Delay Aware Of Co Channel Interference Computer Science Essay

Published Date: 02 Nov 2017

Department of Electronics and Communication Engineering

Adhiparasakthi Engineering College, Melmaruvathur.

Chennai, India

[email protected],

[email protected], [email protected]

Abstractâ€"Multi-hop cooperative relay networks have been regarded as a promising path towards future wireless communication background. In the multi-hop cooperative relay network, each node has multiple channels and multiple interfaces have to enhance the Quality of service (QoS) in terms of bandwidth requirement. This facility is affected by the co-channel interference mechanism by taking the packets with simultaneous channels. This co-channel interference (CCI) sin the multi-hop relaying system would reduce the throughput and increase the end to end delay of a packet transmission in fact reducing the network performance. This issue is analyzed by decode and forward mechanism alternatively know as store and forward technique to transport the information. This mechanism implements signal to interference noise model at the channel level at the expected threshold. This would schedule the packet transmission based Signal-to-Interference-plus-Noise Ratio value (SINR) Based on the approach, this would reduce outage between network devices in the relay network.

Keywords â€" Cooperative diversity, decode and forward, multi-branches, co-channel interference, outage probability.

Introduction

The time and spatial diversity, of the cooperative communications appear as a capable technique to enhance system performance in wireless networks. Spatial diversity is typically achieved by using multiple antennas at both the transmitter and the receiver sides. Recently, Multiple Input and Multiple Output (MIMO) communication systems and the related channel coding techniques which are targeted to increase spectrum efficiency (in bps/Hz) and to improve the strength of the wireless link, have been proposed to implement space diversity in the next generation wireless networks However, all these improvements come at the cost of multiple Radio Frequency (RF) front ends at both the transmitter and the receiver [1]-[3].

Furthermore, the number of antennas implemented on small mobile devices might be constrained due to device size and energy constraints. In order to conquer this practical problem of MIMO systems, cooperative communication enables single-antenna device in a multi-user environment to share their antennas and form a virtual multiple-antenna transmitter that allows them to achieve diversity without the requirement of additional antennas at each device. Therefore, while MIMO systems are regarded as a key technology to improve the performance and Capacity of wireless communications over conventional single antenna systems, the concept of cooperative communications has been recently considered as a solution Common to all relaying techniques discussed so far is the store-and-forward operation of the nodes in a relay chain [4]-[5].

Each receiver along this chain exploits only the copy of the information that has been sent by its relevant transmitter, while it discards emissions from other transmitters in the chain. The basic idea of cooperative relaying is to go one step further by exploiting two fundamental features of the wireless medium We consider routing in a multi hop network supported by an infrastructure and communication relations limited to a few hops only. Multiples simultaneous routes become possible, making the choice of routing algorithm important[6]-[9].

Some key properties of wireless environments make design of wireless networks particularly complex and challenging. First, radio signals experience significant attenuation, called path-loss, as well as self-interference, called fading, induced by multipath propagation through a loss medium. communicate over longer distances. wireless network share a common communication medium. Cooperative diversity has normally been studied with respect to the placement of relays and in its number, and allocation of power, typically under conditions of additive white Gaussian noise (AWGN) [1]â€"[6]. On the other hand, co-channel interference often dominates (AWGN) in wireless networks with crowded frequency reuse. Moreover, cooperative diversity schemes can be susceptible to CCI, because, all the relays may use the same carrier frequency in throughout the network .Some studies analysis of cooperative relaying systems have focused on the effect of CCI in terms of signal-to-interference ratio (SIR), while neglect the effect of AWGN [7], and there has been no research considering the effect of both CCI and AWGN. Dual-hop relaying systems have a similar source-relay destination path compared to the cooperative relaying systems considered in this work, but signal combining is not required since a source-to-destination path does not exist.

Figure 2: Layered Protocol Architecture

As a result of this wealthy channel environment, wireless system designers are presented with many challenges. These include, for example: reliably transmitting information among radio terminals; mitigating severe channel impairments such as multipath fading and interference from other users; efficiently allocating and utilizing resources such as power and bandwidth; scaling as the number of terminals in the network grows; and supporting a large and ever-growing number of applications, such as voice, data, and multimedia networking. Engineers have historically partitioned solutions to these problems into a stack of protocol layers, each serving a particular purpose. Figure 2 illustrates these layers, and indicates the functions they usually serve in the wireless setting.

Traditionally, the communication theory, information theory, and signal processing communities have played a role mainly at the Application Layer in the form of source coding and at the Physical Layer in the form of channel coding. From a broader perspective, one can ask whether the particular layers and allocation of functions shown in Figure 2 are appropriate, especially fading mitigation in the PHY Layer and interference management in the MAC Layer, and whether there is a more natural set of abstractions. Indeed, many new results seem to use across the traditional protocol layers, especially in the wireless setting. This phenomenon is perhaps attributable to the rich channel environment, and presents opportunities for cross-fertilization of ideas.

II COOPERATIVE DIVERSITY SCHEME AND RELAY SELECTION

(i).Cooperative Diversity Scheme

Cooperative diversity techniques exploit the spatial characteristics of the network to create transmits diversity, in which the same information can be forwarded through multiple paths towards a single destination or a set of destination nodes. The initial attempts for developing cooperative communications concentrated on physical layer techniques. These approaches refer to the cooperative processing and retransmission of the overheard information at the nodes surrounding the source and the destination [7]. By mutually combining different copies of the same signals transmitted by source and relay nodes, the destination can improve its ability to decode the original packets.

However, the innovation of cooperative communications is not confined only to the physical layer schemes. To efficiently take the advantage of physical layer information, such mechanisms also require investigation on relaying techniques used for mutually exchanging data, on multiple access methods to schedule the transmission and minimize overhead, on coding schemes used for packets combining and error correcting these packets prior to forwarding, and on the additional scenario factors introduced by cooperation . It is worth noting that if the MAC protocol is not appropriately designed for cooperative communication, the cooperative gain may diminish or even disappear.MAC layer for higher throughput and more reliable communication instead of only studying the advantages of cooperation at the physical layer.

A more general scenario was all the nodes affected by CCI, and the all signals have Rayleigh fading with different local mean, but the effect of Additive White Gaussian (AWGN) was not considered. DF cooperative relaying system using MRC was analyzed for links affected by AWGN, where all the desired signals experience Rayleigh fading with different local mean power. DF cooperative relaying systems using Maximal Ratio Combining ( MRC )were analyzed when the links are affected by CCI , in the case of Nakagami fading where both the desired and interfering signals have a Nakagami-𝑚 distribution with different local mean power and 𝑚-factor. However, the analysis neglected AWGN and the outage probability was expressed in terms of a hyper geometric function.

Figure 2: Multi relay cooperation model

Moreover, there was no comprehensive study of the effect of CCI on the outage performance in Figure 2.The performance analysis of DF cooperative relaying systems in the presence of both CCI and AWGN is very limited, and most expressions for the outage probability involve special functions or infinite series. This work studies the outage probability of DF cooperative relaying systems using MRC in the presence of CCI and AWGN for non-identical Nakagami faded links, i.e., all links have different local mean power and Nakagami- 𝑚 factor for both the desired and interfering signals. the outage performance is analyzed for three different environments, an interference dominant environment where the interference power dominates the noise power; an equal interference and noise environment, i.e., the interference power is equal to the noise power; a noise dominant environment where the noise power dominates the interference power. Finally, the effect of imbalanced powers of CCI received at the relay and the destination is analyzed with various Nakagami-𝑚factors and different numbers of relays, to gain insight as to whether the relay or destination is more sensitive to CCI and, hence, more critical in the end-to-end outage performance.

(ii).Optimal Relay Selection

Relay selection is an essential procedure for cooperative communications. A relay can be selected according to its instantaneous channel gains on the basis of a real valued metric that is a function of the relay-destination channel gain, the source relay channel gain, or both. An illustration of network model for relay selection is below Figure 3.

Figure 3: Network model for relay selection.

The relay selection algorithm, the source node monitors its neighbor’s and dynamically determines a relay as the one which exhibits the best link quality. This is the optimal single relay selection scheme. The error rate of this scheme is first discussed in which an approximation on the cumulative density function of the received SNR is used. Then, a rigorous upper bound on the error rate of this scheme is given the nearest neighbor selection is proposed, in which the relay Cooperative Communications and Relay Selection that is the closest to the destination cooperates. In those two papers, DF is used and node spatial positions are considered. Although this selection criterion might not be optimal in all scenarios, it is very simple to be implemented in a distributed manner and can achieve high performance.

(iii).Optimal Number Of Relays

While most of relay selection schemes focus on a single relay selection, i. e., only one of the relay nodes cooperates, another alternative is to use multiple relay nodes so that both spatial diversity and time diversity can be obtained since relay nodes are spatially distributed. It is demonstrated that with proper design of cooperative multiple access control protocol, multiple relay strategy outperforms single relay scheme. For networks with a large number of relay nodes, say n, as Each relay has two choices; there will be 2n −1 possibilities of cooperation’s (the Case that no relay cooperates is obviously excluded). Even though the destination node knows all the channels so that it could find the optimal solution by exhaustive Search, the computational complexity of this exhaustive search is expensive.

ll. SYSTEM AND CHANNEL MODEL

The multi branch dual hop cooperative relaying network shown in Figure 2. The system consists of a source S, a destination D, and multiple relays ,= 1, 2, …, where M denotes the maximum number of relays. Co-channel interferers affected all the relays and destination I, = 1, 2, …., 𝐿 where 𝐿 is the number of interferences. the received signals of the source-to-destination, source-to-relay, and relay-to-destination paths are,

SD = S + D + ,

S = S + +

D = ( ) + +

,

where, , and represent the transmit powers of the source, the-th relay, and the -th interferer, respectively. The AWGN 𝑛 has a zero mean and a variance in all links, and is the transmitted symbol with unit power. The channel gain can be denoted as

,

where is a constant; || has a Nakagami-𝑚 distribution, is the distance between the transmitter and the receiver, and is the path loss exponent. Throughout this paper, and indicate the instantaneous SNR of the source-to-destination, the source to--th relay, the 𝑚- th relay-to-destination, and the source- -th relay-destination links, respectively. The local mean of Rx SNR of the desired signal can be expressed where is the Tx SNR, and E is the statistical long-term average operator. By assuming the normalized channel gain of the source-to-destination link is E= 1, the normalized local mean of Rx SNR of the source-to--th relay and that of the -th relay-to-destination can be expressed by

= , = , ()

Similarly, local mean of Rx INR of the -th interferer-to- -th relay and that of the -th interferer-to-destination can be expressed as

= , = ,()

Correspondingly.the output SINR with MRC is the sum of the individual SINRs of the diversity branches. The output SINR is given by

= = =

Where and are the received powers for the -th desired signal and the -th interfering signal, respectively.

IV SIMULATION RESULTS

The performance of the algorithm is analyzed over a varied range of simulation Parameters. It shows that as the threshold value increase the time spent in 802.11 decreases. This is because the user/device criterion for a strong signal increases, forcing most of the signal strength measurements to be weak and hence the user hand over the another network.

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Figure 4: Packet Loss Rate Analysis

Packet loss rate versus nodes in the Wireless network is plotted in Figure 4. As the Number of nodes increases the packet loss rate is decreases frequently. The plots clearly show that the packet loss rate decreases with increasing maximum threshold and increases with increasing network load. The variation of the average queuing delay. End-to-end packet loss-rate and delay are fundamental network metrics, both of which impact the performance of network applications.

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Figure 5: Bit Error Rate Analysis

SINR range Vs Bit Error Rate plotted in Figure 5. As the Signal - to â€"Interference-plus- Noise Ratio increases, the bit error rate is decreases abruptly. It is the likelihood that a single error bit will occur within received bits, independent of rate of transmission BER has been measured by comparing the transmitted signal with the received signal and computing the error count over the total number of bits. For any given modulation, the BER is normally expressed in terms of signal to noise ratio .

C:\Users\RAMESH\Desktop\change graps\3.pngFigure 6:Outage Probability Analysis

Outage probability Versus TXSINR plotted in Figure 6. Graph shows the time to time variation of outage probability based on the signal strength. The interesting result is that as the number of branches increases, the outage performance gets worse in the low SINR region and a cooperative diversity gain occurs in the high SINR region. The reason for this behavior is that as the number of relays increases under a fixed total power constraint, the individual TX powers decrease, and the impact of the decreased TX power dominates the cooperative diversity gain in the low SINR region.

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Figure 7: Average Throughput Analysis

Throughput range Versus Number of Nodes in the networks is plotted in Figure 7. The decode and forward process to achieve approximately minimum 63% to maximum 67%. In packet switched systems where the load and the throughput always are equal (where packet loss does not occur), the maximum throughput may be defined as the minimum load in bit/s that causes the delivery time (the latency) to become unstable and increase towards infinity. This value can also be used deceptively in relation to peak measured throughput to conceal packet shaping.

V Conclusion and future .work

The effects of noise and interference on the outage probability were analyzed in terms of diversity and channel condition. The results shows that for a given total interference plus noise power, the outage performance is more severely degraded by noise as opposed to CCI for low and moderate SINR, whereas the opposite is true for high SINR and high diversity order. Since with the implementation of decode and forward mechanism, the network performance of the co-channel interference mode obtained. Based on the experimental results It seems to the network throughput is reached up to approximately 67% and minimum of 62%,Outage probability concerns about 0.75to increase the performance at the extend level, We need co-channel aware packet scheduling algorithm to reduce the outage probability and increase the network performance to reach at the extend level. This shall be implemented in phase2 of my project and the performance shall be compared.

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Future Work

To reduce the outage probability

To reduce the pocket loss rate

To reduce the Bit error rate

To improve the average throughput and all this above features develop with the help of co-channel aware packet scheduling algorithm in phase II.