# Reducing CQI Signalling Overhead in HSPA

Authors: Saied M. Abd El-atty; Dimitrios N. Skoutas; Angelos N. Rouskas
Journal: Research Letters in Communications
 (2008)

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## Abstract

The efficiency of adaptive modulation and coding (AMC) procedure in high speed Downlink packet access (HSDPA) depends on the frequency of the channel quality information (CQI) reports transmitted by the UE to Node B. The more frequent the reports are the more accurate the link adaptation procedure is. On the other hand, the frequent CQI reports increase uplink interference, reducing thus the signal reception quality at the uplink. In this study, we propose an improved CQI reporting scheme which aims to reduce the required CQI signaling by exploiting a CQI prediction method based on a finite-state Markov chain (FSMC) model of the wireless channel. The simulation results show that under a high downlink traffic load, the proposed scheme has a near-to-optimum performance while produces less interference compared to the respective periodic CQI scheme.


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## Body

## 1. Introduction

High-speed packet access (HSPA) aims to
advance the performance of the existing UMTS networks by improving the level of
quality of service (QoS) and increasing the supported peak data rates at both
the forward and the reverse link. HSPA consists of the HSDPA and high-speed
uplink packet access (HSUPA) standards.AMC procedure of HSDPA makes possible the
adaptation of the employed transport format and resource combination (TFRC) to
the wireless channel variations as well as to the varying rate requirements of
the UE. However, as the rate of the wireless channel variation increases, more frequent
CQI reports by the UE to Node B are needed in order to have an efficient AMC.
On the other hand, as the number of CQI reports increases, uplink interference
also increases, thus reducing uplink reception quality. The authors of [1–3] propose a number of CQI schemes which aim to keep
high the efficiency of AMC while at the same time reduce the required CQI
information. In this paper, we propose a new CQI reporting scheme which reduces
the required CQI signaling by exploiting a CQI prediction method based on an
FSMC model of the wireless channel.The remainder of the paper is organized as
follows: in Section2, we describe the CQI reporting procedure as it is
determined by 3GPP specifications and subsequently we discuss the CQI
interference problem at the uplink. The proposed prediction-based CQI
reporting scheme (P-CQI) is presented in Section 3. The employed packet scheduler is illustrated in
Section 4. Finally, in Section 5, we present and discuss the simulation results, while
Section 6 concludes our paper.


## 2. System Concepts and Problem Statement

### 2.1. System Concepts

The HSDPA operation utilizes a number of new channels [4].The user data are transmitted through the high-speed Downlink
shared channel (HS-DSCH) while the associated signaling is transmitted through
the high-speed shared control channel (HS-SCCH) at the forward link and at the
high-speed dedicated physical control channel (HS-DPCCH) in the uplink.The feedback information from the terminal
to the base station, carried on the HS-DPCCH, is essential for the HSDPA
operation as it makes possible the use of adaptive modulation and coding. The
HS-DPCCH frame consists of three slots and has duration of 2 milliseconds. The
first slot is used by the hybrid automatic repeat request (HARQ) process, while
the other two slots are used for the transmission of CQI. CQI is not a direct signal-to-interference and noise ratio (SINR) measurement but instead it is an integer
index to the TFRC which the UE requests from the packet scheduler located at Node B
[5].Given a typical target error rate of 10%,
the requested TFRC corresponds to the maximum transport block size which has a
minimum of 90% probability to be transmitted correctly. Two successive CQI
values correspond approximately to a step of 1 dB at the SINR of the HS-DSCH [4, 5].At Release 5, 3GPP [6] proposes a periodic-CQI feedback scheme which, as
illustrated at Figure 1(a), has a report cycle of rc. The possible values of rc are 0, 1, 5, 10, 20, 40, 80 sub-frames or
correspondingly 0, 2, 10, 20, 40, 80, 160 milliseconds. The enhanced-CQI reporting
(E-CQI) scheme described at release 6 [7]
extends Release 5 specifications by introducing
additional CQI reports during periods of downlink activity. As shown in Figure 1(b), the additional CQI reports are transmitted with
every packet acknowledgment (ACK) (and/or Non-ACK). The aim of the “enhanced-CQI
reporting” is to use longer report cycles compared to the periodic-CQI scheme
and increase the number of the CQI reports when it is needed (i.e., when the
downlink activity increases).Figure 1
CQI reporting schemes.


### 2.2. Problem Statement

It is obvious that
the shorter the report cycle is, the more advantageous for the AMC procedure of
HSDPA it is, as it provides
better adaptation to the variations of the wireless channel. However, at the
same time, the frequent CQI signaling increases uplink interference and thus
decreases the average UE throughput as well as the achievable
energy-per-bit
to noiseEb/I0 ratio at the reverse link. The
“enhanced-CQI reporting” scheme of [7]
is a step towards the right direction, however, it
will still perform as a periodic scheme in the case of CBR services such as
VoIP or even during the bursty periods of VBR services such as FTP.In this paper, we propose an improved CQI reporting scheme which aims to
reduce the required CQI signaling even when the downlink data activity is high
by employing a CQI prediction method. According to this
scheme, Node B predicts all the
intermediary CQI reports between two subsequent CQI
reports by utilizing an FSMC model of the wireless
channel. Thus, as shown in Figure1(c), in our proposed mechanism, a
number of CQI reports can be predicted instead of transmitted.The proposed prediction-based CQI reporting scheme (P-CQI) is based on
the optimum periodic-CQI feedback scheme [6]
which has the minimum reporting cycle of 2 milliseconds.
Therefore, every 2 milliseconds, a CQI report is either transmitted by the UE or
predicted at Node B. By increasing the number of intermediary CQI predictions,
the actual reporting cycle is increased and consequently CQI transmissions are
decreased. Thus, by employing P-CQI, a significant interference reduction in
the uplink can be achieved.Adopting the simplified interference
analysis presented at [8], we can measure the benefit of using P-CQI or any
other report scheme which omit the same percentage of CQI reports. Considering
a fixed number Mu=30 of users in the cell, we calculate an
approximate estimation of the signal reception quality gain at Node B. Table 1 shows how the gain of the Eb/I0 ratio increases, as the ratio of predicted CQI reports to the total number of
CQI reports increases. The periodic-CQI scheme with a reporting cycle of 2 milliseconds
is used as a reference base.Table 1
Eb/I0 gain versus increasing ratio
of CQI predictions.
Ratio of predicted CQI1/22/33/44/5reports/total CQI reportsEb/I0 Gain (dB)1,482,232,672,98As we can see in Table1, the uplink reception quality improves as the
number of CQI predictions increases. Although a high ratio of CQI predictions
may be impractical in a real system, as prediction accuracy decreases when the
number of predicted samples is increased, we can conclude from Table 1 that
even by predicting, and thus avoiding, the transmission of just one every two
CQI reports, we can achieve a significant gain of approximately 1.5 dB.


## 2.1. System Concepts

The HSDPA operation utilizes a number of new channels [4].The user data are transmitted through the high-speed Downlink
shared channel (HS-DSCH) while the associated signaling is transmitted through
the high-speed shared control channel (HS-SCCH) at the forward link and at the
high-speed dedicated physical control channel (HS-DPCCH) in the uplink.The feedback information from the terminal
to the base station, carried on the HS-DPCCH, is essential for the HSDPA
operation as it makes possible the use of adaptive modulation and coding. The
HS-DPCCH frame consists of three slots and has duration of 2 milliseconds. The
first slot is used by the hybrid automatic repeat request (HARQ) process, while
the other two slots are used for the transmission of CQI. CQI is not a direct signal-to-interference and noise ratio (SINR) measurement but instead it is an integer
index to the TFRC which the UE requests from the packet scheduler located at Node B
[5].Given a typical target error rate of 10%,
the requested TFRC corresponds to the maximum transport block size which has a
minimum of 90% probability to be transmitted correctly. Two successive CQI
values correspond approximately to a step of 1 dB at the SINR of the HS-DSCH [4, 5].At Release 5, 3GPP [6] proposes a periodic-CQI feedback scheme which, as
illustrated at Figure 1(a), has a report cycle of rc. The possible values of rc are 0, 1, 5, 10, 20, 40, 80 sub-frames or
correspondingly 0, 2, 10, 20, 40, 80, 160 milliseconds. The enhanced-CQI reporting
(E-CQI) scheme described at release 6 [7]
extends Release 5 specifications by introducing
additional CQI reports during periods of downlink activity. As shown in Figure 1(b), the additional CQI reports are transmitted with
every packet acknowledgment (ACK) (and/or Non-ACK). The aim of the “enhanced-CQI
reporting” is to use longer report cycles compared to the periodic-CQI scheme
and increase the number of the CQI reports when it is needed (i.e., when the
downlink activity increases).Figure 1
CQI reporting schemes.


## 2.2. Problem Statement

It is obvious that
the shorter the report cycle is, the more advantageous for the AMC procedure of
HSDPA it is, as it provides
better adaptation to the variations of the wireless channel. However, at the
same time, the frequent CQI signaling increases uplink interference and thus
decreases the average UE throughput as well as the achievable
energy-per-bit
to noiseEb/I0 ratio at the reverse link. The
“enhanced-CQI reporting” scheme of [7]
is a step towards the right direction, however, it
will still perform as a periodic scheme in the case of CBR services such as
VoIP or even during the bursty periods of VBR services such as FTP.In this paper, we propose an improved CQI reporting scheme which aims to
reduce the required CQI signaling even when the downlink data activity is high
by employing a CQI prediction method. According to this
scheme, Node B predicts all the
intermediary CQI reports between two subsequent CQI
reports by utilizing an FSMC model of the wireless
channel. Thus, as shown in Figure1(c), in our proposed mechanism, a
number of CQI reports can be predicted instead of transmitted.The proposed prediction-based CQI reporting scheme (P-CQI) is based on
the optimum periodic-CQI feedback scheme [6]
which has the minimum reporting cycle of 2 milliseconds.
Therefore, every 2 milliseconds, a CQI report is either transmitted by the UE or
predicted at Node B. By increasing the number of intermediary CQI predictions,
the actual reporting cycle is increased and consequently CQI transmissions are
decreased. Thus, by employing P-CQI, a significant interference reduction in
the uplink can be achieved.Adopting the simplified interference
analysis presented at [8], we can measure the benefit of using P-CQI or any
other report scheme which omit the same percentage of CQI reports. Considering
a fixed number Mu=30 of users in the cell, we calculate an
approximate estimation of the signal reception quality gain at Node B. Table 1 shows how the gain of the Eb/I0 ratio increases, as the ratio of predicted CQI reports to the total number of
CQI reports increases. The periodic-CQI scheme with a reporting cycle of 2 milliseconds
is used as a reference base.Table 1
Eb/I0 gain versus increasing ratio
of CQI predictions.
Ratio of predicted CQI1/22/33/44/5reports/total CQI reportsEb/I0 Gain (dB)1,482,232,672,98As we can see in Table1, the uplink reception quality improves as the
number of CQI predictions increases. Although a high ratio of CQI predictions
may be impractical in a real system, as prediction accuracy decreases when the
number of predicted samples is increased, we can conclude from Table 1 that
even by predicting, and thus avoiding, the transmission of just one every two
CQI reports, we can achieve a significant gain of approximately 1.5 dB.


## 3. Prediction-Based CQI Scheme

The CQI reports
indicate the requested transport format by the UE and thus they reflect the
current channel conditions. Therefore, they can be interpreted to SINR
measurements. The obtained SINR values are then used by the P-CQI scheme to
predict, through an FSMC model, the next state of the wireless channel and
therefore the next CQI. Consequently, we can predict the next CQI at Node B
reducing thus the number of the needed CQI reports.


### 3.1. Defining the FSMC Model of the Wireless Channel Conditions

Letψi be a random variable denoting
the value of the received SINRi of user i in a Rayleigh
multipath fading environment, which is proportional to the square of the signal
envelop. The probability density function of ψi can be
expressed [9] as p(ψi)=(1/ψ0)e-ψi/ψ0, ψi≥0,
where ψ0=E{ψi} is the mean value of
SINR, which can estimated by averaging the SINR of all Mu active users in the cell as ψ0=∑j∈Muψj/Mu. According to the FSMC model, K+1 increasing SINR values Ψ0=0<Ψ1<Ψ2<⋯<ΨK=∞ define K states that describe the channel condition as follows: the wireless channel of user connection i is considered to be in state Sk if the measured ψi lies in the interval {Ψk,Ψk+1}.Assuming that the channel fades
slowly with respect to the CQI feedback
report cycle and the Doppler shiftfd in the carrier
frequency fc is fd=νfc/c, then, following the
equal probability method, the steady-state probability of state k is [10]
(1)πk=∫ΨKΨK+1p(ψ)dψ=e−Ψk/ψ0−e−Ψk+1/ψ0. Then the transition probabilities at the FSMC model can be approximated by the following
equation:(2)pk,k+1≅1πkfdTs2πΨk+1ψ0e−Ψk+1/ψ0,pk,k−1≅1πkfdTs2πΨkψ0e−Ψk/ψ0,pk,k=1−(pk,k+1+pk,k−1), where Ts is the HSDPA
subframe duration (2 milliseconds). We also assume that the channel remains in
one state at each HSDPA subframe and that the transition probability between nonadjacent
states is very small. Therefore, we can assume that transitions happen at the
end of the HSDPA subframe and occur only between adjacent states.


### 3.2. Prediction of the Next CQI

The CQI prediction is based on the constructed FSMC wireless channel model. Given
the current state of the channel which is computed by a CQI report, the next
statem is the one in which the Markov chain will transit to with the
highest state transition probability pm,k=max⁡(pk,k,pk,k+1,pk,k−1).More future states may be predicted in the same manner using the same
calculated transition probabilities. The SINR value is then translated at Node B to the respective CQI value (i.e.,
TFRC). The state transition probabilities are updated periodically based on the
real SINR levels received from the mobiles each time the real CQI measurements
are collected. The steps involved in the prediction procedure are illustrated
in Figure2.Figure 2
CQI prediction method.


## 3.1. Defining the FSMC Model of the Wireless Channel Conditions

Letψi be a random variable denoting
the value of the received SINRi of user i in a Rayleigh
multipath fading environment, which is proportional to the square of the signal
envelop. The probability density function of ψi can be
expressed [9] as p(ψi)=(1/ψ0)e-ψi/ψ0, ψi≥0,
where ψ0=E{ψi} is the mean value of
SINR, which can estimated by averaging the SINR of all Mu active users in the cell as ψ0=∑j∈Muψj/Mu. According to the FSMC model, K+1 increasing SINR values Ψ0=0<Ψ1<Ψ2<⋯<ΨK=∞ define K states that describe the channel condition as follows: the wireless channel of user connection i is considered to be in state Sk if the measured ψi lies in the interval {Ψk,Ψk+1}.Assuming that the channel fades
slowly with respect to the CQI feedback
report cycle and the Doppler shiftfd in the carrier
frequency fc is fd=νfc/c, then, following the
equal probability method, the steady-state probability of state k is [10]
(1)πk=∫ΨKΨK+1p(ψ)dψ=e−Ψk/ψ0−e−Ψk+1/ψ0. Then the transition probabilities at the FSMC model can be approximated by the following
equation:(2)pk,k+1≅1πkfdTs2πΨk+1ψ0e−Ψk+1/ψ0,pk,k−1≅1πkfdTs2πΨkψ0e−Ψk/ψ0,pk,k=1−(pk,k+1+pk,k−1), where Ts is the HSDPA
subframe duration (2 milliseconds). We also assume that the channel remains in
one state at each HSDPA subframe and that the transition probability between nonadjacent
states is very small. Therefore, we can assume that transitions happen at the
end of the HSDPA subframe and occur only between adjacent states.


## 3.2. Prediction of the Next CQI

The CQI prediction is based on the constructed FSMC wireless channel model. Given
the current state of the channel which is computed by a CQI report, the next
statem is the one in which the Markov chain will transit to with the
highest state transition probability pm,k=max⁡(pk,k,pk,k+1,pk,k−1).More future states may be predicted in the same manner using the same
calculated transition probabilities. The SINR value is then translated at Node B to the respective CQI value (i.e.,
TFRC). The state transition probabilities are updated periodically based on the
real SINR levels received from the mobiles each time the real CQI measurements
are collected. The steps involved in the prediction procedure are illustrated
in Figure2.Figure 2
CQI prediction method.


## 4. Node B Packet Scheduling

For the packet scheduling, we employ the
scheduler presented at [11] and adapt it to HSDPA. Thus, the scheduling period Ts is decreased to 2 milliseconds while multicode
operation and AMC are employed.


### 4.1. Priority Sorting

According to this scheme, a priorityPi that can be calculated by
the following equation is assigned to the traffic flow of user i:(3)Pi=TQ,i(nTs)Tth,i×(1−Pe,i)i∈Mu,n=0,1,2,…, where TQ,i is the delay of the head of line (HOL)
packet in the queue during the nth scheduling period, Tth,i is the delay threshold of packets for the specific service, and Pe,i is the bit-error
probability during the next frame determined by the state of the wireless
channel which is predicted by the FSMC model of the channel. If k is the predicted next state of the
wireless channel of user i,Pe,i is given by [10](4)Pe,i=1πk∫ΨkΨk+1pem(ψ)⋅p(ψ)dψ,
where pem(ψ) denotes the error probability for a
specific modulation scheme.In HSDPA, the transmitted signal is modulated with either QPSK or 16QAM. Thepem(ψ) for the QPSK and 16QAM is given, respectively,
by the following equation [12]:(5)pemQPSK(ψ)=12erfc(ψ),pem16QAM(ψ)=38erfc(25ψ)−964erfc2(25ψ).


### 4.2. Rate Allocation

The flows are sorted in decreasing order of their
priorities and the scheduler assigns, to the highest priority connection, the
maximum TFRC for the current subframe according to the requested (or predicted)
CQI and the available HSDPA capacity. The rate allocation procedure continues
with the next connection in the sorted list until either (a) all the
connections of the list are examined and all their respective queued packets
are scheduled for transmission during the next subframe, or (b) all the
available capacity has been allocated.


## 4.1. Priority Sorting

According to this scheme, a priorityPi that can be calculated by
the following equation is assigned to the traffic flow of user i:(3)Pi=TQ,i(nTs)Tth,i×(1−Pe,i)i∈Mu,n=0,1,2,…, where TQ,i is the delay of the head of line (HOL)
packet in the queue during the nth scheduling period, Tth,i is the delay threshold of packets for the specific service, and Pe,i is the bit-error
probability during the next frame determined by the state of the wireless
channel which is predicted by the FSMC model of the channel. If k is the predicted next state of the
wireless channel of user i,Pe,i is given by [10](4)Pe,i=1πk∫ΨkΨk+1pem(ψ)⋅p(ψ)dψ,
where pem(ψ) denotes the error probability for a
specific modulation scheme.In HSDPA, the transmitted signal is modulated with either QPSK or 16QAM. Thepem(ψ) for the QPSK and 16QAM is given, respectively,
by the following equation [12]:(5)pemQPSK(ψ)=12erfc(ψ),pem16QAM(ψ)=38erfc(25ψ)−964erfc2(25ψ).


## 4.2. Rate Allocation

The flows are sorted in decreasing order of their
priorities and the scheduler assigns, to the highest priority connection, the
maximum TFRC for the current subframe according to the requested (or predicted)
CQI and the available HSDPA capacity. The rate allocation procedure continues
with the next connection in the sorted list until either (a) all the
connections of the list are examined and all their respective queued packets
are scheduled for transmission during the next subframe, or (b) all the
available capacity has been allocated.


## 5. Performance Evaluation

The performance of the proposed P-CQI
reporting scheme is evaluated via event-driven simulation. We consider a cell
with a radius of 1 km. Node B is located at the centre of the cell. The session
arrival process is modelled by a Poisson distribution, while the session
duration is exponentially distributed with equal mean. The traffic load
increases by increasing the number of users in the cell. At the downlink, the
user’s data are transmitted through HSDPA while on the uplink the HS-DPCCH is
employed for the transmission of the signaling data.For each connection the traffic is assumed to arrive according to an “ON-OFF” model
during the duration of the session. As long as the
connection is in the “OFF” state, it has no arrivals. While in the “ON” state, a batch ofN packets arrives per timeslot. N is uniformly distributed between NL and NH, where NL,NH∈R+. A packet is
defined as the amount of bits that can be received during one timeslot at the
lowest available rate R. The probability PON of being in the ON state,
as well as the NL,NH are predefined for each connection.The initial
location of each UE is randomly distributed in the cell, the directions of
movement of the users are uniformly distributed, while their velocity is also uniformly
distributed in a [0,3] km/h interval. The macrocell propagation model proposed
in [13] is adopted for calculating the path loss at
distance di (km) from Node B. Therefore, the
attenuation Lp of the transmitted
signal for a Node B antenna height of 15 meter and a 2 GHz carrier frequency is
defined as Lp(di)=128.1+37.6log⁡(di) [dB]. The modeling
of the wireless channel is performed through a four-state FSMC [10] which provides the required accuracy without adding
excessive complexity. The equal probability method (EPM) [10, 14] is used to determine the steady-state probabilities
and by this means the transition probabilities. The CQI signaling delay is not
taken into account as it is expected to affect the performance of all the
evaluated CQI schemes in a similar manner and thus does not alter our comparison.


### 5.1. Effect of the CQI Reporting Scheme in AMC

If the CQI information is not accurate, the AMC operation of HS-DSCH cannot be efficient. As a
consequence, this affects various metrics, such as bit-error rate (BER), packet
delay and throughput. In the following, we evaluate the proposed P-CQI scheme
by measuring the effect of prediction on the above metrics.Considering the worst case, where E-CQI performs as the
periodic-CQI due to high downlink activity, we assume
services withPON equal
to 1 while NL=4, NH=6 and the delay
threshold Dth is set to 100 milliseconds.
Furthermore, given that the optimum performance of AMC is achieved when
the CQI reporting is as frequent as possible, we use the periodic-CQI feedback scheme
with a report cycle of 2 milliseconds as a reference. The evaluated P-CQI scheme has a report
cycle of 2 milliseconds with a CQI prediction ratio of 1/2 (P-CQI_2ms1/2). Hence, one every two CQI
reports is predicted and the required CQI signaling is reduced by half corresponding
to an actual report cycle of 4 milliseconds. The periodic-CQI feedback scheme with a report cycle of 4 milliseconds, which causes the same uplink
interference as P-CQI_2ms1/2, is also
evaluated for comparison.As we can see in Figure3, the average BER for the periodic-CQI_4ms is
significantly higher than that of P-CQI at medium-to-high traffic loads. On the
other hand, the performance of P-CQI is close to the optimum performance of the
periodic-CQI_2ms at all traffic loads. The difference between P-CQI and periodic-CQI_2ms is due to the fact that the CQI prediction procedure cannot always be
accurate. Therefore, P-CQI can achieve performance comparable to
the performance of the optimum periodic-CQI_2ms while produces as low interference
as the periodic-CQI_4ms.Figure 3
Average bit-error rate under periodic-CQI and P-CQI.This conclusion can also be
verified by Figures4 and 5 where
the average packet delay and the average cell throughput,
as a percentage of the total capacity, are shown, respectively. While both
metrics increase as the traffic load increases, we can see that again the performance
of P-CQI is very close to the optimum performance while at the same time
outperforms periodic-CQI_4ms especially at medium to high traffic loads.Figure 4
Average packet delay under periodic-CQI and P-CQI.Figure 5
Average cell throughput under periodic-CQI and P-CQI.


## 5.1. Effect of the CQI Reporting Scheme in AMC

If the CQI information is not accurate, the AMC operation of HS-DSCH cannot be efficient. As a
consequence, this affects various metrics, such as bit-error rate (BER), packet
delay and throughput. In the following, we evaluate the proposed P-CQI scheme
by measuring the effect of prediction on the above metrics.Considering the worst case, where E-CQI performs as the
periodic-CQI due to high downlink activity, we assume
services withPON equal
to 1 while NL=4, NH=6 and the delay
threshold Dth is set to 100 milliseconds.
Furthermore, given that the optimum performance of AMC is achieved when
the CQI reporting is as frequent as possible, we use the periodic-CQI feedback scheme
with a report cycle of 2 milliseconds as a reference. The evaluated P-CQI scheme has a report
cycle of 2 milliseconds with a CQI prediction ratio of 1/2 (P-CQI_2ms1/2). Hence, one every two CQI
reports is predicted and the required CQI signaling is reduced by half corresponding
to an actual report cycle of 4 milliseconds. The periodic-CQI feedback scheme with a report cycle of 4 milliseconds, which causes the same uplink
interference as P-CQI_2ms1/2, is also
evaluated for comparison.As we can see in Figure3, the average BER for the periodic-CQI_4ms is
significantly higher than that of P-CQI at medium-to-high traffic loads. On the
other hand, the performance of P-CQI is close to the optimum performance of the
periodic-CQI_2ms at all traffic loads. The difference between P-CQI and periodic-CQI_2ms is due to the fact that the CQI prediction procedure cannot always be
accurate. Therefore, P-CQI can achieve performance comparable to
the performance of the optimum periodic-CQI_2ms while produces as low interference
as the periodic-CQI_4ms.Figure 3
Average bit-error rate under periodic-CQI and P-CQI.This conclusion can also be
verified by Figures4 and 5 where
the average packet delay and the average cell throughput,
as a percentage of the total capacity, are shown, respectively. While both
metrics increase as the traffic load increases, we can see that again the performance
of P-CQI is very close to the optimum performance while at the same time
outperforms periodic-CQI_4ms especially at medium to high traffic loads.Figure 4
Average packet delay under periodic-CQI and P-CQI.Figure 5
Average cell throughput under periodic-CQI and P-CQI.


## 6. Conclusions

In this paper, we propose a prediction-based CQI reporting scheme
(P-CQI). P-CQI has better performance
compared with a periodic-CQI scheme which causes the same uplink interference. Due to the prediction
of a number of CQI reports, the P-CQI scheme reduces significantly the required
CQI signaling while at the same time has a performance near to optimum. As a consequence,
the reception quality at the uplink is increased. The only induced cost by the
use of P-CQI is an insignificant increase of the complexity at Node B because
Node B has to calculate a number of CQI reports instead of receiving them from
the UE.



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*Source: 982805-2008-04-13.xml*