Smart Cooperative Relay Schemes in LTE-Advanced System

Saransh Malik Chonnam National University

South Korea +82-62-530-0654

saranshmk@gmail.com

Dahee No Chonnam National University

South Korea +82-62-530-0654

youngkye66@naver.com

Dae Jin Kim Chonnam National University

South Korea +82-62-530-1756

djinkim@chonnam.ac.kr

Sangmi Moon Chonnam National University

South Korea +82-62-530-0654

msm0804@naver.com

Se Young Kim Chonnam National University

South Korea +82-62-530-0758

seyoung55@daum.net

Intae Hwang Chonnam National University

South Korea +82-62-530-0654

hit@chonnam.ac.kr

Bora Kim Chonnam National University

South Korea +82-62-530-0654

bora54321@naver.com

Jin Lee Chonnam National University

South Korea +82-62-530-0758

endlesssz@naver.com

ABSTRACT Cooperative relaying is considered as the most cost-efficient method in 3GPP LTE-Advanced in terms of coverage prolongation and transmission efficiency. In this paper, we analyze the best performing cooperative relaying scheme between the Amplify– and–Forward (AF) and Decode-and–Forward (DF) schemes for LTE-Advanced systems. The comparison between AF and DF Relay Nodes (RN) is important because both approaches are currently under consideration for 3GPP LTE-Advanced (LTE-A). The performance analysis of these two relay nodes considers the criteria of: (1) Linear equalization techniques such as Zero Forcing (ZF) and Minimum Mean Square Error (MMSE) and (2) Cooperative Diversity using 2x2 Multiple Input and Multiple Output (MIMO) Alamouti scheme also termed as Space Frequency and Block Coding. Simulation results show that the Bit Error Rate (BER) performance of AF RN and DF RN improves in LTE-Advanced system and that DF RN clearly outperforms AF RN.

Categories and Subject Descriptors G.4 [MATLAB]: Workspace, structure, functions ,text scripting, graph plotter.

General Terms Algorithms, Documentation, Performance, Design, Experimentation, standardization, theory.

Keywords Amplify-and-Forward (AF), Decode-and-Forward (DF), Zero Forcing (ZF), Minimum Mean Square Error (MMSE), Cooperative diversity , MIMO,OFDM, LTE-Advanced.

1. INTRODUCTION The Long Term Evolution–Advanced (LTE-A) is the latest and the fastest data transmission technology proposed by the third Generation Partnership Project (3GPP) which fulfills the 4G requirements specified by the International Telecommunication Union (ITU-R)[1]. LTE-A focuses on a cell planning strategy in order to achieve better selection criteria based on either signal-to-noise-ratio (SNR) or SINR. Thus, we perform 3GPP compliant simulations in order to evaluate the effects of different strategies on system performance.

Deploying decode and forward relay nodes (RNs) is a promising solution in LTE-Advanced networks for meeting the growing demand and challenging requirements for coverage extension and capacity enhancement [2]. RNs are diverse in functionality and mode of operation. Amplify-and-Forward (AF) relays have been used just as a stop gap relay implementation, but it is a well known fact that AF relays amplify not only the desired signal but also both interference and noise. Decode and- Forward (DF) relays, detect the desired signal and then encode and forward it. Therefore, DF relays seem an appropriate choice for interference limited environments. The system considered in this paper is half duplex. In this paper, we look at the design and implementation of AF RN and DF RN in order to reduce the complexity and gain coverage extension while keeping the same power constraint. We investigate cooperative relay detection schemes and cooperative diversity schemes within the LTE-A framework. Schemes in conventional systems are compared with LTE-A link transmission

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parameters of the proposed schemes. In these schemes we use an evolved NodeB (eNB) base station, the relay node RN and User equipment (UE) destination node.

Our comparison and analysis is based on using AF and DF protocols on a single hop relay node. We analyze the link connection with a phase-I eNB to the RN and UE , then again for a phase-II RN with UE. The performance is evaluated in terms of the detection technique’s zero forcing, MMSE and the cooperative diversity using block coding technique with 2x2 MIMO at the eNB , RN and the UE with LTE-A.

The paper is organized as follows: Section 2 presents the theoretical analysis of the cooperative relaying schemes AF and DF in conventional systems. In Section 3, we evaluate cooperative relay detection methods in LTE–A systems. The performances are categorized by linear detection methods applied to LTE-A Parameters. In Section 4, a comparison of cooperative diversity with conventional relay protocols in a LTE-A framework is made. In Section 5,we present the performance analysis results supporting our proposal and finally, section 6 contains the conclusions and future enhancement of our work.

2. Cooperative Relaying Schemes in Conventional Systems The conventional relaying schemes such as Amplify-and-Forward (AF) and Decode-and-Forward (DF) are stated as the backbone of relay communication. The system we consider assumes a half duplex transmission scheme. Both relay node works in half duplex and the performance is considered as unchanged at the link level [3].Figure 1. shows the model of half duplex transmission in relay systems. In phase I the eNB transmits full signals and these signals are received by both the RN and the UE. In phase II the UE receives another signal from the relay node. The signal nature of the signal from the relay node depends on the type of protocol followed by the relay node.

Figure 1. Half Duplex Relay Transmission.

The relay may simply amplify the received signal and forward it, as in Amplify-and-Forward (AF), or it may first decode the received information and then forward the encoded symbols to the destination, which is referred to as Decode-and-Forward (DF).

2.1 Cooperative Relaying Scheme: Amplify- and-Forward (AF) Amplify-and-Forward (AF) is the simplest way of cooperating. Each user in this method receives a noisy version of the signal transmitted by its partner. As the name implies, the user then

amplifies and retransmits this noisy version. The base station combines the information sent by the user and partner, and makes a final decision on the transmitted bit. Although noise is amplified by cooperation, the base station receives two independently faded versions of the signal and can make better decisions on the detection of information. In amplify-and-forward it is assumed that the base station knows the inter user channel coefficients for optimal decoding, so some mechanism of exchanging or estimating this must be incorporated into any implementation. Here we assume that the power of the signal retransmitted at the relay node is scaled uniformly with respect to all the bits in the package, such that the average (re-)transmission energy per signal equals ES. In time slot 1, the signals received at the relay and the destinations are [4]

(1) and the amplification factor is given as –

Where n0 and ni, D, i = 1,2 denote the zero-mean complex AWGN at the inter-user channel and home channel with variances equal to N1/2 and N0/2 per dimension, respectively. IN time slot 2, the equivalent signal to be retransmitted by the relay contains a unit average power (2) of:

(2) The relays signal at destination is given as (3)

(3) Where n is the zero mean complex Gaussian Noise with variance

per dimension. At, the destination we receive

using the maximal ratio combination rule before decoding.

2.2 Cooperative Relaying Scheme: Decode-and –Forward (DF) The signal transmission in DF mode for the first time slot is the same as that of the AF mode (see 2 and 3). During time slot 2, the relay first demodulates and decodes the received signal. Upon success, it re-encodes the data (possibly using a different code) and forwards it to the destination [5]. Hence, the destination receives:

(4) In the outage case, where the relay fails to decode the data

correctly, it cannot help its partner in the current round of cooperation. It may select to either stay silent (to save energy) or transmits its own data (to improve the channel utilization) [5]. The mutual information between the source and the destination is limited by the mutual information of the weakest link between the source–relay and the combined channel from the source–destination and relay–destination. More specifically, the mutual

information for decode-and-forward transmission in terms of channel fades can be given by -

(5) where , the min operator in the above equation takes into account the fact that the relay only transmits if decoded correctly, and hence the performance is limited by the weakest link between the source–destination and source–relay.

Since, the channel is affected by Rayleigh Flat fading, the above random variables are all exponential random variables with a parameter of one. Averaging over the channel conditions, the outage probability for decode-and-forward at high SNR is given by

(6) From (8), it can be seen that fixed relaying has the

advantage of easy implementation, but the disadvantage of low bandwidth efficiency. This is because half of the channel resources are allocated to the relay for transmission, which reduces the overall rate. This is especially true when the source–destination channel is not so bad, because under this scenario a high percentage of the packets transmitted by the source to the destination can be received correctly by the destination and the relay’s transmissions are wasted.

3. Cooperative Relay Detection Methods in LTE-Advanced Systems In selecting the techniques for equalization we must compare the performance of the receiver and check the signal error performance of each relay node implementation [6].

3.1 AF and DF with ZF The source, relay and destination nodes are equipped with Ns, Nr, and Nd antennas, respectively. All data streams are transmitted through the relay and the direct link, which is considered to fade with increasing distance and time delay from source to destination. Hs,r , Hr,d and Hs,d are the channel matrices for the source-relay and the relay destination links with the dimensions NrxNs and NdxNr, respectively.

Figure 2. Source to Relay to Destination Functional Block Diagram in the Equalization

The communication process between the source and destination nodes is completed in two time slots. In the first slot, the Nsx1 source signal vector s is transmitted to the relay and destination. The received signal at the relay node can be written as

(7) where, yr and vr are the received signal and the additive Gaussian noise vectors at the relay node, respectively. In the second slot, the source node remains silent and the relay node multiplies the received signal vector by the NrxNr relay amplifying matrix F and

transmits the amplified signal vector xr to the destination node. Thus,

(8)

where, H = Hr,d .F. Hs,r is the equivalent MIMO channel and v = Hr,dFvr + vd is the equivalent noise. The ZF linear detector with the constraint WHH=IN is given by (9)

(9) In AF transmission, we simply multiply the amplification factor while using the relay as shown in Figure 2. In the next step, to achieve the desired value at the destination we multiply the value of W from the relay and destination using MRC. For DF, we need to calculate the channel fading and then calculating the SNR threshold value at the relay node. Then the OFDM system decodes the received signal and send it back at the destination.

W is also known as the pseudo-inverse for a general mxn matrix and (.)-1 indicates a simple matrix inversion. In order for a pseudo-inverse to exist, Nd must be greater than or equal to Ns. For the AF, we multiply the value of the received version with the amplified value (3).which gives us the amplified value of the signal at the receiver. Similarly, in the case of DF we use (6) with the given values of W and we can get the equalized value at the receiver.

3.2 AF and DF with MMSE The transmission mode is similar for both transmission schemes only the values of the channel matrix changes. For the equalized value of MMSE at the destination node we basically depend on the mode of transmission from the relay and from the source node. MMSE uses

(10) Where, C = Hr;dFFHHH

r;d + INd is the noise covariance. For AF, we multiply the system matrix with the MMSE channel matrix. The system enhances the noise due to the amplification factor but due to channel inversion a noise reduction is still observed. In DF, due to the increase in the delay of computation we detect the signal at the receiver and we multiply the channel matrix by equation (10).

(11) In order to receive the exact value . Power comparison helps us to analyze the exact value of the BER.

Due to the enhancement of noise and interference increases in the error are expected but these are damped later by re-encoding .The effect of channel fades increases within time as

the node is considered as a cell end so a large delay is noticed in the direct link.

4. Cooperative Diversity in LTE-Advanced System In half duplex, DF relaying, resources used on the access link can be reused among n RNs within the overlaying macro cell. It should be noted that LTE’s space-frequency domain split of physical resource blocks (PRBs) in the relaying system is done for simplicity. In order to maintain exact simulation results we exclusively use the frequency. By assuming equal resource consumption in RNs, , the values of the power will be constant at both relay node and the destination node.

Cooperation leads to an interesting trade-off in code rates and transmit power. In the case of power, one may argue on one hand that more power is needed because each user, when in cooperative mode, is transmitting for both users. On the other hand, the baseline transmits power for both users will be reduced because of diversity. In the face of this trade-off, one hopes for a net reduction of transmit power, if everything else is constant [7].This is shown in the figure 3,

Figure 3. SFBC Mode in a Half-Duplex Transmission

We now consider, the case of a 2 transmit antennas and 2 receiver antennas in an Alamouti scheme, which will be used in our proposed cooperative scheme. A cooperative relay-based 2× 2 Alamouti scheme is presented in figure 4. In this scheme we use the, three-node system shown in figure 3. .The 2×2 Alamouti scheme is considered between any two nodes in figure 4 (i.e., S-R, R-D, and S-D). During the first stage of cooperation, the source (S) sends the symbols x1,x2 using antenna 1 and 2, respectively, during the first time slot and sends –x*2,x*1 and during the second time slot.

Figure 4. SFBC mechanism for 2x2 MIMO System

The relay and the destination antennas receive the symbols transmitted during the first stage. Then, the relay generates two decision variables V(1)

1,R and V(1)2,R (superscripts

show it is stage 1 ) [8]. (12)

(13) Then the relay decision variables V(1)

1,R and V(1)2,R , are given as

(15) In the same time domain another two decision variables, V(1)

1,D and V(1)

2,D , are generated at the destination during the first cooperative stage and given as -

(16) In the second stage, the relay sends its own decision variables V(2)

1,D and V(2)2,D to the destination using the second stage time

slot. The destination uses Alamouti decoding to generate

(17) where,

(18) The effective decision variables (i.e., N1,eff and N2,eff ) are then sent to the ML detector to recover the transmitted symbols x1 and x2, respectively. The most important characteristic of an Alamouti scheme is that no feedback from the receiver to transmitter is required for channel state information (CSI) to obtain full transmit diversity. It also has identical performance as MRC if the total radiated power is doubled from that used in maximum ratio combining (MRC).

4.1 MIMO Diversity with AF System The amplification factor is applied at the relay node .Then, the signal is amplified at relay and again transmitted using predefined constraints. Figure 5 shows the functional block diagram of the AF scheme.

Figure 5. MIMO-OFDM Functional Block Diagram of the AF Relay Node in an LTE-A System

The amplification factor beta is given by the coefficients of the channel and the noise variance. The magnitude of the square of the channel shows the channel gain multiplication at a relay node.

To satisfy the transmitted power per source symbol constraint of P = P1 + P2. The received signal at the destination after the k-th relay transmission is given by

(19) The interference in this technique is enhanced a lot more therefore the performance may not excel. The LTE-A parameters help us to resolve this problem. The interference cancellation among subcarriers is well resolved in LTE-A system which helps to improvise the amplification of noise and interference at the relay node and the destination node. Therefore. when the signal is amplified at the relay the noise level does not interfere with the data subcarriers due to the long Cyclic Prefix size of the subcarriers.

4.2 MIMO Diversity with DF System Decode-and-Forward (DF) is closest to traditional methods; its original intention was to eliminate noise in the cooperation node to avoid noise amplification. In this mode, the mobile terminal is always trying to decode the received signals first and then forwards it to the destination node after encoding, so the effects of noise, which is generated at the cooperation node, are removed. The merit of this mode is that it is simple and can easily be to various channels.

Figure 6. MIMO-OFDM Functional Block Diagram of the DF Relay Node in LTE-A Systems Figure 6, illustrates the proposed scheme in a MIMO-OFDM system with a Decode-and-Forward relay. The threshold to compare the performance of the high SNR values is set at the relay node. The cooperation node needs to decode the original information completely. This process has a large time cost. However, there are many advantages to this method, for example:

the cooperation node is able to correct errors if there is a wrong check code in the original information and so receiver will not get the correct information. The decision variables are given by the following equations:

(20) Assuming that the time domain noise samples are statistically independent and identically distributed the subcarrier noise terms are also statistically independent [9]. It is clear form (20) that we enhanced the received signal power for both x1 and x2 at the cost of reducing the bandwidth efficiency by half. The transmitted K and N space–frequency (SF) codeword from the relay nodes is given by –

(21) where Cr(k, n) is the symbol transmitted by the n-th relay node on the k-th subcarrier. Note that: Cr will be in SF code transmitted by the relay nodes if all of them have decoded the signal correctly in phase 1. The SF is assumed to satisfy the power constraint ||Cr||2 F≤ K.Hrn ,d(k) is the attenuation of the channel between the n-th relay node and the destination node on the k-th subcarrier, vrn ,d(k) is the destination additive white Gaussian noise on the k-th subcarrier, and it is the state of the n-th relay.

(22) It will equal 1 if the n-th relay has decoded the signal correctly in phase 1, otherwise, it will equal 0. The simulation results will justify the use of higher order modulation to recover for the loss in bandwidth efficiency. The simulation in the next section assumes that the power consumption in the cooperative system is the same as in the direct system where the relay is helping the source by relaying its data to the destination.

5. Simulation Results In the simulations, we consider two different Parameters one for the detection scheme and the other for cooperative diversity. The simulations parameters are derived from technical specification of LTE –A .

Table 1. Simulation Parameters based on LTE-A Parameters Value

Bandwidth 10MHz Subcarrier spacing 15KHz Sub frame Duration 1 ms Sampling frequency 15.36 MHz FFT Size 1024 Occupied Subcarriers 600+1(DC Subcarrier) No. of Subcarriers/RB 12 CP size(samples) 256 No. of OFDM symbols/ sub-frame

12

Channel Models Flat,EPA,ETU,EVA Modulation Scheme QPSK,16QAM Noise AWGN Decoding Technique ZF,MMSE Antenna Configuration 1x1,2x2 Relay Node (eNB) 1 Relaying Protocol AF,DF

*Flat –Flat Rayleigh Fading Channel, EPA – Extended Pedestrian A Model, EVA – Extended Vehicular A Model ETU - Extended Typical Urban The simulation follows the LTE-A parameters regarding both detection and diversity. All the simulations are performed with direct transmission named as ‘No Relay’, the AF protocol and the DF protocol. The simulation for the detection scheme is performed using QPSK with Flat Rayleigh Fading channel model and 1x1 antenna configurations. On the other hand, the cooperative diversity simulation use a 2x2 antenna configuration and a 16 QAM Modulation scheme. The system assumes perfect CSI for both receiving nodes, also the power constraint is same at both nodes.

Figure 7. Detection technique Zero Forcing with No relay, AF, DF.

The figure 7 shows the BER performance of ZF with No relay , AF and DF. The figure shows the better performance in the relay systems then the basic system while the DF scheme performs best overall. As the simulations of ZF-AF and ZF-No Relay are very close in performance it is clear that the performance of AF is improved in the LTE-A system. Also, ZF-DF shows very good performance compared to ZF-No Relay and ZF-AF, this proves that the usefulness of DF to improve the performance of ZF detection methods in LTE-A systems.

Figure 8. Detection technique MMSE with No relay, AF, DF. Figure 8, shows that performance of MMSE is better with MMSE DF and also that MMSE AF is an improvement over MMSE in a No relay system. The better performance is gained by reducing in the computational complexity of low interfering data subcarriers and reducing interference at the relay and destination nodes.

Figure 9. Detection technique ZF and MMSE showing overall performance of No relay, AF, DF. Figure 9, shows the complete simulation with our proposed system . These simulations clearly show that the performance of MMSE-DF is better than any other detection scheme [10]. Also, we see that the LTE-A framework helps to improve detection

scheme system performance when a relay system is implemented. Summarizing the performance: MMSE –DF > ZF-DF>MMSE-

AF=MMSE-No Relay>ZF-AF>ZF-No Relay.

Figure 10. 2x2 MIMO Cooperative Diversity implemented with LTE-A System The simulation results in figure 10 clearly show the performance of the diversity when implemented with different relay schemes. The system shows the best results with a 2x2 DF relaying system. As we can see, high order data rates can be achieved with 2x2 DF. Also it shows large variations in the improvement of 1x1AF and 2x2 DF BER performances. Even though, in previous tests the BER performance of AF is no better than DF there the performance of 2x2 AF is better than 1x1 DF. Summarizing the performance: 2x2 DF > 2X2 AF>1x1 DF> 1x1 AF> 2x2 No Relay>2x1 No Relay

6. Conclusions In this paper we compared the performance of relaying schemes regarding equalization techniques and cooperative diversity in a LTE-A system. Our proposed DF relay proved to have excellent performance in terms of cooperative diversity and in the detection technique. The AF relaying scheme was also a drastic improvement over traditional methods when allied with full diversity in LTE-A systems. The simulations results shows that LTE-A is very well suited to cooperative communication and shows excellent performance in terms of signal error performance.

7. Acknowledgements This research was supported by MKE (Ministry of Knowledge Economy), Korea, under the ITRC(Information Technology Research Center) support program supervised by the NIPA(National IT Industry Promotion Agency)(NIPA-2011-C1090-1111-0008). This study was financially supported by Chonnam National University, 2011

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