CHAPTER I: WIRELESS CHANNEL MODEL 1.1 Path Loss 1.1.1 Theory The decline in power density (attenuation) of an electromagnetic wave as it propagates over space is known as path loss or path attenuation. Path loss is an important factor to consider while analyzing and designing a telecommunication systems link budget. In wireless communications and signal propagation, this word is frequently used. Freespace loss, refraction, diffraction, reflection, aperturemedium coupling loss, and absorption are all possible causes of path loss. Terrain contours, environment (urban or rural, flora and foliage), propagation medium (dry or wet air), distance between transmitter and receiver, and antenna height and position are all factors that affect path loss. 1.1.2 Cause Path loss typically includes propagation losses due to the natural expansion of the radio wave front in free space (which usually takes the shape of an everincreasing sphere), absorption losses (also known as penetration losses) when the signal passes through media that are not transparent to electromagnetic waves, diffraction losses when part of the radiowave front is obstructed by an opaque obstacle, and losses due to other phenomena. Path loss typically includes propagation losses due to the natural expansion of the radio wave front in free space (which usually takes the shape of an everincreasing sphere), absorption losses (also known as penetration losses) when the signal passes through media that are not transparent to electromagnetic waves, diffraction losses when part of the radio wave front is obstructed by an opaque obstacle, and losses due to other phenomena. 1.2 Shadowing The route loss model discussed in the preceding section seeks to calculate the path loss in a deterministic manner for a given transmitter and receiver position. In actuality, the position of a receiver includes the topography as well as the objects that surround the transmission line. Measurements were taken under a variety of situations, with statistical variances noted. Different levels of the received signal power were measured at a certain frequency and distance. As a result, the received signal power is not predictable for a given fixed distance, frequency, and transmission power, but fluctuates according to objects in and surrounding the signal path. Shadowing is the name for these stochastic, locationdependent changes. Its worth noting that these stochastic fluctuations are constant in time as long as the receiver and his surroundings remain stationary. The term shadowing refers to the disparity between the observed received signal strength and the theoretical value estimated using route loss calculations. However, averaging numerous received signal power levels for the same distance produces the precise route loss value. The fluctuations of the recorded signal level compared to the average anticipated route loss were determined using path loss measurements for a variety of settings and distances. It has a normal distribution with a 0 mean in decibels, implying a lognormal distribution of received power around the path loss mean value. The KolmogrovSmirnov test was used to verify this hypothesis, and it was confirmed to be valid with large confidence intervals. The theoretical underpinning for the lognormal distribution is that in an environment with surrounding objects, different signals travel across the propagation medium with random re ections and diractions. The additional loss in each path, expressed in decibels, is equal to subtracting a random loss from the path loss value. The total of all the dB losses for a large number of propagation pathways converges to a normally distributed random variable (central limit theorem) since the different propagation paths are independent. This becomes a lognormal distribution in natural units. The path loss shadowing fluctuations may thus be computed from the distribution. p(a_SH )=1(σ_SH √2π) exp(a_SH2)(2σ_SH2 ) where σ_SH is the signals variability and all variables are measured in decibels. To obtain the variations, the value of the variation due to shadowing is added to the path loss value. adB= 10∙ log P0Pt= a_PL dB + A_SH dB
HO CHI MINH CITY UNIVERSITY OF TECHNOLOGY AND EDUCATION FACULTY OF HIGH-QUALITY TRAINING REPORT cooperative network COOPERATIVE NETWORK Name of Students Student ID Nguyễn Phúc Tiến 19161030 HO CHI MINH CITY UNIVERSITY OF TECHNOLOGY AND EDUCATION FACULTY OF HIGH QUALITY TRAINING REPORT COOPERATIVE NETWORK Name of Students Student ID Nguyễn Phúc Tiến 19161030 Ho Chi Minh City, 12th, December, 2021 ` DISCLAIMER The information of this project is the opinion or opinion in the article that is of individual group, not influenced or controlled by any company, organization or sponsor The author always tries to provide accurate and truthful information to the best of his knowledge Over time, technology may change so the content of the article may no longer be accurate One very important thing that people often ignore, is that the product is only maximized when in enclosed spaces So if the above condition is not met, the user should accept certain risks if any When reading the content, it means that you have accepted the terms of the author mentioned above COPY RIGHT These articles and content are the copyrights of me (except articles with reference) The author does not agree to arbitrarily take the content of the article to publish or republish on another website If you really want to republish any posts, please quote The author used images found on the internet If any images are copyrighted, the author will always respect ` TABLE OF CONTENTS ` LIST OF FIGURES Chapter Chapter LIST OF ABBREVIATION Multiple-input, multiple-output (MIMO) Frequency modulation (FM) ` Two-wave with diffused power (TWDP) Amplify-and-Forward (AF) Decode-and-Forward (DF) Compress-and-Forward (CF) Signal-to-noise ratio (SNR) Multi-hop Decode-and-Forward (MDF) Orthogonal frequency-division multiplexing (OFDM) single frequency networks (SFNs) Diversity DF (DDF) adaptive relaying protocol (ARP) fractional incremental relaying (FIR) negative acknowledgment (NACK) acknowledgment (ACK) Maximal Ratio Combining (MRC) carrier-to-noise ratio (CNR) Equal-gain Combining (EGC) wireless ad hoc network (WANET) Wireless sensor networks (WSNs) Multi-hop Amplify-and-Forward (MAF) Switched Combining (SWC) Selection Combining (SC) Very high frequency (VHF) Ultra high frequency (UHF) INTRODUCTION Data communication over wireless networks is a field that is gradually advancing in both directions magic and applicability This is the spearhead in the information ` and communication industry now and in the future However, the transmission of information through radio channels is not guaranteed for many reasons such as weather and terrain In practice, the signal is transmitted from the transmitter to the receiver along many different paths, causing random fluctuations in the amplitude, phase, and angle of incidence of the received signal, a phenomenon known as multipath fading The influence of multipath fading on signal transmission quality is very large This problem has received a lot of research attention and various methods have been proposed to limit the effect of this fading such as using diversity techniques MIMO However, with each method there are disadvantages This report will present another method to reduce the effects of fading, which is Multi-hop Communication, which is a relatively new technique The main idea of this technique is to split the transmission path between the source node and the destination node by using intermediate nodes in the middle (relay) to relay the signal Node relay in addition to signal transmission is also responsible for amplifying and transmitting, decoding, and transmitting to expand the coverage area improve the quality of the system This is also an issue worthy of attention and research CHAPTER I: WIRELESS CHANNEL MODEL 1.1 Path Loss ` 1.1.1 Theory The decline in power density (attenuation) of an electromagnetic wave as it propagates over space is known as path loss or path attenuation Path loss is an important factor to consider while analyzing and designing a telecommunication system's link budget In wireless communications and signal propagation, this word is frequently used Free-space loss, refraction, diffraction, reflection, aperture-medium coupling loss, and absorption are all possible causes of path loss Terrain contours, environment (urban or rural, flora and foliage), propagation medium (dry or wet air), distance between transmitter and receiver, and antenna height and position are all factors that affect path loss 1.1.2 Cause Path loss typically includes propagation losses due to the natural expansion of the radio wave front in free space (which usually takes the shape of an ever-increasing sphere), absorption losses (also known as penetration losses) when the signal passes through media that are not transparent to electromagnetic waves, diffraction losses when part of the radiowave front is obstructed by an opaque obstacle, and losses due to other phenomena Path loss typically includes propagation losses due to the natural expansion of the radio wave front in free space (which usually takes the shape of an ever-increasing sphere), absorption losses (also known as penetration losses) when the signal passes through media that are not transparent to electromagnetic waves, diffraction losses when part of the radio wave front is obstructed by an opaque obstacle, and losses due to other phenomena 1.2 Shadowing The route loss model discussed in the preceding section seeks to calculate the path loss in a deterministic manner for a given transmitter and receiver position In actuality, the position of a receiver includes the topography as well as the objects that surround the transmission line Measurements were taken under a variety of situations, with statistical variances noted Different levels of the received signal power were measured at a certain frequency and distance As a result, the received ` signal power is not predictable for a given fixed distance, frequency, and transmission power, but fluctuates according to objects in and surrounding the signal path Shadowing is the name for these stochastic, location-dependent changes It's worth noting that these stochastic fluctuations are constant in time as long as the receiver and his surroundings remain stationary The term "shadowing" refers to the disparity between the observed received signal strength and the theoretical value estimated using route loss calculations However, averaging numerous received signal power levels for the same distance produces the precise route loss value The fluctuations of the recorded signal level compared to the average anticipated route loss were determined using path loss measurements for a variety of settings and distances It has a normal distribution with a mean in decibels, implying a lognormal distribution of received power around the path loss mean value The Kolmogrov-Smirnov test was used to verify this hypothesis, and it was confirmed to be valid with large confidence intervals The theoretical underpinning for the log-normal distribution is that in an environment with surrounding objects, different signals travel across the propagation medium with random re ections and diractions The additional loss in each path, expressed in decibels, is equal to subtracting a random loss from the path loss value The total of all the dB losses for a large number of propagation pathways converges to a normally distributed random variable (central limit theorem) since the different propagation paths are independent This becomes a log-normal distribution in natural units The path loss shadowing fluctuations may thus be computed from the distribution where is the signal's variability and all variables are measured in decibels To obtain the variations, the value of the variation due to shadowing is added to the path loss value 1.3 Fading Fading is the fluctuation of a signal's attenuation with numerous factors in wireless communications Time, geographic location, and radio frequency are among ` the factors Fading is frequently shown as a chaotic process A communication channel that fades is known as a fading channel Fading in wireless networks can be caused by multipath propagation (also known as multipath-induced fading), weather (especially rain), or shadowing from barriers impacting wave propagation (also known as shadow fading) Fading is the fluctuation of a signal's attenuation with numerous factors in wireless communications Time, geographic location, and radio frequency are among the factors Fading is frequently shown as a chaotic process A communication channel that fades is known as a fading channel Fading in wireless networks can be caused by multipath propagation (also known as multipath-induced fading), weather (especially rain), or shadowing from barriers impacting wave propagation (also known as shadow fading) Stopping at a traffic light and hearing an FM broadcast degrade into static is a classic example of deep fade, as the signal is re-acquired if the car drives only a fraction of a meter The truck came to a halt at a spot where the signal was subjected to strong destructive interference, resulting in the loss of the transmission Similar brief fades can also be seen on cellular phones In cellular networks and broadcast communication, fading channel models are frequently used to simulate the effects of electromagnetic transmission of information over the air Fading channel models are often used to mimic the distortion induced by the water in underwater audio communications 1.3.1 Models of fading: 1.3.1.1 Nakagami distribution: The Nakagami distribution, also known as the Nakagami-m distribution, is a gamma-like probability distribution There are two parameters in the Nakagami distribution family: a shape parameter a second parameter that controls spread The Nakagami distribution is a relatively recent concept, having been suggested for the first time in 1960 It has been used to analyze the influence of fading channels on wireless communications and to model attenuation of wireless signals travelling numerous pathways 10 ` CHAPTER II: COOPERATIVE COMMUNICATION 2.1 Cooperative Communication Protocol Consider the three-node network in Figure, where the source is connected to a relay and a destination, and the channels between the nodes are hsr, hsd, and hrd, respectively The relay can now assist in the transmission of information in a variety of ways Figure 1: The fundamental relay channel The relay amplifies the received signal by a specific factor and retransmits it in Amplify-and-Forward (AF) The relay decodes the packet and then re-encodes and retransmits it in Decode-and-Forward (DF) In Compress-and-Forward (CF), the relay makes a quantized (compressed) version of the signal it receives from the source and sends it to the destination, where it is combined with the directly transmitted signal from the source In the following, we'll assume that all relaying nodes work in halfduplex mode, which means they can't send and receive in the same frequency range at the same time This is understandable because wireless signal transmit and receive levels are sufficiently dissimilar that the sent signal would "swamp" the RX, making it difficult to identify the receive signal These relay processing methods may now be paired with a variety of transmission protocols that specify when and from which nodes certain information blocks are transferred We've arranged them in ascending order of performance (and at the same time of increasing complexity) 15 ` 2.1.1 Decode-and-Forward DF is the most essential of all the relaying techniques Before re-encoding and retransmitting a packet, the relay receives it and decodes it, removing the impacts of noise Following that, we'll look at the capacity of a few of the implementations Multi-hop Decode-and-Forward is the most straightforward strategy to examine (MDF) If we assume constant transmit power and equal time splitting between the two phases, the overall data rate per unit bandwidth is Ps and Pr are the source and relay powers, respectively, while Pn is the noise power In other words, the link with the lowest Signal-to-Noise Ratio SNR becomes the "bottleneck" that decides total capacity; the half-duplex limitation is responsible for the factor 1/2 The capabilities of the source-relay and relay-destination links are terminology used inside the operation A data packet must travel through both lines for a transmission to be successful; the link with the lower capacity is thus the bottleneck that determines the possible trans- mission rate The values of Ps and Pr can be fixed or can be optimized given the power constraints and the values of the channel coefficients hsr and hrd In the latter case the powers should be adjusted in such a way that the capacity of the source-relay link is the same as the one for the relay-destination link, i.e., Further improvements to this approach (as well as the ones discussed below) can be made by separating a data transmission time slot into unequal portions and optimizing the length of those two sections The destination listens throughout both phases of Diversity-Decode-and-Forward (DDF), allowing it to sum up the signals received from the source (phase 1) and the relay (in phase 2) Then there are two significant examples to consider: Repetition coding transmission from the relay: in this situation, the relay employs the same encoder as the source As a consequence, the source can add up the received signals before decoding, improving the SNR Assume that the subsequent restriction transmission is successful only if the message from both the source and the 16 ` relay is received successfully by the destination In that situation, the greatest pace that may be achieved is and its best power distribution is A smarter protocol would only use the relay if it can genuinely aid, otherwise it would be idle Adaptive DDF is the name of such a protocol "Incremental relaying," in which the relay does not send if the destination can already decode the packet after the first transmission phase, achieves even greater performance Transmission from the relay using incremental-redundancy encoding: the relay decodes the packet and re-encodes it using a different coder in this scenario Intuitively, the RX can sum the mutual information from the two transmission phases – in other words, it perceives a low-rate code in which certain information bits and parity-check bits come in the first phase and some in the second Such a protocol's capability is We define the entire system as being in outage if the attainable rate falls below the required threshold Rth, using the idea of outage capacity In the case of nonadaptive DDF, the likelihood of such an outage is 17 ` The first term on the right-hand side corresponds to the case where the sourcerelay connection is too weak (since the protocol requires the relay to transmit in the second phase anyway, this causes an outage), and the second term corresponds to the case where the source-relay connection is strong enough, but the relay-destination and source-destination connections are too weak to sustain sufficient information flow to the destination Because the system's numerous linkages are independent, the probabilities add up If all of the connections are Rayleigh fading, the first component dominates in the limit of large SNRs since it only gives diversity order 1; the second term vanishes if either the source-relay or the relay-destination link is of sufficient quality The overall diversity order is due to the protocol's requirement that the source-relay link be of sufficient strength Diversity order may be accomplished using adaptive DDF: two independent pathways (source-destination or source-relaydestination) are available, and transmission is successful if any of those paths delivers sufficient quality 2.1.2 Amplify-and-Forward The essential premise of AF is that the relay amplifies the (noisy) signal yr that it receives with a gain; yr is not manipulated in any other way (like decoding, demodulating, etc.) The AF processing at the relay is thought to cause a half-time slot delay Thus, the signal received at the destination in the first phase is just the (attenuated) signal from the source plus noise (additional words exist for Intersymbol interference Amplify-and-Forward (IAF), which we will not discuss further) The signal in the second phase is the sum of the source's direct signal and the relay's signal, which is the amplified source word from the previous phase that position: where xs and x2 signify the source and relay transmit signals, respectively, superscript (1) and (2) denote the first and second transmission phases, respectively, and nr and nd imply noise at the relay and destination, respectively (xs(2) can be zero, depending 18 ` on the protocols given above) Power limits limit the amplification factor We demand that if there is an immediate power limitation, The limitation must be averaged across the fading realizations in the case of an instantaneous power constraint The delay of a completely analog repeater is actually considerably lower in practice Despite the scheme's apparent simplicity, there are a variety of alternative protocol implementations, as seen in the categorization above Let's look into Multi-hop Amplify-and-Forward (MAF) performance with Pr = Ps = P first During the first phase, the signal arriving at the RX is just the source signal multiplied by the channel coefficient hsd, and the noise has variance Pn The signal arriving at the destination in the second phase is the source signal multiplied by hsrhrd, and the noise has variance As a result, the SNR is simply = P|hsrhsd|2 /P’ However, in MAF, the optimal power allocation is provided by We want to combine the signals from the two phases in Diversity-Amplify-andForward (DAF) to maximize the SNR, i.e., we want to maximum-ratio combining As a result, the first phase's signal must be increased by i.e., phase-adjusted and multiplied by the square root of the receive SNR at that time The signal from the second phase must be amplified by using a similar motive 19 ` The equivalent SNRs for the two phases, assuming Ps = Pr = P, are And As always with Maximum Ratio Combining (MRC), the total SNR = + The capacity as a result is log2(1 + ), where the factor 1/2 comes from the relay's halfduplex limitation The method also exhibits diversity order since the signal might reach the target through two separate paths: directly or through the relay However, the direct approach is not particularly beneficial for coverage extension relays with reasonable SNRs (as opposed to the infinite SNRs used for diversity order calculations) — if we could get good reception with the direct way, we wouldn't need the relay in the first place 2.1.3 Compress-and-Forward CF and AF are similar in that the relay does not decipher messages but instead passes everything it gets (including noise) The forwarded signal is a quantized, compressed version of the signal received at the relay, which is the major distinction from AF The quantization and compression process may be viewed as a source encoding issue, in which the received signal is a (analog) source whose information should be encoded into a digital signal with as few distortions as feasible – but the rate at which that signal can be delivered is restricted (and depends on the relay-destination channel) This signal is combined with the signal received directly from the source node at the destination to rebuild the original signal For some channel configurations, CF has been demonstrated to provide more capacity than DF or AF It is, however, far more involved than any of those forms, and as a result, it will not be discussed further in this essay The sources listed at the conclusion of the chapter provide more information 20 ` 2.3 Cooperative Relaying Protocols: 2.3.1 Adaptive Relaying Protocols: A simple adaptive relaying protocol (ARP) that combines the benefits of both the DF and AF protocols while minimizing their drawbacks All relays in the proposed scheme are assigned to one of two relay groups: the DF relay group or the AF relay group The DF relay group contains all relays that can successfully decode the signals delivered from the source, whereas the AF relay group contains all relays that cannot decode the signals correctly The AF relay group's relays all amplify and transmit the received signals from the source, whereas the DF relay group's relays decode, reencode, and forward the received signals to the destination The ARP is processed in the same way as the AF and DF at the destination All signals sent from the relays in both the AF and DF groups arrive at the destination and are merged into one signal The source data can then be recovered using a Viterbi decoding technique The suggested ARP's performance is evaluated and compared to that of other relaying protocols It is demonstrated that the suggested ARP method outperforms the AF scheme and avoids error propagation caused by faulty decoding at relays in a DF protocol, therefore outperforming both the AF and DF protocols At high signal to noise ratios, this performance benefit improves as the number of relays increases, and eventually approaches perfect DTC (SNR) 2.3.2 Incremental Relaying Feedback from the destination concerning the success or failure of direct transmission is utilized in incremental relaying Only when direct transmission fails is the relay allowed to send the signal; otherwise, the source proceeds with the next message, decreasing the total time for transmission from two to one time slot The spectral efficiency of incremental relaying improves Incremental relaying protocols, also known as hybrid automatic-repeat-request protocols, are extensions of incremental redundancy techniques (ARQ) By re-transmitting partial information from relays, the fractional incremental relaying (FIR) protocol enhances spectral efficiency even more If the destination is unable to decode the packet correctly, as signaled by a negative acknowledgment (NACK) from the destination, the relay breaks the received packet into fractions and transmits a fraction The relay continues 21 ` to deliver the next fraction until it receives an acknowledgement (ACK) from the destination or reaches the maximum number of relay transmissions 2.4 Combining Strategies There are two types of combining techniques used to integrate several diversity branches in the reception: post-detection combining and pre-detection combining In pre-detection combining, the signals from diversity branches are merged coherently before detection Signals, on the other hand, are detected independently before being combined in post-detection For both combining strategies for coherent detection, the communication system's performance is same However, employing pre-detection combining for non-coherent detection improves the performance of the communication system In the case of coherent modulation, this means that the kind of combining technique has no influence on performance In non-coherent detection, post-detection combining is not difficult, and the findings are widely used 2.4.1 Maximal Ratio Combining (MRC): To fight channel fading, this is a highly helpful combining technique In comparison to other ways, this is the best combining procedure for achieving the best performance improvement The MRC is a widely used combining method for improving performance in noise-limited communication systems in which the AWGN and fading are independent among the diversity branches The MRC, on the other hand, requires summing circuits, weighting, and co-phasing Before summing or combining, the signals from separate diversity branches are co-phased and weighted in the MRC combining process To maximize the overall carrier-to-noise ratio, the weights must be proportionate to the separate signal levels (CNR) The weighting used to the diversity branches must be changed based on the SNR It is possible to use MRC in the transmit diversity transmission method However, in this instance, the transmitter should get accurate feedback on the condition of the sub-channels between a single receive antenna and numerous transmit antennas In a mixed transmit-receive diversity channel, however, it is not possible to weight broadcasts from many antennas appropriately for each receiving antenna Furthermore, if a communication system's interference is minimal, a method that mixes the diversity branches in order to optimize the signal-to-interference-plus-noise 22 ` ratio may give significantly greater performance than MRC If we can see noise power at the receiver where only thermal noise is accounted for, the assumption holds true for spatially white Gaussian noise The thermal noise power is uncorrelated and equal for each branch if we utilize the same type of antenna components Figure 2: Maximal Ratio Combining 2.4.2 Equal-gain Combining (EGC): The most optimal diversity combining strategy is MRC, however it necessitates a highly costly receiver circuit design to adjust the gain in each branch For the sophisticated fading, it requires adequate tracking, which is extremely difficult to perform realistically It is, nevertheless, relatively simple to achieve equal gain combining using a simple phase lock summing circuit The EGC is identical to the MRC except that it does not have the weighing circuits Because there is an opportunity to blend signals with interference and noise with high quality signals that are interference and noise free, the performance improvement in EGC is slightly smaller than in MRC In the reception of diversity, the EGC can use coherent modulation In EGC, diversity channels' envelope gains are ignored, and the diversity branches are concatenated with equal weights but conjugate phase Because the channel's envelope gain is not estimated, the structure of equal-gain combining (EGC) is as follows 23 ` Figure 3: Equal-gain Combining 2.4.3 Selection Combining (SC): Very high frequency (VHF), ultra high frequency (UHF), and mobile radio applications are not suited for MRC or EGC In a constantly changing, multipath fading, and random-phase environment, realizing a co-phasing circuit with accurate and consistent tracking performance is difficult Because of its ease of implementation, SC is a better choice for mobile radio applications than MRC and EGC In SC, the signal level of the diversity branch with the highest signal level must be chosen As a result, the fundamental algorithm of this approach is based on the notion of selecting the best signal from all the signals at the receiver end Even in the presence of a rapid multipath fading environment, steady operation is simple to establish It has been demonstrated experimentally that the performance advantage realized by selection combining is only marginally higher than that provided by a perfect MRC As a result, the SC is the most widely utilized wireless communication diversity approach The most common method of selection combining is to keep track of all the diversity branches and choose the best one for detection (the one with the greatest SNR) As a result, we may argue that SC is a selection technique at the available diversity rather than a combining approach SNR measurement, on the other hand, is tough since the system must pick it in a short amount of time When the average noise power on each branch is the same, picking the branch with the greatest SNR is comparable to selecting the branch with the highest received power As a result, choosing the branch with the most signal composition, noise, and interference is 24 ` realistic Selection combining can also be employed in transmission if feedback information about the channel status of the diversity branch is available Figure 4: Selection Combining 2.4.4 Switched Combining (SWC): In selection combining, monitoring all diversity branches is impractical Furthermore, if we want to continually monitor the signals, we'll need the same number of receivers and branches As a result, selection combining is implemented using the switched combining method The best switching threshold in SWC must be determined When the threshold is set to a very high value, the rate of unwanted switching transients rises If the threshold is set too low, however, the variety benefit will be minimal In the case of frequency hopping systems, the switching of switch combinations can be done on a regular basis The value of threshold selection, the time delay that results from the loop of feedback of monitoring estimation, switching, and decision, and the performance increase gained by the switching technique are all dependent on the value of threshold selection Furthermore, phase transients and a carrier's envelope might limit performance increase The phase transient is responsible for creating mistakes in the detection stream of data in an angle modulation system, such as GSM To eliminate envelope transients in this scenario, a pre-detection band pass filter might be utilized 25 ` CHAPTER III: APLICATION 3.1 Wireless ad hoc network A wireless ad hoc network (WANET) or mobile ad hoc network (MANET) is a form of wireless network that is decentralized Because it does not rely on preexisting infrastructure, such as routers in wired networks or access points in wireless networks, the network is ad hoc Instead, each node contributes in routing by forwarding data to other nodes, thus which nodes forward data is determined dynamically based on network connection and the routing algorithm in use Ad hoc is a communication mode (setting) in the Windows operating system that allows machines to connect directly with one other without the use of a router Wireless mobile ad hoc networks are dynamic, self-configuring networks with nodes that are free to roam The hassles of infrastructure setup and management are removed from such wireless networks, allowing devices to form and join networks "on the fly." Because each device in a MANET is free to travel in any direction, it will regularly alter its links with other devices Each must be a router since it must forward traffic that is not connected to its own usage The key problem in constructing a MANET is supplying each device with the necessary information to appropriately route traffic Due to 1) the desire to route packets to/through every other node, 2) the percentage of overhead traffic required to maintain real-time routing status, 3) each node has its own goodput to route independent of the needs of others, and 4) all must share limited communication bandwidth, such as a slice of radio spectrum, this becomes more difficult as the MANET scales up These networks can be selfcontained or linked to the broader Internet Between nodes, they may include one or more transceivers that are all distinct 3.2 Wireless sensor network Wireless sensor networks (WSNs) are networks of geographically scattered and specialized sensors that monitor and record environmental variables and send the information to a central point Temperature, sound, pollution levels, humidity, and wind are just some of the ambient factors that WSNs may monitor 26 ` These networks are similar to wireless ad hoc networks in that they rely on wireless connection and spontaneous network creation to carry sensor data wirelessly Temperature, sound, and pressure are examples of physical or environmental factors that WSNs monitor Modern networks are bi-directional, gathering data and allowing sensor activity to be controlled Military uses such as battlefield monitoring prompted the creation of these networks Industrial and consumer applications, including as industrial process monitoring and control and machine health monitoring, employ such networks A WSN is made up of "nodes," which can range in number from a few to hundreds or thousands, each of which is connected to additional sensors A radio transceiver with an internal antenna or a link to an external antenna, a microprocessor, an electrical circuit for interacting with the sensors, and an energy source, generally a battery or an integrated form of energy harvesting, are all common components of such nodes Although microscopic proportions have yet to be achieved, a sensor node might range in size from a shoebox to (theoretically) a grain of dust Sensor node prices vary widely, ranging from a few dollars to hundreds of dollars, depending on the complexity of the node Energy, memory, processing speed, and communications bandwidth are all limited by size and cost limits A WSN's architecture can range from a basic star network to a complex multi-hop wireless mesh network Routing or flooding can be used for propagation 27 ` CHAPTER 4: CONCLUSION Cooperative communication based on relay transmission is envisaged for usage in 5G networks, notably in 'green' networks and vehicle networks Cooperative communication reduces energy usage, allowing mobile devices to function for longer periods of time Furthermore, by employing a variety of wireless data standards, it is feasible to increase transmission quality and assure high data rates The strategies for implementing cooperative communication presented in the study range in sophistication and complexity It's safe to expect that using cooperative communication will be one of the approaches to assure the 5G network parameters that weren't accessible in earlier generations of radio communication networks 28 ` REFERENCES Ana Aguiar, James Gross (2003) Wireless Channel Models, Technical University Berlin, Telecommunication Networks Group (7-36) Muhammad Mehboob Fareed and Mohamed-Slim Alouini (2013) Efficient Incremental Relaying, King Abdullah University of Science and Technology (1-2) Md Jaherul Islam Performance Analysis of Diversity Techniques for Wireless Communication System, Blekinge Institute of Technology (4953) Andreas F Molisch, Wireless communications, 2nd Ed., John Wiley & Sons, 2011 Yonghui Li, Branka Vucetic (2006) On the Performance of A Simple Adaptive Relaying Protocol For Wireless Relay Networks, School of Electrical and Information Engineering (2400) Wikipedia (n.d) Path Loss Retrieved from Path loss - Wikipedia Wikipedia (n.d) Fading Retrieved from Fading - Wikipedia 29 ... utilized 25 ` CHAPTER III: APLICATION 3.1 Wireless ad hoc network A wireless ad hoc network (WANET) or mobile ad hoc network (MANET) is a form of wireless network that is decentralized Because it... may monitor 26 ` These networks are similar to wireless ad hoc networks in that they rely on wireless connection and spontaneous network creation to carry sensor data wirelessly Temperature,... These networks can be selfcontained or linked to the broader Internet Between nodes, they may include one or more transceivers that are all distinct 3.2 Wireless sensor network Wireless sensor networks