CHAPTER 6 JOINT SUBCHANNEL POWER CONTROL AND ADAPTIVE BEAMFORMING FOR MC-CDMA SYSTEMS

Transcription

1 CHAPTER 6 JOINT SUBCHANNEL POWER CONTROL AND ADAPTIVE BEAMFORMING FOR MC-CDMA SYSTEMS 6.1 INTRODUCTION The increasing demand for high data rate services necessitates technology advancement and adoption of B3G termed as 4G cellular standards. The capacity of MC-CDMA systems is limited by co-channel interference, besides the near-far effect and the time-varying fading caused by variations in the received power at the base station. However the most important issue that needs to be addressed is to combat deep fades, occurring frequently but for a very brief time. Though power control serves to mitigate the impact of deep fades, its effectiveness is clearly limited [ in MC-CDMA systems. It is evident that if a user experiences a deep fade requiring transmitted power level to be raised significantly, it will affect the SINR experienced by other users and consequently degrades the QoS. This may lead to the problem of instability as all the users increase their transmitted power level to achieve their threshold SINR (SINRI~). A joint power control and adaptive beamforming approach using an iterative algorithm suitable for MC-CDMA system is presented in this chapter. This scheme computes the transmitted powers and the beamforming weight vectors such that the threshold SINR is achieved for each link with minimum transmitted power. Thus this technique improves the capacity of the system with guaranteed QoS by utilizing minimum transmitted power. 6.2 JOINT POWER CONTROL AND BEAMFORMING In a multicellular environment the inter-cell and the intra-cell interfennces affect the quality and the capacity of all CDMA based systems. In addition,

2 MC-CDMA, being a OFDM based system is susceptible to the deeply faded subc-arriers. The overall BER is dominated by the performance of the subcarrier with the worst SNR. As a result, the error probability of the whole system increases slowly by increasing the transmined power of each user. As a result the total network power which is the sum of the transmitted power of all the users also increases. Thus an algorithm for minimizing the overall error probability with an optimum transmitted power of each user is essential. A reverse link SINR based power control scheme is a preferred technique to minimize the interference and to compensate for the near far effect, while maintaining reliable QoS. It is difficult for power control alone to handle the effect of deeply faded subcarriers. One of the other options is to discard them which results in reduction of data rates. Hence, it is imperative to use power control in conjunction with another device that can help reduce the effect of deep fades, such as beamforming. An iterative algorithm of transmined power and beamforming weight vectors at each subchannel jointly updating, converging to an optimal solution is found to be suitable. In this scheme a predetermined amount of power is allocated to the deeply faded subcarriers. These two schemes [102, 1031 one for adjusting the transmitted power and the other for improving the received signal strength to mitigate the effect of interference, are combined to have a better performance. The antenna arrays are exploited to perform time and frequency domain beamforming [105, 1061 to reduce interference. The frequency domain beamforming approach requires one fast Fourier transform (FFT) block at each antenna element and the weighted outputs are combined at each receiver. This increases the computational complexity of the system. The time domain beamforming approach reduces the complexity of the system [I071 resulting from the number of beamformers and FFT block at the receiver. The optimal solution of the beamforming weights and the transmitted powers may be obtained by taking into account the data information of all users and minimizing the power radiated by the mobile terminals while maintaining the SINR requirements. Joint beamforming and power control is thus a powerful means for reducing the interference, minimizing the total transmined power and increasing the capacity in MC-CDMA systems.

3 6.3 SYSTEM MODEL Multicellular environment with multiusers in MC-CDMA system is considered. The users are distributed around each base station at varying range. The mobiles in other base stations are power controlled by their own base stations [141]. The total number of users and the number of users in each cell are represented by where M Mb Mo K is the total number of users is the number of users in the interfering base station b is the number of users in the dh (desired) base station and is the total number of base stations. The impulse response of the channel, the channel transfer function and the received signal are given by equations (5.1), (5.2) and (5.3) respectively. 6.4 POWER CONTROL The objective of power control is to minimize the transmitted power while the SlNRs are kept above a threshold value. The minimum transmined power [40] is obtained when all of the SMRs are equal to the threshold value. A distributed power update scheme is envisaged to achieve this goal. The power of the bh mobile user at the dh base station at the nihstage of iteration is updated by r-im -1 where interference power I: = 2 IH,,~'P,(~) + 'zi~,,1~~(~) N, is the noise power b.,,.i 1.1

4 The updated power is the function of intracellular interference at the b" base station and the intercellular interference due to the users in the other base stations, the channel transfer function H,a and the threshold SINR which are locally estimated and transmitted through a feedback channel to the corresponding mobile. 6.5 JOINT POWER CONTROL AND ADAPTIVE FREQUENCY DOMAIN BEAMFORMING The block diagram for the joint power control and adaptive frequency domain beamforming for MC-CDMA systems is shown in Figure 6.1. The joint beamforming and power control algorithm is performed at each subchannel separately assuming perfect orthogonalization among subcarriers. The energy of the beam pattern [I051 at subchannel c is where the first ten represents the interference plus noise and the second term is the power of the signal from the desired direction. The SINR at the output of the beamformer at subchannel p is given by 2 SINR =,, P:IH,P,~'IE~P~ ahhl2,-i [I:~ET~.(' + N.IE:~'] The frequency domain beamforming weight vector and the autocorrelation matrix are represented by equations (5.8) and (5.9). The updated transmined power is

5 Figure 6.1 Block diagram for joint power control and adaptive frequency domain beamforming for MC-CDMA systems

6 6.5.1 Algorithm for Joint Power Control and Adaptive Frequency Domain Beamforming The algorithm explained below serves to achieve an optimal power control and adaptive beamforming at each subchannel. If there is a solution for the joint power control and beamforming problem, this algorithm will converge to the optimum solution and be unique. Slep 1 Transmitted power is initialized. Step 2 The optimum weight vector and the autocorrelation matrix are computed as in the equations (5.8) and (5.9). Slep 3 The interference power is calculated and is transmitted to the mobile through the feedback channel. Slep 4 The mobile transmitter power at each subchannel is updated. Step 5 If Php (n + I) > P,, then P,P(n + I) = P, where P- is a predetermined maximum power. h-l 21 php(n+~)-php(n)l~~~ Step 6 If p-" the iteration is stopped otherwise n is set equal to (n+l) and the steps from 2 to 6 are repeated, where fl is a threshold that defines the speed of convergence. The deeply faded subcarriers are assigned with predetermined maximum power through this joint power control and beamforming algorithm. This avoids discarding of the deeply faded subcarriers and consequent reduction of data rate. 6.6 JOINT POWER CONTROL AND ADAPTIVE TIME DOMAIN BEAMFORMLNG The block diagram for integrated power control and adaptive time domain beamforming for MC-CDMA system is shown in Figure 6.2. It is understood fium the figure that joint power control and beamforming at each subcarrier is not possible separately. The error and weight vectors are calculated in the frequency domain, since the symbol decisions are made only at the output of the FFT block. If time domain

7 beamforming is used, the frequency domain emr needs to be compensated and is related to that quantity of error in the time domain. One way of compensation is to minimize the energy at the beamformer output. But it is not possible to minimize the energy of all of the subcarriers simultaneously. Therefore the sum of the energies N -I 2 E o that is equivalent to the energy at the output of the beamformer [I071 is 1-0 minimized. The beamforming weight vector using MVDR algorithm for time domain beamforming is given by equations (5.13) and (5.14). Figure 6.2 Block diagram for joint power control and adaptive time domain beamforming for MC-CDMA system

8 6.6.1 Algorithm for Joint Power Control and Adaptive Time Domain Beamforming Step 1 Step2 Step 3 Step 4 The transmitted power is initialized. The optimum weight vector and the autocorrelation matrix are computed as in the equations (5.1 3) and (5.14). The interference power is calculated and is transmitted to the mobile through the feedback channel. The mobile transmitter power at each subchannel is updated. Step5 If P:(n+l)> P, then P:(n+l) = P, where P, is a predetermined maximum power. h -1 Cl P:(~+I)-~DP(~)~~S~ Step 6 If PO the iteration is stopped otherwise n is set equal to (n+l) and the steps from 2 to 6 are repeated, where p is a threshold that defines the speed of convergence. This algorithm is similar to that for the frequency domain beamforming except in step 2 where the base station calculates the sum of autocorrelations of all subcarriers and instead of the weight vector for each subcarrier, the weight vector for each antenna element is calculated. 6.7 SIMULATION RESULTS AND DISCUSSION The simulation parameters are given in Table 6.1. The users are randomly distributed in a cell according to uniform distribution. The multipath channel model used is COST207 which is a six tap typical urban type channel. The average power of the signal at each of the base station is assumed to be unity. It is assumed that the transmitter is located at a far distance and the received signals are considered as a plane wave. The results illustrate the advantage of frequency domain beamforming and the interference suppression capability of the proposed scheme under the practical channel model. The simulation results reveal that an MCCDMA system using one

9 beamformer per subcarrier exhibits a better performance than with a single beamformer for all subcarrier. The BER performance of MC-CDMA system with joint power control and beamforming algorithm under frequency selective fading environment is evaluated. The BER performance of joint power control and frequency domain beamforming with two wideband interferers located at [60'-60'1, [40'-40'1 and [2Y-25'1 are shown in Figures 6.3 to 6.5 respectively. The spatial location of the desired user is at 0 with respect to the array normal. The results show that the BER performance for 1024 subcarrier system is similar to one using 256 beamfonners, however there is a signiticant performance degradation for the case with I28 beamformers. Table 6.1. Simulation parameters for joint power control and adaptive beamforming

10 1olr num of beamfomerr=l28 4 num of bearnfomen=256 - num of bbamformers=512 -t- num of beamfomen=l ' SlNR Figure 6.3 BER performance of joint power control and adaptive frequent) domain beamforming with hvo wideband interferers at [-60,60'] - num of beamformen=l28 ' num of beamformen=256 num of beamformen= num of beamfonners=lgz4 lo SlNR Figure 6.4 BER performance of joint power control and adaptive frequency domain beamforming with two wideband interferers at [-40,40"]

11 - 10' num of bearnfomers=l28 num of bearnfomers=256 num of beamiormen=512 I -8- num of beamformers=lozd ' SINR Figure 6.5 BER performance of joint power control and adaptive frequency domain beamforming with two wideband interferers at ] angle of separat~on=( angle of separat~on=[ angle of separation=[ Figure 6.6 BER performance in joint power control and adaptive time domain beamforming under frequency selective fading channel

12 In Figure 6.6, the BER performance of joint pouer control with time domain beamforming is found to deteriorate than the previous case. The performance comparison of MC-CDMA system uith interferers located at different angles of separation [ , (40-40"] and [25-25 ] are analyzed. The BER performance of time domain beamformer degrades as the angle of separation of interferers is decreased wlthoul beamlorm~ng 50 wlth t~medoma~n bearnform~ng wlth frequency doma~n beamformlng Figure 6.7 Total nehvork power against SINR Figure 6.7 depicts variation of the amount of total netuork pouer required for transmission uith respect to the threshold SINR. 'The total netuork poser transmitted is minimized significantl) b) the joint pouer control and beamforming algorithm. even though the BER performance IS almost similar to the system with onlk power control algorithm and uithout bearnforming. The total netuorh poser consumption is observed to be leas in joint power control uith frequent) domain beamforming than

13 with time domain beamforming for the same threshold SINR by using frequency domain beamforming. It results in the reduction of total network power by 5 dbm whereas in the time domain beamforming the total network power is reduced only by 2 dbm. However the complexity is greatly reduced by having only one beamformer at the base station in the time domain beamforming. Thus there is a trade off between the complexity and performance in the two techniques of beamforming. Figure 6.8 Outage probability curves for joint power control and beamforming techniques The capacity of MCCDMA systems with joint power control and adaptive beamforming techniques analyzed through outage probability, (the probability of the user being discarded), is shown in Figure 6.8. It depicts less outage probability for joint power control and adaptive frequency domain beamforming than that for adaptive time domain beamforming. Maximum outage probability is noticed with conventional MCCDMA systems with power control without beamforming.

14 Table 6.2 Capacity analysis for MC-CDMA systems Schemes Conventional power control Fuzzy logic power control FGA power control Joint power control and adaptive time domain beamforming Joint power control and adaptive frequency domain beamforming Number of users 8 I I The capacity analysis of MC-CDMA systems for different schemes tested in this work are summarized in Table 6.2. It is evident that for an outage probability of 0.05, the capacity of the joint power control and frequency domain beamforming is 5 times more than the conventional scheme with fixed step power control. Though the complexity of the joint power control and frequency domain beamforming is higher than the other schemes, the capacity and performance of this scheme are far superior. 6.8 SUMMARY Future wireless services require higher data rates to be transmitted with unlimited capacity from the available resources. MC-CDMA systems realized using advanced DSP techniques and implemented through the fast and more sophisticated digital signal processors provide high data rate services. Though for the same amount of bandwidth with required QoS, the power control and adaptive beamforming independently mitigate the interference and increase the capacity, the joint scheme achieves the same target with less amount of total network power. The performance of the joint power control and beamforming iterative algorithm for MC-CDMA systems on both frequency and time domain beamfoming separately has been studied. It has been revealed that the received SNR of all subchannels are at least equal to the threshold SINR value while minimizing the total network power of the system. The algorithm has been investigated under flat fading and frequency selective channel environments. The integrated frequency domain beamforming and adaptive power

15 control has found to yield 5dB less total network power compared to single antenna case for the same threshold SINR, while it is only 3 db less for the integrated time domain case. Thus the joint scheme using frequency domain beamforming scheme reduces the interference and enhances the capacity of the MC-CDMA systems, by 5 times or more, compared to the conventional scheme, with guaranteed QoS for the =me amount of transmitted power. But it has to be pointed out that the frequency domain beamforming is relatively a complex one. Therefore there is a trade-off between the two schemes in terms of performance and complexity. It is worth pointing out that joint power control and beamforming approaches will go a long way in realizing an optimum radiated power, user-friendly mobile environment.