# A simple generalization of the CDMA reverse link pole capacity formula

TL;DR: A formula that computes the maximum number of users supported per base station in a cellular radio network is generalized to consider the frequency reuse number and arbitrary processing gains to quantify a cost associated with in-cell interference.

Abstract: A formula that computes the maximum number of users supported per base station in a cellular radio network is generalized to consider the frequency reuse number and arbitrary processing gains. The generalization quantifies a cost associated with in-cell interference by accounting for the lack of interference from the desired user on the total interference and by considering the impact of the frequency reuse number on the out-of-cell interference. This interference cost results in an increase in the received Eb/Io relative to FDMA which should be weighted against a reduction in the Eb/Io requirement resulting from using CDMA.

## Summary (2 min read)

Jump to: [I. INTRODUCTION] – [II. SPREADING WITH IN-CELL INTERFERENCE] – [III. SPREADING WITHOUT IN-CELL INTERFERENCE] and [IV. CONCLUDING REMARKS]

### I. INTRODUCTION

- The more calls that can be supported by a base station at an acceptable quality, the less base stations that are needed to support a given subscriber demand.
- A formula from [1] is sometimes used to estimate the maximum number of users supported by each base station.
- Such a condition establishes a maximum on the number of users supported for a given QoS objective and in theory a pole exists in the transmit power required to meet the QoS.
- An assumption is commonly made in deriving various forms of this formula (e.g., [1] - [4] ) that the number of interfering users in the serving cell creating in-cell interference (ICI) power is the same as the number of users in each of the other base stations that create (OCI) out-of-cell interference power.
- Such an assumption counts the desired signal as interference which becomes increasingly significant for lower processing gains.

### II. SPREADING WITH IN-CELL INTERFERENCE

- Consider an idealized hexagonal lattice of base stations where the number of users supported by each base station is increased uniformly throughout the network until the interference plus noise power is just at a level required to meet a given QoS objective.
- Tradeoffs arising from using different combinations of spreading, modulation, and coding for a fixed bandwidth and spectrum efficiency are recent areas of research (e.g., [5] - [8] ).
- Note that (5) includes no assumptions about power control or access technique.
- The interference limited form of ( 5) happens to also be the pole capacity since at the pole capacity noise becomes insignificant.

### III. SPREADING WITHOUT IN-CELL INTERFERENCE

- The following equation is a lower limit on (2) by considering only a single user per carrier in each base station as: (7) This is an FDMA limiting case when there is no reuse of the same channel within a base station.
- For nonunity spreading gains, can be increased at the cost of a reduction in the number of users supported by increasing the spreading gain.
- The spreading gain from ( 4) when (8) Substituting ( 8) into (7) gives the total number of users supported when spread spectrum is used with FDMA and a frequency reuse strategy prohibiting ICI as (9).
- The plot shows that ICI degrades the for CDMA.
- For an requirement of 7 dB, roughly 200 users are shown for CDMA with .

### IV. CONCLUDING REMARKS

- A formula that computes the number of users supported under peak load conditions was generalized and investigated under different spreading and interference conditions.
- This formula assumes an idealized hexagonal network of base stations, a uniform number of users in all base stations, and the same data rate requirement for all users.
- The influence of multiuser detection on these results for CDMA is an area further research.
- Benefits of spread spectrum resulting in a reduction of the requirement were not considered in the analysis but rather the costs associated with the received interference for a peak network load using uniform geographical assumptions.
- Spread spectrum and frequency reuse were considered jointly in this formulation as they both can significantly impact received interference and spectrum efficiency.

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IEEE TRANSACTIONS ON COMMUNICATIONS VOL. 49, NO. 10, OCTOBER 2001 1719

A Simple Generalization of the CDMA Reverse Link Pole Capacity Formula

Pete Boyer, Milica Stojanovic, and John Proakis

Abstract—A formula that computes the maximum number of

users supported per base station in a cellular radio network is gen-

eralizedtoconsiderthe frequencyreusenumberand arbitrarypro-

cessing gains. The generalization quantifies a cost associated with

in-cell interference by accounting for the lack of interference from

thedesired useron thetotal interferenceand byconsidering theim-

pact of the frequency reuse number on the out-of-cell interference.

This interference cost results in an increase in the received Eb/Io

relative to FDMA which should be weighted against a reduction in

the Eb/Io requirement resulting from using CDMA.

Index Terms—Discount, markup, template.

I. INTRODUCTION

T

HE EFFICIENT use of the RF spectrum serves as a fun-

damental design goal for cellular radio network engineers.

The more calls that can be supported by a base station at an ac-

ceptable quality, the less base stations that are needed to support

a given subscriber demand. Since there are large fixed capital

costs associated with base station deployment, it is desirable to

maximize the number of subscribers that each base station can

support.

A formula from [1] is sometimes used to estimate the max-

imum number of users supported by each base station. In [1],

the number of users per CDMA carrier is given as

(1)

where

RF spread bandwidth;

data rate;

signal-to-noise ratio (SNR) per bit;

rise above thermal;

frequency reuse efficiency.

This formula applies to CDMA networks such as IS-95 that

are noncooperative in the sense that they do not exploit interfer-

ence through multiuser detection. This formula has historically

been associated with CDMA networks when interference rises

Paper approved by Z. Kostic, the Editor for Wireless Communication of the

IEEE Communications Society. Manuscript received February 15, 2000; revised

September 12, 2000.

P. Boyer was with Verizon Laboratories, Waltham, MA 02254 USA. He is

now with Equilateral Technologies, Lexington, MA 02420 USA (e-mail: pete.

boyer@equilat.com).

M. Stojanovic was with the Department of Electrical and Computer Engi-

neering, Northeastern University, Boston, MA 02115 USA. She is now with the

Department of Aeronautics and Astronautics, Massachusetts Institute of Tech-

nology, Cambridge, MA 02139-4307 USA (e-mail: millitsa@mit.edu).

J. Proakis is with the Department of Electrical and Computer Engineering,

Northeastern University, Boston, MA 02115 USA (e-mail: proakis@neu.edu).

Publisher Item Identifier S 0090-6778(01)09099-7.

to a level where users cannot compensate for less than the de-

sired quality of service (QoS) by increasing their transmitted

power. Such a condition establishes a maximum on the number

of users supported for a givenQoS objective and in theory a pole

exists in the transmit power required to meet the QoS. The for-

mula solves for the number of users when all users at all base

stations are exactly at the required

needed to meet

a QoS objective such as a mean opinion score (MOS) or a frame

error rate (FER). This is a pole condition since any additional

user would create interference that could not be compensated

for through increases in the transmitted power.

An assumption is commonly made in deriving various forms

of thisformula(e.g.,[1]–[4])that the number of interfering users

in the serving cell creating in-cell interference (ICI) power is

the same as the number of users in each of the other base sta-

tions that create (OCI) out-of-cell interference power. Such an

assumption counts the desired signal as interference which be-

comes increasingly significant for lower processing gains. By

removing this assumption, the number of users for arbitrary pro-

cessing gains and frequency reuse numbers is found. The fol-

lowing generalization considers the impact of both allowing and

prohibiting ICI in cellular system design.

II. S

PREADING WITH IN-CELL INTERFERENCE

Consider an idealized hexagonal lattice of base stations where

the number of users supported by each base station is increased

uniformly throughout the network until the interference plus

noise power is just at a level required to meet a given QoS ob-

jective. At this point, the network ideally blocks additional calls

due to quality considerations. Blocking due to resource limita-

tions, a traditional blocking mechanism applying to any cellular

technology, is assumed to be insignificant.

A bit stream after source coding of

bits per second has

a bandwidth expansion due to channel coding with code rate,

, and a potential bandwidth change due to modulation with

a spectral efficiency of modulation,

, as shown in Fig. 1. A

spreading sequence of bandwidth

increases the bandwidth

before spreading,

, by a spreading gain, . The posi-

tive bandwidth of this signal at RF is doubled due to the shifting

of the spectrum. Tradeoffs arising from using different combi-

nations of spreading, modulation, and coding for a fixed band-

width and spectrum efficiency are recent areas of research (e.g.,

[5]–[8]). Exploring these tradeoffs requires the consideration of

not only the required

needed to meet a given QoS,

but also the effect that the bandwidth expansion/contraction has

on the received

when the number of users is held

constant. Themaximumnumberofusers supported occurs when

all of the users are exactly meeting the requirement since the ad-

dition of users beyond this maximum cannot be accomplished

0090–6778/01$10.00 © 2001 IEEE

1720 IEEE TRANSACTIONS ON COMMUNICATIONS VOL. 49, NO. 10, OCTOBER 2001

Fig. 1. System diagram and signal bandwidths for a generic communications link in a cellular network that employs direct sequence spread spectrum.

without degrading the received and correspond-

ingly the QoS.

The total number of users,

, in a given available bandwidth

at each base station is

(2)

where

number of users supported for each carrier at a base

station;

available bandwidth to the cellular operator;

frequency reuse number (or cluster size).

The number of users per carrier can be found by directly

writing the carrier-to-(interference plus noise) power ratio of

each user assuming that the interference is ideally spread and

despread as

Carrier Power

ICI OCI Noise Power

(3)

where

received carrier power of each user;

noise power in the despread signal bandwidth ;

total interference from one out-of-cell user in all of the

other cells normalized to the carrier power;

spreading gain;

reduction in interference due to the voice duty cycle.

The processing gain,

, defined by can differ from

the amount of bandwidth expansion resulting from direct se-

quence spreading, and thus arises the need for a spreading gain

term. Also, reverse link (mobile to base station) values for

with power control can be found for in [9]–[17] and for

in [16] and [17].

Equation (3) can be written in terms of

by

noting the carrier power in the numerator is

and the total

interference plus noise power in the despread bandwidth in the

denominator is

. Utilizing the bandwidth relation-

ship in Fig. 1 for

gives

(4)

Solving for

in (4) and substituting it into (2) gives

(5)

When (

) in the denominator of (3) is replaced by , the

second term in (5) goes away and (5) reduces to forms in [1],

[3], and [4] with

and

.

The rise above thermal is sometimes used to measure reverse

link load [4] with respect to the total number of users at a pole in

the carrier power when considering reverselink QoS with power

control. The pole capacity is the interference limited form of (5)

since at the pole, the

goes to infinity with the power. The

pole can be seen by equating (4) with the required

needed to meet the QoS objective, , and solving for

as

(6)

As the number of users per base station per carrier produces

interference that approaches the requirement, the received en-

ergy per bit goes to infinity. Setting the denominator of (6)

equal to zero, solving for

, and using (2) gives the interfer-

ence limited form of (5). Note that (5) includes no assumptions

about power control or access technique. It simply computes

the number of users supported as a function of the received

. The interference limited form of (5) happens

to also be the pole capacity since at the pole capacity noise be-

comes insignificant.

IEEE TRANSACTIONS ON COMMUNICATIONS, VOL. 49, NO. 10, OCTOBER 2001 1721

Fig. 2. Maximum number of users supported versus received

E =I

for the generalized pole capacity formula.

III. SPREADING WITHOUT IN-CELL INTERFERENCE

The following equation is a lower limit on (2) by considering

only a single user per carrier in each base station as:

(7)

This is an FDMA limiting case when there is no reuse of

the same channel within a base station. When

, the

spreading gain is unity and this lower limit is conventional cel-

lular FDMA with a frequency reuse number of

. For nonunity

spreading gains,

can be increased at the cost of

a reduction in the number of users supported by increasing the

spreading gain. The spreading gain from (4) when

is

(8)

Substituting (8) into (7) gives the total number of users sup-

ported when spread spectrum is used with FDMA and a fre-

quency reuse strategy prohibiting ICI as

(9)

At this limit, a value for

may require a different calculation

than with CDMA. The OCI will be due to a smaller number

of users making the interference that is averaged throughout a

cell less indicative of the actual interference. Additionally, a soft

handoversolution may become difficult to achieveor infeasible.

Various studies have computed

under a variety of conditions

in [9]–[17] with primary considerations being factors such as

shadowing margin, path loss slope, and the number of base sta-

tions in soft handover. Representative values for

are chosen

for the purpose of illustration.

The interference limited forms of (5) and (9) are plotted in

Fig. 2 for two frequency reuse numbers with

for

using the mean value from [9] and a value of for

from [17]. A value of 0.4 for the voice duty cycle is from

[3]. The spreading gain, code rate, and the spectrum efficiency

of modulation match that of IS-95 reverse link traffic channels

excluding orthogonal modulation. The available spectrum con-

sidered is that of an 800-MHz cellular operator deploying nine

CDMA carriers. The plot shows that ICI degrades the

for

CDMA. A hypothetical FDMA system with spread spectrum

and no ICI is plotted until the FDMA spreading gain is unity

giving conventional FDMA at two points that correspond to the

two frequency reuse numbers. For an

requirement of 7

dB, roughly 200 users are shown for CDMA with

. This

is in contrast to roughly 360 users for the nine carriers using

[3]. The difference is that the spreading gain used here is less

than the processing gain used by [3]. Since the value of

is the

same for FDMA and CDMA for each reuse number, the figure

shows a roughly 4-dB cost associated with the ICI relative to

using FDMA with

. The figure also indicates that there

would be a loss in

or a reduction in users if a channel as-

signment for a reuse number of 3 were used to reduce the OCI

for CDMA. For high

design objectives, the figure shows

1722 IEEE TRANSACTIONS ON COMMUNICATIONS VOL. 49, NO. 10, OCTOBER 2001

interference benefits of conventional cellular frequency assign-

ments for FDMA networks.

IV. C

ONCLUDING REMARKS

A formula that computes the number of users supported under

peak load conditions was generalized and investigated under

different spreading and interference conditions. This formula

assumes an idealized hexagonal network of base stations, a uni-

form number of users in all base stations, and the same data

rate requirement for all users. By considering an FDMA limit

without ICI, a fundamental cost of CDMA was observed due to

ICI. This cost should be offset by a reduction in the requirement

as a result of using CDMA. The influence of multiuser detection

on these results for CDMA is an area further research.

Frequency reuse through conventional frequency assignment

with CDMA was observed to result in less users for the same

. When spread spectrum is combined with FDMA to elim-

inate ICI, higher

, and lower spreading gains result for the

same number of users. Benefits of spread spectrum resulting in

a reduction of the

requirement were not considered in

the analysis but rather the costs associated with the received in-

terference for a peak network load using uniform geographical

assumptions. Spread spectrum and frequency reuse were con-

sidered jointly in this formulation as they both can significantly

impact receivedinterference and spectrum efficiency. The band-

width effects of channel coding, modulation, and spread spec-

trum were considered as they impact the interference received

by all users under peak network load conditions.

A

CKNOWLEDGMENT

The authors would like to thank A. Giordano for his support.

R

EFERENCES

[1] A. M. Viterbi and A. J. Viterbi, “Erlang capacity of a power controlled

CDMA system,” IEEE J. Select. Areas Commun., vol. 11, Aug. 1993.

[2] T. Rappaport, Wireless Communications Principles and Prac-

tice. Englewood Cliffs, NJ: Prentice-Hall, 1996.

[3] Qualcomm, “An overview of the application of code division multiple

access (CDMA) to digital cellular systems and personal cellular net-

works,” submission to TIA TR 45.5, Doc. #EX60-10 010, May 21, 1992.

[4] H. Xia, “CDMA system design and deployment,” in VTC ’98 Tutorial

Notes, Ottawa, ON, Canada, May 18–21, 1998.

[5] P. Malm and T. Maseng, “Optimum number of signal alternatives in mo-

bile cellular systems,” in Proc. PIMRC ’98, Boston, MA, Sept. 8–11,

1998.

[6] D. Nikolai, K. Kammeyer, and A. Dekorsky, “On the bit error behavior

of coded DS-CDMA with various modulation techniques,” in Proc.

PIMRC ’98, Boston, MA, Sept. 8–11, 1998.

[7] E. Biglieri, G. Caire, and G. Taricco, “Coding and modulation under

power constraints,” IEEE Commun. Mag., pp. 32–39, June 1998.

[8] A. Coreia and A. Cercas, “CDMA with multiuser detection vs. coding,”

in Proc. PIMRC ’98, Boston, MA, Sept. 8–11, 1998.

[9] K. Gilhousen et al., “On the capacity of a cellular CDMA system,” IEEE

Trans. Veh. Technol., vol. 40, pp. 303–312, May 1991.

[10] A. J. Viterbi, A. M. Viterbi, K. S. Gilhousen, and E. Zehavi, “Soft

handoff extends CDMA cell coverage and increases reverse link

capacity,” IEEE J. Select. Areas Commun., vol. 12, pp. 1281–1288,

Oct. 1994.

[11] A. Viterbi, “Other-cell interference in cellular power-controlled

CDMA,” IEEE Trans. Commun., vol. 42, pp. 1501–1504, Apr. 1994.

[12]

, CDMA Principles of Spread Spectrum Communica-

tion. Reading, MA: Addison-Wesley, 1995.

[13] D. Lee et al., “Other-cell interference with power control in macro/mi-

crocell CDMA networks,” in Proc. VTC ’96, 1996, pp. 1120–1124.

[14] K. Cheah and K. Li, “On the interference of surrounding cells in a

DS-CDMA system,” in Proc. IEEE Singapore Int. Conf. on Networks,

Singapore, July 1995, pp. 152–156.

[15] J. Wang and L. Milstein, “Approximate interference of a microcellular

spread spectrum system,” Electron. Lett., vol. 31, no. 20, pp. 1782–1783,

Sept. 1995.

[16] A. Rojas and J. Paradells, “Interference and capacity in CDMA hybrid

systems with hysteresis margin,” in Proc. PIMRC ’98, Boston, MA,

Sept. 8–11, 1998.

[17] A. Rojas, J. Gorricho, and J. Paradells, “Capacity comparison for

FH/FDMA, CDMA and FDMA/CDMA schemes,” in Proc. VTC ’98,

Ottawa, ON, Canada, May 18–21, 1998.

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##### References

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15 Jan 1996

TL;DR: WireWireless Communications: Principles and Practice, Second Edition is the definitive modern text for wireless communications technology and system design as discussed by the authors, which covers the fundamental issues impacting all wireless networks and reviews virtually every important new wireless standard and technological development, offering especially comprehensive coverage of the 3G systems and wireless local area networks (WLANs).

Abstract: From the Publisher:
The indispensable guide to wireless communicationsnow fully revised and updated!
Wireless Communications: Principles and Practice, Second Edition is the definitive modern text for wireless communications technology and system design. Building on his classic first edition, Theodore S. Rappaport covers the fundamental issues impacting all wireless networks and reviews virtually every important new wireless standard and technological development, offering especially comprehensive coverage of the 3G systems and wireless local area networks (WLANs) that will transform communications in the coming years. Rappaport illustrates each key concept with practical examples, thoroughly explained and solved step by step.
Coverage includes:
An overview of key wireless technologies: voice, data, cordless, paging, fixed and mobile broadband wireless systems, and beyond
Wireless system design fundamentals: channel assignment, handoffs, trunking efficiency, interference, frequency reuse, capacity planning, large-scale fading, and more
Path loss, small-scale fading, multipath, reflection, diffraction, scattering, shadowing, spatial-temporal channel modeling, and microcell/indoor propagation
Modulation, equalization, diversity, channel coding, and speech coding
New wireless LAN technologies: IEEE 802.11a/b, HIPERLAN, BRAN, and other alternatives
New 3G air interface standards, including W-CDMA, cdma2000, GPRS, UMTS, and EDGE
Bluetooth wearable computers, fixed wireless and Local Multipoint Distribution Service (LMDS), and other advanced technologies
Updated glossary of abbreviations and acronyms, and a thorolist of references
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### "A simple generalization of the CDMA..." refers background in this paper

...2 for two frequency reuse numbers with for using the mean value from [9] and a value of for from [17]....

[...]

...Various studies have computedunder a variety of conditions in [9]–[17] with primary considerations being factors such as shadowing margin, path loss slope, and the number of base stations in soft handover....

[...]

...Also, reverse link (mobile to base station) values for with power control can be found for in [9]–[17] and for in [16] and [17]....

[...]

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^{1}TL;DR: Generating Pseudorandom Signals (Pseudonoise) from PseudOrandom Sequences by Modulation and Demodulation of Spread Spectrum Signals in Multipath and Multiple Access Interference.

Abstract: 1. Introduction. Definition and Purpose. Basic Limitations of the Conventional Approach. Spread Spectrum Principles. Organization of the Book. 2. Random and Pseudorandom Signal Generation. Purpose. Pseudorandom Sequences. Maximal Length Linear Shift Register Sequences. Randomness Properties of MLSR Sequences. Conclusion. Generating Pseudorandom Signals (Pseudonoise) from Pseudorandom Sequences. First- and Second-Order Statistics of Demodulator Output in Multiple Access Interference. Statistics for QPSK Modulation by Pseudorandom Sequences. Examples. Bound for Bandlimited Spectrum. Error Probability for BPSK or QPSK with Constant Signals in Additive Gaussian Noise and Interference. Appendix 2A: Optimum Receiver Filter for Bandlimited Spectrum. 3. Synchronization of Pseudorandom Signals. Purpose. Acquisition of Pseudorandom Signal Timing. Hypothesis Testing for BPSK Spreading. Hypothesis Testing for QPSK Spreading. Effect of Frequency Error. Additional Degradation When N is Much Less Than One Period. Detection and False Alarm Probabilities. Fixed Signals in Gaussian Noise (L=1). Fixed Signals in Gaussian Noise with Postdetection Integration (L>1). Rayleigh Fading Signals (L>/=1). The Search Procedure and Acquisition Time. Single-Pass Serial Search (Simplified). Single-Pass Serial Search (Complete). Multiple Dwell Serial Search. Time Tracking of Pseudorandom Signals. Early-Late Gate Measurement Statistics. Time Tracking Loop. Carrier Synchronization. Appendix 3A: Likelihood Functions and Probability Expressions. Bayes and Neyman-Pearson Hypothesis Testing. Coherent Reception in Additive White Gaussian Noise. Noncoherent Reception in AWGN for Unfaded Signals. Noncoherent Reception of Multiple Independent Observations of Unfaded Signals in AWGN. Noncoherent Reception of Rayleigh-Faded Signals in AWGN. 4. Modulation and Demodulation of Spread Spectrum Signals in Multipath and Multiple Access Interference. Purpose. Chernoff and Battacharyya Bounds. Bounds for Gaussian Noise Channel. Chernoff Bound for Time-Synchronous Multiple Access Interference with BPSK Spreading. Chernoff Bound for Time-Synchronous Multiple Access Interference with QPSK Spreading. Improving the Chernoff Bound by a Factor of 2. Multipath Propagation: Signal Structure and Exploitation. Pilot-Aided Coherent Multipath Demodulation. Chernoff Bounds on Error Probability for Coherent Demodulation with Known Path Parameters. Rayleigh and Rician Fading Multipath Components. Noncoherent Reception. Quasi-optimum Noncoherent Multipath Reception for M-ary Orthogonal Modulation. Performance Bounds. Search Performance for Noncoherent Orthogonal M-ary Demodulators. Power Measurement and Control for Noncoherent Orthogonal M-ary Demodulators. Power Control Loop Performance. Power Control Implications. Appendix 4A: Chernoff Bound with Imperfect Parameter Estimates. 5. Coding and Interleaving. Purpose. Interleaving to Achieve Diversity. Forward Error Control Coding - Another Means to Exploit Redundancy. Convolutional Code Structure. Maximum Likelihood Decoder - Viterbi Algorithm. Generalization of the Preceding Example. Convolutional Code Performance Evaluation. Error Probability for Tailed-off Block. Bit Error Probability. Generalizations of Error Probability Computation. Catastrophic Codes. Generalization to Arbitrary Memoryless Channels - Coherent and Noncoherent. Error Bounds for Binary-Input, Output-Symmetric Channels with Integer Metrics. A Near-Optimal Class of Codes for Coherent Spread Spectrum Multiple Access. Implementation. Decoder Implementation. Generating Function and Performance. Performance Comparison and Applicability. Orthogonal Convolutional Codes for Noncoherent Demodulation of Rayleigh Fading Signals. Implementation. Performance for L-Path Rayleigh Fading. Conclusions and Caveats. Appendix 5A: Improved Bounds for Symmetric Memoryless Channels and the AWGN Channel. Appendix 5B: Upper Bound on Free Distance of Rate 1/n Convolutional Codes. 6. Capacity, Coverage, and Control of Spread Spectrum Multiple Access Networks. General. Reverse Link Power Control. Multiple Cell Pilot Tracking and Soft Handoff. Other-Cell Interference. Propagation Model. Single-Cell Reception - Hard Handoff. Soft Handoff Reception by the Better of the Two Nearest Cells. Soft Handoff Reception by the Best of Multiple Cells. Cell Coverage Issues with Hard and Soft Handoff. Hard Handoff. Soft Handoff. Erlang Capacity of Reverse Links. Erlang Capacity for Conventional Assigned-Slot Multiple Access. Spread Spectrum Multiple Access Outage - Single Cell and Perfect Power Control. Outage with Multiple-Cell Interference. Outage with Imperfect Power Control. An Approximate Explicit Formula for Capacity with Imperfect Power Control. Designing for Minimum Transmitted Power. Capacity Requirements for Initial Accesses. Erlang Capacity of Forward Links. Forward Link Power Allocation. Soft Handoff Impact on Forward Link. Orthogonal Signals for Same-Cell Users. Interference Reduction with Multisectored and Distributed Antennas. Interference Cancellation. Epilogue. References and Bibliography. Index.

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Qualcomm

^{1}TL;DR: This work presents an approach to the evaluation of the reverse link capacity of a code-division multiple access (CDMA) cellular voice system which employs power control and a variable rate vocoder based on voice activity.

Abstract: This work presents an approach to the evaluation of the reverse link capacity of a code-division multiple access (CDMA) cellular voice system which employs power control and a variable rate vocoder based on voice activity. It is shown that the Erlang capacity of CDMA is many times that of conventional analog systems and several times that of other digital multiple access systems. >

804 citations

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###### Q2. What have the authors stated for future works in "A simple generalization of the cdma reverse link pole capacity formula" ?

The influence of multiuser detection on these results for CDMA is an area further research.