POWER CONTROL IN MC CDMA

Power control comprises the technique and algorithm used to manage and

adjust the b.ananitter power of base station and hand sets. Power conhi d u c a

cochannel interference, manages voice quality, maximizes cell capacity and

minimizes handset mean transmit power. As the channel path loss varia due to

mob~le station movement, the mobile station's and base station's traffic channels

transmitted power must be changed accordingly in order to ensure that the rtceived

s~gnal strength is equal to the receiver's sensit~vity. If the transmitted power IS not

~ncreased with an increase in path loss, the received signal power will fall below

receiver sensitivity, degrading quality of service (QoS). Conversely if the trwsm~ned

power is not decreased with a decrease In path loss, the received signal power will

exceed the receiver sensitivity, there by creating excessive interfcrencc that limits

system capacity. The drawback in the latter case as applicable to the reverse llnk is

that the excessive current is dmned from the mobile station battery and decreases the

talk-tune. Therefore accurate power control is necessary to guarantee, that the

received signal strength is not less and not more than the receiver sensitivity. In the

operation of CDMA system power control is crucial, since

1) In CDMA all users share the same radio spectrum and in cellular mobile

environment users move with random velocity in random directions. If all the

usen are allowed to transmit at the same power, mobile station (MS) near the

base station (BS) will saturate the amplifiers in BS and will introduce

distortion Apart from this the strength of the signal received from far end MS

will be very weak and will be masked by near end MS. This is referred to 8s

near far effect This problem can be eliminated by proper powa control.

ii) In CDMA, users are distinguished by their unique coda, which are normally

orthogonal in nature. In cellular mobile environment there is every possibility

that tbe orthogonality will be lost due to the random movement of the mobile

&ations. Therefore users will be interfering one another and particularly MS

near to the BS will be a potential source of interference. To be more specific

weak MS, i.e MS at a far away distance will be affected worse by this

interference. This problem can also be resolved by going for a proper power

control.

iii) Capacity of CDMA system is generally interference limited. As power

control reduces interference and BER, capacity increment can be achieved.

4.2 POWER CONTROL IN IS-95 CDMA

Mobile stations at different geographical locations in a cell site cannot

transmit with equal power to base station, as loss is different for different paths. Path

loss variations can be categorized in to long term variations and short term variations.

Long term variations are due to the changes in the distance between the mobile and

base station and shadowing while short term variations are caused by fast fading. This

differentiation motivates the use of two distinct types of reverse link power control

mechanisms: the open loop and the closed loop power control. The two loops operate

concurrently, and their effect is compounded to determine the mobile station transmit

power adjustments. The open loop component is the reciprocal part of the long-term

channel path loss, while the closed loop component is the adjustment necessary to

account for fast fading and open loop inaccuracy. Also base station cannot transmit

with the same power to the mobile station since in FDD environment uplinks and

downlinks are not identical. Therefore, IS-95 (Interim standard) incorporates both

reverse link and forward link power control.

4.2.1 Reverse Link Power Control

Power control on the reverse link adjusts the transmitter power of each mobile

station, such that nominal received power from each MS at the BS is the same [I].

Power to be transmitted h m the MS is decided based on the signal to interference

and noise ratio (SM) required to maintain the required f m e error rate (FER). If the

transmitted power is larger than that required to maintain the target FER unnecessary

interfaewe will be there which will reduce the capacity. Conversely if the power is

m l e r than the minimum required, QoS is degraded and the call may be dropped. In

IS-95, logical 1 bit is transmitted to indicate that the received power is greater than the

target power, while a logical 0 bit signifies the power is less than the target power.

The MS adjust its transmitted power according to the dictates of the command bit

with a fixed increment/dment power. In IS-95 command bit sent at the rate of 800

bps alters transmitted power by It1 dB.

4.2.2 Forward Link Power Control

Forward link power control is similar in nature to its reverse link counterpart,

although the implementations are quite different. Equivalent to the reverse link,

forward link power control adjusts the base station code channel transmitted power to

achieve the target SINR at the mobile station receiver. Forward link power control

consists of an open loop and a closed loop. Forward link open loop functionality is

implemented at the base station, while closed loop functionality is implemented at the

mobile station.

4.3 SIR BASED REVERSE LINK POWER CONTROL

The major disadvantage of IS-95 power control scheme is the algorithm is not

dynamic and efficient power control is not possible, which leads to poor capacity

enhancement [164]. Since E a , of each user is measured by single user receiver, the

decision taken for power control based on this may not be matching well at all

circumstances. So a dynamic and effective power control algorithm for MC CDMA

system is proposed in this section. The first major modification in the proposed power

control algorithm is that, instead of measuring E a 0 of every user using single user

receiver, E&, is measured for the entire user through a typical correlator similar to

parallel interference cancellation. The major drawback of parallel type of interference

canceller is, that the user with least power will suffer. But since this is incorporated

with perfect power control scheme, the problem of PIC will be eliminated. Hence at

the outset signal to interference ratio (SIR) of the entire user is obtained accurately at

a quicker time. The second major modification of the proposed scheme is in the

method used in indicating the error to the mobile station. Base station calculates SIR

needed to achieve the target FERBER based on the modulation scheme used

considering class of service and compares with the measured SIR. BS calculates the

difference in SIR and will indicate to the MS, power to be increasedtdecreased in

terms of k l to k4 dB, every 625 p. Since the correction signal is indicated to the MS

through 3 bits instead of 1 bit (IS-95), 8 different power correction options

(+-l,f 2, f 3 and k 4dB) and quicker convergence is possible. Since the proposed

algorithm utilizes a better error measuring technique and a faster error correcting

technique, better reduction in interference and better improvement in capacity when

compared with IS-95 CDMA is achieved. Apart from this to cater to the needs of

multimedia service to be offered in the third generation, proposed algorithm permits

to fix different targets for different services. Figure 4.1 gives the flow chart of the

algorithm used.

4.3.1 Performance of Single Sewice Users

A simulation is performed using MATLAB with channel similar to that of the

one described in section 2.4.The power control algorithm is implemented in the line

of flowchart given in Figure 4.1 and the performance evaluated. For comparison

purpose, performance of the MC CDMA system without power control is also

simulated. A simple cell environment is considered with 5 users. Users 1,2 and 3 are

static and at different radial distance from the base station, with user 1 at the nearest

point from the base station. User 4 and user 5 are considered to be moving users, with

both users 4 and 5 at a radial distance greater than that of user 1 to 3. User 4 is

assumed to move away kom base station and user 5 moves towards base station, and

it is also assumed both users 4 and 5 are moving with constant average velocity. The

SIR of all the usen as observed by the base station for a period of 5 minutes is

indicated in Figure 4.2. It can be inferred, user 1 is received at highest SIR by the base

station followed by users 2 and 3. Also it is inferred the SIR of user 4 continuously

decrease and SIR of user 5 continuously increase as expected. Figure 4.3 depicts the

BER of the five users for the same 5 minutes, without power control. As expected

user 1, 2 and 3 will have their BER in the increasing order, BER of user 4 and 5 will

continuously vary and particularly user 4 will have BER continuously increasing, and

the user may get his link detached due to the poor performance.

Received signal from all the mobile stations

Compute the d i f fmce Compute the d i f f m c e

I

Select a value +1 dB, +2dB,+3dBor+4dB

Fig.4.1 Flow chart of the proposed algorithm

Figure 4.4 illustrates the BER of all the five users after implementing

proposed power control algorithm. It can be observed that all the five users have their

BER restricted to the target value. Important point to be observed is, mobile station is

instructed to transmit power which is just required to maintain the required QoS.

Hence, ultimately the interference level in the air, particularly contributed by the near

end user will be reduced to a greater extent. Hence, apart from ensuring target BER

for the entire user the algorithm will reduce interference and serve to enhance the

capacity to a greater extent. To further explore the performance of the proposed

algorithm, same cell environment is considered with 5 users moving in random radial

positions at random velocity in random directions. The SIR of all the users as

observed by the base station for a period of 5 minutes is indicated in Figure 4.5. It

should be noted that all the users are received at random SIR by the base station.

Figure 4.6 displays the BER of all the five users for the same 5 minutes, without

power control. As expected all the users will be having their BER randomly varying,

far away users will have a degraded performance whereas the near by user will

introduce more interference in air. Figure 4.7 depicts the BER of the entire five users

with power control algorithm implemented. Again, all the users BER is kept intact.

This simulation is performed to test the influence of user's mobility on the

performance of the proposed algorithm. Results indicate that the algorithm

dynamically controls the power, wherever the user is.

4.3.2 Performance of Multi Service Users

Future generation wireless senices will be of multimedia in nature, therefore

the proposed algorithm is modified in order to provide different target SIR required

for different services and the performance is evaluated. The same environment is

again used with 9 users, users 1 to 3, 4 to 6 and 7 to 9 belongs to different senice

category. Figure 4.8 explains the SIR of all users for a period of 5 minutes, again

random movement is considered. Figures 4.9 and 4.10 illustrate the BER of all the

users without and with power control respectively. Here, it is noted that there are three

target BER and users 1 to 3, 4 to 6 and 7 to 9 settles at different BER. This result

indicates that the algorithm fulfils the requirement of multi service environment also.

Fig.4.2 Power level of static and dynamic users

Fig.4.3 Performance without power control

56

Fig.4.4 Performance with power control

Fig.4.5 Power level of random users

Fig.4.6 Performance of random users without power control

Fig.4.7 Performaace of random users with power control

Fig.4.8 Power level of multi service users

Fig.4.9 Performance of multi service users without power control

Fig. 4.10 Performance of multi service uwn: with power control

4.4 QoS BASED SUBCARRIER AND POWER ALLOCATION

Hushang Li and H.V.Poor have opened a new avenue for spectral efficiency of

rnulti rate DS-CDMA in which they proposed power allocation instead of power

control [165]. In 1998 S.Sun et al has proposed optimal fonvard link power allocation

for data transmission in CDMA systems [166]. Subsequently R.Vannithamby el a1

11671 has proposed an optimal ratelpower allocation scheme for hybrid

CDMA/TDMA cellular system. Xiang Duan et al [168] has further studied the

transmit power minimization in power controlled multimedia systems. Ln 1999

P.Viswanath et al [I691 and later ti Gao et al (1701 have analyzed on the influence of

optimal sequences, power control on capacity of synchronous CDMA systems.

C.Y.Wong has proposed an adaptive subcanier, bit and power allocation scheme for

mldticanier OFDM [171]. In 2000 W.Rhee et a1 has analyzed on increase in capecity

of multi canier OFDM through dynamic sub channel allocation 11721 and

Jiho Jang et al has developed [I731 a hansnit powa adaptation method that

maximizes the total dab rate of multi user OFDM in a downlink in two steps:

subcarrier assignment for wrs and power allocation for subcarriers. F i p 4.1 1

depicts the block diagram of a typical MC CDMA system with the proposed powa

control and subcarrim allocation algorithm. A simple cell environment, with k user is

considered. In the transmitter section the data symbols of all the usen are spread&

using orthogonal variable spreading factor (OVSF) code. Subcanier allocation

algorithm and power control algorithm is incorporated in the transminu, using

channel condition as a feedback brn the receiver section. Proposed algorithm selects

the optimal set of subcaniers, performs power control kn selected sub set of

subcarriers and transmits the information in the selected power controlled subcarrier

through a multi path Rayleigh fading channel in AWGN floor.

4.4.1 Subcamer Allocation

In a cellutar FDD mobile environment, it is well known that there will he less

correlation between forward and reverse link of a channel, linking a transmitter and

receiver [174]. This being the state of fact, it is clear, that all the subcarners may not

be good for the links used by all the users in a single cell site. It should also be

understood that, one subcarrier which happens to be worst for one user may be the

best for some other user. In fact, it is quite unlikely that a subcanier will be in deep

fade for all users, as the fading parameters for different users are mutually

independent. Since testing and allotting each and every subcarrier (SC) is normally a

time consuming process, subcaniers will be grouped into different subxts, for

example 16 subcarriers can be grouped into 4 subsets, with all the SC in a subset

experiencing same type of fading. SC allocation algorithm just wlects the best subset

of subcarrier that can be used for that user at that instant.

4.4.2 QoS Bawd Power Control

To reduce the further interference in the air, power transmined in the used

subwriers can also be reduced. To implement this, for every user a target SIR is

h v e d based on the senice offered and modulation scheme used. Target powa in

subcrariers y, and r,, are fixed to keep the SIR within a tolerance of * 0.5 dB.

Power control algorithm implemented ensuns all the subcamas an

m i n e d with a power betwear y, and y,, which is the power just required to

meet the QoS of that particular user. Figure 4.12 gives the flow chart of MC CDMA

system with subcarrier allocation and power control algorithni.

Start I

Check chpnnel cond~hons for each

response on sam subfamer sets

Csc SIR > y,, )"I Etc h

aF'Propnatc --c

Go to start

Fig.4.12 Flow chart of SCA and PC rlgoritbrn

63

4.43 Perfonnrnw with QoS Bawl Subcarrkr and Power AUocatioa

To check the performance of the proposed algorithm, simulation is performed

using MATLAB with the channel similar to that of the one described in section 2.4

and the proposed algorithm is simulated based on the flowchart given in Figure 4.12.

Simulation parameters are 16-32 users, 641 16 number of subcarriers. 1614 subcamers

per set, DPSK modulation scheme in Rayleigh fading channel.

in Figure 4.13 the performance of a simple 64 subcarrier MC CDMA system

is shown. AS expected, as the value of SNR increases, BER decreases. Figure 4.14

illustrates the performance of a subcamer allocation algorithm, where the 32

subcaniers which are most suited for that particular user is selected, based on pmpcr

channel estimation. Information for that user is Iransmittcd through the selected

subcarriers and error rate is calculated. Simulation results imply good error rate 1s

obtained with half the number of subcamers (32 instead of 64). It 1s quite obvious

from the result that the performance of 64 subcarriers MC CDMA is achievcd with

just 32 good subcarriers and the remaining 32 subcarriers can be used for some other

users for whom that subcamer set will be good. Hence, ultimately better channel

utility or better capacity can be realized due to the implementat~on of subcarrier

allocation algorithm.

Figure 4.1 5 is the simulated error performance with one subset (i.e. I6 sc) with

100% power, one subset with 80% power, remaining two subsets with O?h power

decided based on the channel conditions i.e, the BER is for both power and subcarrier

allocation algorithm. This result indicates that a better error performance than just

subcarrier allocation is obtained.

The comparison of error performance of MC CDMA, MC CDMA with SCA

and MC CDMA with SCA and power control algorithm are depicted in Figure 4.16.

From this figure it is concluded that MC CDMA with SCA and PC algorithm seems

to be better, since optimum error rate is obtained with comparatively lesser number of

subcarriers. Also it should be noted that since in a power controlled SCA scheme, as

the power transmitted is not 100% in the used 32 subcarriers, the intcrfmnce in much

less.

Fig.4.13 Performance of 64 SC MC CDMA system

k 4 . 1 4 Pedormance of 64 SC MC CDMA system with subcarrier allocation

lo"

E

10'

-

& - --- '--+-zkI;<,

:

nr', i i t i i 2 ; 4 l i f l 8 W t m e

Fig.4.15 Performance of 64 SC MC CDMA with SCA and power control

Fig.4.16 Comparison of MC CDMA SCA and MC CDMA SCA & PC (64)

66

Figures 4.17, 4.18 end 4.19 an for the same type of schemcs as discussed

above but with 16 subcanien. Figure 4.17 is the BER perform~cc for 16 carrier MC

CDMA scheme. Comparison of Rgures 4.13 and 4.17 indicates performance of 64 c

carrier MC CDMA is better due to the more number of subcarrier used.

Figure 4.18 is the performance of the 16 SC MC CDMA scheme with SCA

algorithm only and figure 4.19 is the performance of the 16 SC MC CDMA schcnw

with SCA and PC algorithm. Figures 4.18 and 4.19 are similar to Figurrs 4.14 and

4.15 and hence confirms with the previous inferences. Agure 4.20 is h e comparison

graph for 16 SC MC CDMA. MC CDMA with SCA and MC CDMA with SCA nnd

PC algorithm. Figure 4.20 again confirms the conclusion anived b w d on the

Figure 4.16.

Fig.4.17 Perfomnee ot 16 SC MC CDMA system

Fig.4.18 Performance of 16 SC MC CDMA system with subcarrier elloation

W n d

Fig.4.19 Performance of 16 SC MC CDMA with SCA and PC

Fig.4.20 Comparison of MC CDMA SCA and MC CDMA SCA & PC (161

45 CONCLUSION

In this chapter. MC CDMA transmission in a muld user environment is

considered. Power transmitted by the mobile station is optimized by the proposed SIR

based reverse link power control algorithm. This algorithm ensures the overall

optimization of the power vansmined by the mobile station by adaptively assigning

power to the users based on the target SIR and service offered. Rrther it is proved

that the proposed algorithm is accurate and dynamic. The power transmitted by the

base station is also optimized through the proposed subcanier allocation and power

control algorithm. In this algorithm subcarriers are grouped into subsets and SClCCled

subsets are power controlled and allocated to the user based on the channel condition.

These algorithms reduce interference in air both in uplink and downlink and hence

increase the capacity to a tune of about 30%.