat75] taking advantage of the
fact that communication signals are in fact highly structured. In
the early era of blind channel identi_cation, use of high-order statistics
was frequently considered to identify non-minimum phase systems
[Sat75, God80, TA83, BG84, SW90, Men91]. A major drawback working
with high-order statistic based estimators is their slow convergence rate.

1.4 Outline and Contributions 9

Often very large sets of output data must be available to obtain accurate
estimates. Under time varying conditions this fact limits the usefulness
of these high-order statistics based estimators and implies that to ensure
fast convergence, only estimators working with second order statistics
or _nite alphabet properties are suitable from a practical point-of-view.
Unfortunately, considering a single-input single-output (SISO) system, it
can be veri_ed that unique identi_cation of the channel is impossible
considering
only the second order statistics of the output data. However, as
was _rst discovered and exploited by Tong et al. in [TXK91, TXK93] and
later by several other researchers (for example [MDCM95]), by transforming
the SISO system into a single-input multiple-output (SIMO) system
considering for example temporal oversampling, it can be shown that
unique identi_cation up to a complex scalar multiplication of the channels
is indeed possible studying only the second order statistics of the
observed data. For thorough discussions on blind estimation, the interested
reader is referred to the overviews given in [LXTK96, TP98] and
the references therein.

In contrast to the standard blind parameter identi_cation problem
addressed in the references above, using blind parameter estimation techniques
in a receiver to extract information about interfering users, a complicating
factor exist. That is, the desired user's signal will act as interference
while estimating the parameters of the interfering users. In this
thesis, a semi-blind parameter estimation approach is suggested where
the known training data of the desired user is taken into account to handle
this problem.

http://www.lib.kth.se/Fulltext/KLANG030613.PDF

===============================================================================================

Motorola even acknowledges that interference can be reduced through manipulation
of various algorithms.

From Motorola:

<SNIP>
"During co-channel interference
conditions where the desired and
interfering BR signals are subject to log-normal
fading such that the subscriber is
periodically locking into the
interfering BR, the iDEN subscriber is
not discarding sync timing infor- mation
from the BR with the incorrect color
code.

Instead, the subscriber changes its timing reference to the interfering BR.
When this occurs the desired BR attempts to correct any timing errors. The
cor-rections, however, are not received by the subscriber since it is locked
onto the interfering signal. This can lead to rapid increases in the time
correction value. Consequently, when the log-normal fade sub- sides, the
subscriber's time correction is erroneous.
=========================================================================================

Reducing interference between the MS and the BR allows the carrier to use LESS
power for the same area of coverage thereby reducing the chances for OOBE and
Adjacent channel interference.

I asked this before and everyone disappeared .......

Q: What percentage of Nextel interference is OOBE?

Nextel claims to know more about interference than Motorola the company who
created their iDEN system. The only thing Nextel has EVER created was
INTERFERENCE.

> If you have what you believe is a better way to permanently

> solve this issue then set it out on the list serve but please quit bashing
> honest efforts to explain the consensus plan.

I have been since 1999-

The explanation is one sided and does not fully address the alternatives

>  One last point the consensus
> plan did not just spring forth from Nextel and blindly accepted by those of
> us in public safety who looked at it.  There were some very tough back and
> forth negotiations.  Nextel had to concede several points before we in
> public safety could except the plan.  We made major changes to the plan to
> improve it.  As to Appendix F - that was very difficult to reach agreement
> and it was modified many times before submission to the FCC.  It has been
> modified to improve it after the original filing.

But it still has serious problems and the court battle will just frustrate
Public Safety and Nextel will eventually walk away (see: Nextwave  v. Nextel)

Marcel-

---

From: "gwweimer3" <[email-masked]>
Date: Tue, 17 Feb 2004 03:24:45 -0000

--- In [email-masked], Marcelrf@B... wrote:

> What happened to the BER measurement reference that Berine proposed 
for Appendix "F" several months ago? Is there another revision I 
missed? This was a step in the right direction.  Using analog 
measurement techniques in a digital world is one problem with 
appendix "F".

Nothing happened to the BER approach BERNIE proposed. It was 
the "Consensus" of the people drafting Appendix F that the exact 
measurement protocol should be included in a Revised Best Practices 
guide as recommended in the appendix. The exact protocol will be 
developed by the TIA/EIA workgroup and will probably be similar to 
that developed by Bernie (which is very good). The approach will also 
include measurements in the analog mode since a large majority of the 
current system are analog. Using digital techniques in an analog 
P.S./SMR system is a problem also, especially when the receiver 
experiencing interference is analog or at least operating in analog 
mode due to its infrastructure.
George

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From: [email-masked]
Date: Mon, 16 Feb 2004 23:03:48 -0500

See bellow

gwweimer3 wrote:

> current system are analog.

I saw the TIA submission- I thought he proposed both scenarios.

> Using digital techniques in an analog

True, but since the majority of the interference is Digital on Analog it would
be a useful criteria.
More and more P/S systems are transitioning to Digital and Appendix F should
address future past concerns. With the Federal mandate driving transition for
the Feds, Public Safety will soon follow as more and more agencies deploy mixed
networks (FED/Local).

When iDEN experiences interference issues we normally see a High RSSI and a low
SQE.
Using RSSI alone is useless. I bet P-25 has a similar scenario.

Marcel-

P.S. Thanks for the reply-

> George

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