[IEEE 2012 First National Conference for Engineering Sciences (FNCES) - Baghdad, Iraq (2012.11.7-2012.11.8)] 2012 First National Conference for Engineering Sciences (FNCES 2012) -

The First National Conference for Engineering Sciences FNCES'12 / November 7‐8, 2012

Throughput Improvement for Wireless Networks

Using MIMO Network Coding

Abdulkareem Abdulrahman Kadhim College of Information Eng.

Al-Nahrain University, Baghdad, Iraq [email protected]

Alza Alubaidy College of Information Eng.

Al-Nahrain University, Baghdad, Iraq [email protected]

Abstract

Modern wireless communication networks demand higher throughput. As conventional methods that use more bandwidth or larger modulation levels are limited, new methods for better system performance are suggested. Multiple antenna systems where Multi-Input Multi-Output (MIMO), used to enhance channel capacity, and Network Coding (NC) are examples of such methods. In this paper, NC is used in conjunction with MIMO technique in order to obtain advantages of both mentioned techniques. A simple packet based network coding for butterfly network topology with MIMO is modeled and simulated. The system is tested over different wireless fading channel models and with different MIMO arrangements. As a result the performance of 2x2 combined Multi-Inputs Multi-Output with Network Coding (MIMO-NC) have shown improved throughput over the original MIMO system by about 33% on the expense of slight loss in error performance at relatively high signal-to-noise power ratios.

Keywords: Network coding, Throughput, MIMO, Butterfly network.

I. INTRODUCTION

a- MIMO Concepts

In wireless systems, the use of multiple antennas at the transmitter and receiver is known as MIMO technology. The technique originally proposed to combat fading introduced in multipath channels [1]. In such channels the transmitted signal may follow different paths in its way to the intended receiver. These multipath signals may arrive with different angles,

attenuation factors, time delays and frequencies. MIMO technology offers benefits in spatial dimensions by using multiple antennas at transmitter and the receiver, in addition to the benefits in both time and frequency dimensions that are used in traditional system Single-Input Single-Output (SISO) [1]. As a result, the interference introduced by multipath channel can either be avoided or reduced by MIMO system. The main advantage of MIMO system can be seen as array gain where coherent combining of multiple antennas at the receiver or transmitter or both resulted in increasing the average Signal-to-Noise power Ratio (SNR). Spatial diversity gain is another advantage of MIMO technology where a redundancy can be created by providing the receiver with multiple copies of the transmitted signal. The spatial multiplexing gain of MIMO can also be seen as a way to increase data rates [1, 2]. b- Network Coding NC is an approach used to improve transmission throughput of wireless networks in addition to some other advantages. NC has been suggested to combat the limitations on networks devices and channels in classical networks [3]. With network coding, the router will combine the packets instead of only store-and-forward the output messages by routing, thus maximizing the overall system performance [4]. In its simplest form, NC relies on intermediate nodes to combine (using a linear coding scheme) the incoming packets from different source nodes and then to forward the linearly encoded packets to all destination nodes in a single transmission. Network coding can improve throughput, robustness, complexity, reliability and security [5, 6]. In wireless networks further improvement


in resources such as energy efficiency, delay, wireless bandwidth and interference also can be obtained [4,5]. Each coding node serves as a relay node that combines the incoming packets, from different source nodes, in one encoded packet to be transmitted to all destination nodes [7]. Fig-1 shows an example of simple network, where nodes A and B want to exchange their packets via a router (R). The classical network in Fig-1(a) needs 4 transmissions to perform complete receptions of packets generated by source nodes A & B via the relay node (R) to their intended destination nodes. On the other hand and with network coding defined by linear encoding of the incoming packets from source nodes, 3 transmissions are sufficient as in Fig-1(b) [8].

c. Research Background

The present research is an attempt to combine network coding with MIMO technology so that the possible advantage in increasing network throughput can be exploited. The authors in [9] and [10] have shown that the application of NC in wireless networks either contains distributed antenna systems or support user cooperation between user terminals. In both cases, improved diversity gains are achievable. The proposal in which jointly combining NC with MIMO in order to achieve more robustness with respect to packet losses is the main contribution in [9,10]. Nevertheless, to achieve this, they have moved NC functionalities towards the physical layer and implement a more sophisticated decoding process in order to exploit the spatial diversity. In [11] a two-step communication protocol

combined with virtual MIMO and network coding technique is proposed. A three nodes network with multi-antennas on relay node is taken as an illustrative scenario. The work dealt with the theoretical and simulative performance analyses. Their main results showed that MIMO with NC protocol outperforms other relay schemes and provides more robust and efficient transmission. A scheme of MIMO with PNC (Physical Network Coding) also presented in [12], where the relay node extracts the summation and difference of the two end packets and then converts them to the network-coded form with linear MIMO detection method at the relay. The authors in [13] were introduced two types of new decoding algorithms for a network coding relaying system, which adopted multiple antennas at both the transmitter and receiver. They considered the realistic scenario of encountering decoding errors at the relay station, which resulted in erroneous forwarded data. A novel distributed space time block coding scheme with the aid of an error detection code based selection relaying protocol for multi-relay assisted two-way cooperative communication systems with PNC are presented. This novel cooperative communication scheme for two-way relay channels can achieve significant throughput and spectral efficiency improvements. In [14,15] PNC aided two-way relay scheme with multiple-antenna relay node has been proposed. Maximum ratio combining-like scheme is used to achieve both receiver and transmitter diversity. Clearly, the above references were relied on using PNC or NC in conjunction with MIMO to gain robustness and better performance. In the present work, a combined MIMO-NC scheme is to be used to show how the throughput of the network is improved. The remaining parts of the paper are organized as follows: In the next section the model of the network used is to be described. The topology of network, the MIMO system, and other main assumptions are given in this section. The fourth section shows the simulation tests results in the form of error probability and the increase in throughput versus channel SNR. The last section deals with the main concluding remarks of the work.

Figure.1 Two-node Network

A B R

a) Classical Approach

A B R

b) Network Coding


II. SYSTEM MODEL

The network considered in the present work is a wireless network that is interconnected by wireless links. Fig-2 illustrates the basic model used here. S1 and S2 are source nodes, while D1 and D2 are destination nodes. The aim here is to deliver all packets generated from different source nodes to its destination ones with least number of transmissions to increase the overall throughput of the network. S1 and D2 (also S2 and D1) are out of each other's communication range, thus they have a data to be exchanged through the relay (coding) node R.

The coding here uses packet-level network coding to improve wireless throughput. The coding node creates queues for the arrived packets from different sources connected to given coding node. At the coding (or relay) node, these packets are queued in First In First Out (FIFO) principle ready to be encoded if such opportunity is met.

Figure-2 Butterfly network

Each wireless link together with the required operation at each pair of connected nodes can be represented by the transmission model of Figure-3. The source output is either coded packets if the source is the relay node with coding opportunity, or else uncoded packets from source nodes (S1 or S2) or the relay node without coding opportunity. The latter case occurs when there are no packets in the queue of one of the sources at the relay node. When coding is involved at the relay node, the jth coded packet at the relay node PR,j is given by;

… (1)

Where and are the generated packets at

source nodes S1 and S2, respectively, and denote mod-2 addition.

In either case (whether coding is used or not), the content of the transmitted packets are handled as bit stream at the physical layer and are modulated using Binary Phase Shift Keying (BPSK) modulation. Although in practice, the layer architecture of the wireless networks involve additional processing and operations according to given wireless network specifications, here we assume that all such processing and operations are performed at both the source and the destination nodes in perfect manner so that no errors are resulted due to such operations. This assumption simplifies the network model and does not affect the results of the present investigation. The modulated BPSK stream is passed to the MIMO stage to be transmitted over a wireless channel model. The MIMO system used in the work is Alamouti Space Time Block Coding (STBC) MIMO system. Such 2x2 MIMO system is considered here for its reasonable performance and simplicity [16]. This structure is described by the following equations using matrix notation. First the channel of multiple antenna system is given by;

… (2)

where is the quasi static Rayleigh fading

coefficients of the wireless communication channel between receiver and transmitter antenna. Then the received two vectors of any two successive time slots are given by [16];

... (3)

and,

… (4)


where represent the received signal by the

time slot (for j=1, 2) at the antenna (for i=1, 2), } are the generated BPSK symbols given in the form of pairs of two successive symbols ( and ) fed to the antennas every two time slots, and * represents the complex conjugate operation. In the above equations, { are samples of Additive White Gussian Noise (AWGN) added to the signal after the wireless channel. It is assumed here that the multipath channel impulse response is perfectly estimated at the destination node so that the decoding of the MIMO system is performed correctly. Thus any inaccuracy involved by the incorrect estimation of the channel impulse response is not considered here.

At the relay node, a decode-and-forward [17] is used, where the relay node R detects the symbols and using the following equation;

… (5)

Where are the detected values of the corresponding BPSK symbols and ,

respectively, and is the complex conjugate of the transpose for the matrix H.

At the receiving side of the network nodes, the received bit streams are converted back to the corresponding packets. Following the reconstruction of the received packets at the receiving node, it is either passed to the higher layer, if the packets are uncoded, or else decoded if the intended destination node has sufficient information to do so. At each destination node, the received coded packet

from the relay node is used with the aid of

the packet received by direct transmission (uncoded packets for i=1 and 2) from its

intended source. This means that destination node D1, for example, which already received the packet , can decode the packet as

shown below;

… (6)

Similarly, the packet is decoded at the

destination node D2.

The system model that represents the wireless connectivity between any two nodes is shown in Fig-3. This represents a general case for all nodes shown in Fig-2. Clearly when source nodes transmit directly to their corresponding destination nodes the network coding block is not used. Alternatively, uncoded transmission is used.

Figure-3 Model of the system for combined

MIMO-NC techniques

III. ASSESMENT OF SIMULATION RESULTS

Simulation tests were performed to evaluate the performance of systems considered here with and without network coding. The performance measur covers both the evaluation of Bit Error Rate (BER) and the equievelant normalized throughput. These are determined for different SNR's. The SNR is taken here as the average energy per information bit relative to AWGN noise power spectral density given by its variance. The BER rate is taken as the average number of errors in receiving the data at all destination nodes relative to the total number of data bits transmitted from source nodes [18 ]. Three different channels are considered here, the ideal AWGN channel, flat fading channel and multipath fading channel with three paths.The delays for the paths are 0, 0.4, and 0.9 µs, while their gains are 0, -5, and -10 dB, respectively. The multipath fading channel is known in the litreture as SUI-3 and widely used to model


wireless networks. Details of the actual channel modelling and complete system simulationcan be found elsewhere [18]. In addition to the original SISO and MIMO systems, the cases where just single antenna is involved at either the transmitter or reciever side are also considered. These latter cases are known as Single-Input Multiple-Output (SIMO) and Multiple-Input Single-Output (MISO). All mentioned systems are tested with and without network coding. In the case where the system used network coding the system is marked with an extension NC. For example MISO-NC represents multiple-input single-output with network coding. Fig-4 shows the BER performances of different systems considered in the work. In part a of this figure AWGN channel is considered. In this case all systems shows almost a similar BER performance. This is due to the fact that the use of multi-input or/and multi-output dis not show noticeable performance improvement. Further the use of network coding has a negative affect in the sewnse that the systems with network coding show some degradation in BER for given SNR as compared to the corresponding uncoded system. The main reason for such behaiviousr is that with network coding any error involved in receiving packets at relay or coded node will lead to further errors in the decoded packets at destination. The cost of such error extension effect is reasonably small at very high SNR. The BER performances of different systems over flat fading and SUI-3 multipath fading channels are shown in parts a and b of Fig-4. SUI-3 channel is represented by three paths [17], while the model of flat fading channel has only one path and usually considered as standard fading channel in wireless networks modeling. It is worth to mention here that the flat fading channel introduces slightly more level of amplitude distortion as compared to SUI-3 channel. This is the main reason to make the curves in Fig-4(c) to be shifted to the right showing a slightly worse performnances of the systems as compared to their counterparts in Fig-4(b) for flat fading channel. Among all the systems tested here MIMO system (whether coded or not) did show better performances as compared to all other systems over the two fading channels considered. Further, MIMO BER performance is slightly better than MIMO-

NC by about 0.8 dB for the range of BER between 10-4 and 10-3 as shown in Fig-4(b) and Fig-4(c). This is due to the error extension effects encountered in network coded systems.

a. Different systems over AWGN channel

b. Different systems over flat fading channel

c. Different systems over SUI-3 channel Figure-4 Bit error rate performances


The measure of throughput is considered here to show the advantage of network coding when combined with different MIMO systems. Fig-5 shows such performance for the three channel models considered in the paper. As expected the measured throughput is directly proportional to SNR. In most litreture the throughput measurement is given in the form of transmission rates (whether in terms of packet, bit or any other data unit rates). Since, such rate measuremet depends on the useful rate of data units (generated by given source node and correctly received by intended destination one), here we consider another definition for the throughput. The packet rate is considered fixed and the measurement is performed after the final receiption of all generated packets from given source nodes by their intended destination nodes. Thus, actually we measure the normalized throughput given by the ratio of the number of correct received packets at destination nodes relative to the total number of transmitted packets involved in the whole network (from source and relay nodes) to deliver the packets to their destination nodes. Fig-5 show that there is always an increase in normalized throughput for the network coded systems over that avhieved with their uncoded counterparts. The improvement in throughput of course depends on the SNR and the topology of the network considered. Over AWGN channel Fig-5(a) the improvement is at its maximum value for SNR greater than 15 dB. At this range of SNR the BER is well below 10-3. For the fading channels Fig-5(b) & Fig-5(c) this range in SNR is increased to about 16 and 19 dB for the flat fading and SUI-3 channels, respectively. This is achieved with MIMO-NC system. Other systems achieved less improvements in throughouput at higher SNR. Clearly, the use of network coding improves the throughput, and at the same time the use of MIMO enhance such improvement by reducing BER. This work in favor of channel having multipath fading as compared to the other two channels (AWGN and flat fading). As a result, the combination of MIMO and NC provides better throughput enhancement than that achieved by the application of each technique alone over channel having multipath fading.

a. Different systems over AWGN channel

b. Different systems over flat fading channel

c. Different systems over SUI-3 channel

Figure-5 Throughput Performances


IV. CONCLUSION

A combination of MIMO and network coding arrangements are studied here aiming to increase system throughput. The results have shown that the use of SISO-NC over channel having great deal of fading does not improve the throughput unless very high SNR is considered. The use of MIMO-NC is essential when the fading level is high and the operating SNR is relatively small to gain reasonable improvement in throughput. The overall improvement in throughput depends on given topology of the network. Further this improvement cannot be met without MIMO in the case of multipath fading environment. For the network topology considered in the work 33% improvement in throughput with MIMO-NC at moderate and high SNR over fading channels. Finally, MIMO-NC system reserves the advantages of both MIMO in the form of reduced BER over fading channels and NC techniques in improving the resultant throughput. This is achieved at the expense of small BER performance degradation as compared to the original MIMO system without network coding.

REFERENCES

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[IEEE 2012 First National Conference for Engineering Sciences (FNCES) - Baghdad, Iraq (2012.11.7-2012.11.8)] 2012 First National Conference for Engineering Sciences (FNCES 2012) -