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Improved Ad-Hoc Networks Using Cooperative Diversity


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In this paper an ad-hoc network having source, a
destination and a third station which is a relay is analyzed.
The channels used here are modeled having thermal noise,
Rayleigh fading and path loss. Different methods for
combining and diversity protocols are compared.

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Improved Ad-Hoc Networks Using Cooperative Diversity

  1. 1. International Journal of Computer Science &Information Technology 1 IJCSIT, Vol. 1, Issue 1 (Jan-Feb 2014) e-ISSN: 1694-2329 | p-ISSN: 1694-2345 Improved Ad-Hoc Networks Using Cooperative Diversity Omkar Singh Infosys Technologies, Chandigarh, India Abstract: In this paper an ad-hoc network having source, a destination and a third station which is a relay is analyzed. The channels used here are modeled having thermal noise, Rayleigh fading and path loss. Different methods for combining and diversity protocols are compared. Amplify and forward protocol shows a better performance than decode and forward protocol, unless an error correcting code is simulated. To combine the incoming signals the channel quality should be estimated as well as possible. Information about the average quality shows nice benefits, and a rough approximation about the variation of the channel quality increases the performance even more. Whatever combination of diversity protocol and combining method is used second level diversity is observed. The relative distances between the relay and the stations have a large effect on the performance. Keywords: Rayleigh fading, cooperative diversity, relay, diversity protocols, combining methods, path loss. I. INTRODUCTION “The increasing demand for wireless multimedia and interactive Internet services, along with rapid proliferation of a multitude of communications and computational gadgets, are fuelling intensive research efforts on the design of novel wireless communication systems architectu1res for high speed, reliable and cost effective transmission solutions” [2]. The introduction and rapid development of MIMO (multiple- input and multiple-output) systems has promised significant improvements in reliability and throughput for Ad hoc networks; by utilizing multiple antennas at both the transmitter and the receive side. However, this technique is clearly advantageous for cellular base stations, but not feasible for mobile devices, due to their sizes and power constraints [1] [2]. An alternate to this is a newly developed technique known as multi-user cooperative diversity that allows a single antenna user to achieve transmit diversity benefits by sharing their physical resources through a virtual transmit and receive antenna array. The major benefit of this technique includes the diversity – because different paths are likely to fade independently, beam forming gain and interference mitigation [1] [3]. II. FUNDAMENTALS A. Introduction to Cooperative Relaying We consider scenarios as depicted in Figure 1, which include a single relay and where all nodes feature only a single antenna. As is true for all relaying protocols, cooperative relaying schemes suffer from the “orthogonality constraint”2, calling for the assignment of orthogonal resources for reception and transmission at the relay. Without loss of generality, we focus on the time division case and divide the available channel into two orthogonal sub channels in the time domain. Note that in order to achieve the same end-to-end spectral efficiency, we then need to double the spectral efficiency on each of the individual links in this case. Fig. 1. Illustration of a cooperative relaying scenario. The source sends a broadcast message to destination and relay. The relay then forwards additional information about the source message to the destination, which appropriately Cooperative relaying protocols[5] can be classified according to their forwarding strategy as: 1) Amplify-and-Forward: The relay acts as an analog repeater, resulting in noise enhancement in the relay path. 2) Decode-and-Forward: The relay fully decodes, again encodes and retransmits the received message, possibly propagating decoding errors that may lead to a wrong decision at the destination. 3) Decode-and-Reencode: The relay fully decodes the received message, but constructs a codeword differing from the source codeword – thus enabling parallel channel coding. This approach can be seen as an distributed incremental redundancy technique. The main problem is again error propagation. Protocols that require the relay to decode the received message are clearly favorable for implementation purposes since amplify-and-forward style protocols require either the storage of large amounts of analog data (time division) or complicated and expensive transceiver structures (frequency division). The reader is referred to [4] for a detailed discussion of advantages and disadvantages. We may further categorize the transmission schemes based on the protocol nature: 1) Fixed Protocols where the relay always forwards (a processed version of) its received message,2) Adaptive Protocols where the relay uses a threshold rule to decide autonomously whether to forward or not, and 3) Feedback Protocols where the relay only assists the transmission when explicitly required by the destination. A combination of these options yields 9 different cooperative relaying protocols. Static Amplify-and-Forward networks have been extensively discussed in [6], a number of Amplify and Decode-and-Forward protocols have been thoroughly
  2. 2. International Journal of Computer Science & Information Technology 2 investigated in [11] and Decode-and-Reencode protocols have been the subject of evaluation in [9], [15]. B. Combining Type[6] 1. Equal Ratio Combining (ERC) : If computing time is a crucial point, or the channel quality could not be estimated, all the received signals can just be added up. 2. Fixed Ratio Combining (FRC): A much better performance can be achieved, when fixed ratio combining is used. Instead of just adding up the incoming signals, they are weighted with a constant ratio, which will not change a lot during the whole communication. The ratio should represent the average channel quality. 3. Signal to Noise Ratio Combining (SNRC) A much better performance can be achieved, if the incoming signals are weighted on an intelligent way. An often used value to characterize the quality of a link is the SNR, which can be used to weight the received signals. 4. Maximum Ratio Combining (MRC) The Maximum Ratio Combiner (MRC) achieves the best possible performance by multiplying each input signal with its corresponding conjugated channel gain. This assumes that the channels' phase shift and attenuation is perfectly known by the receiver 5. Enhanced Signal to Noise Combining (ESNRC): Another combining method is to ignore an incoming signal when the data from the other incoming channels have a much better quality. If the channels have more or less the same channel quality the incoming signals are rationed equally. III. RESULTS AND DISCUSSIONS The performance of different combinations of the methods are analyzed to illustrate their potential benefits. In this part, it is assumed that the three stations (sender, relay and destination) have an equal distance from each other and therefore the same path loss and average signal-to-noise ratio is assumed. With this equidistant arrangement the different combining and amplifying types are compared to see their advantages and disadvantages. A. Equidistant Arrangement: In this section it is assumed, that the three stations are arranged at the edges of a triangle with a length of one. This means that all the channels will have the same path loss and therefore the same average signal-to-noise ratio Amplify and Forward To compare the benefits of the different combining method, the optimal ratio for the FRC needs to be evaluated first. Fig. 3.1 illustrates the effects of the different weighting. In Fig. 3.2 the effect on the performance of the different combining types using a AAF protocol can be seen. The first pleasant result is that whatever combining type is used, the AAF diversity protocol achieves a benefit compared to the direct link. Even the equal ratio combining shows advantages. But compared to the fixed ratio combining, the performance looks quite poor. Otherwise you should call to mind that the equal ratio combining does not need any channel information, except the phase shift, to perform the combining. The fixed ratio combining on the other hand, needs some channel information to calculate the appropriate weighting. The signal-to-noise ratio combining (SNRC) and the enhanced signal-to-noise ratio combining (ESNRC) show roughly the same performance, which is much better then the one using FRC/ERC.Using the AAF protocol, there is no point in wasting a lot of computing power and bandwidth to get some exact channel information. And even if the channel quality could not be estimated at all (and therefore ERC is used), there is still a benefit using diversity. Decode and Forward The FRC is simulated with different weighting to estimate the ratio that results in the best performance. The simulations, illustrated in Fig. 3.3, show the best performance when a ratio of 3:1 is used. It is quite surprising that this ratio differs that much from the ratio using AAF. Figure 3.1: To estimate the best ratio for FRC different ratios are plotted.The ratio 2:1 gives a good result Figure 3.2: The different combining types are compared with each other. The best performance results when using SNRC/ESNRC. The FRC with a ratio of 3:1 can now be used to compare with the other combining methods. The different combining methods using the DAF protocol are illustrated in Fig. 3.4 In contrast to the AAF protocol, a big benefit results using one of the block analyzing combining methods (SNRC/ESNRC). Using the DAF protocol shows now the benefit estimating every single block separately and hence using more computing power. There is now an additional benefit, to estimate every block precisely when using SNRC, instead of just approximating the channel quality combining the signals with ESNRC. But considering that the achievable benefit is about half a decibel it might not be worth wasting the additional computing power and bandwidth which is
  3. 3. International Journal of Computer Science &Information Technology 3 required to get precise channel estimation. If AAF is used, there is no benefit at all, using the SNRC instead of ESNRC. Figure 3.3: To estimate the best ratio for FRC Different ratios are plotted. The ratio 3:1 results in the best performance. Figure 3.4: The different combining types are compared with each other. The best performance results when using SNRC. IV CONCLUSION The AAF protocol has shown a better performance than the DAF protocol whatever combining method was used at the receiver. But it must be considered that no error correcting code was added to the transferred signal. Therefore it was not possible to take full advantage of the DAF protocol. To get an idea of the potential of the DAF protocol the magic genie was introduced to simulate an error correcting code. The performance of a system using the DAF protocol in combination with a magic genie was much better than one using the AAF protocol. REFERENCES 1. A. Nosratinia, T. E. Hunter, A. Hedayat, “Cooperative Communications in Wireless Networks”, IEEE Communications Magazine, 2004, pp. 74-80. 2. M. Uysal, “Cooperative Communications for Improved Wireless Network Transmission”, Information Science Reference, July 2009. 3. G. K. Karagiannidis, C. Tellambura, S. Mukherjee, A. O. Fapojuwo, “Editorial - Multi-user Cooperative Diversity for Wireless Networks”, EURASIP Journal on Wireless Communications and Networking. 4. E. Zimmermann. “On the cooperative exploitation of spatial diversity in wireless networks”, Dresden University of Technology, Vodafone Chair Mobile Communications Systems, April 2003. 5. Ernesto Zimmermann, et al “On the Performance of Cooperative Relaying Protocols in Wireless Networks”, Dresden University of Technology, Vodafone Chair Mobile communications Systems, Germany 6. Dr John Thompson et al “Cooperative Diversity in Wireless Networks” in March 2004.