The Transmission Channels Types Computer Science Essay

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Radio communications often need a more elaborated model to reduce fading effects, which affect the power of the signal. This attenuation of the signal is mainly due to an environment of propagation rich in echoes and thus characterized by many multi-paths, but also to the relative movement of the transmitter and involving receiver causing channel temporal variations.

Transmission channels types

Binary Symmetric Channels BSC

The binary symmetric channel (BSC) is a discrete channel of which alphabets of entry and of exit are finished and equal to {0; 1}.

We consider in this case that the channel includes all the elements of the chain ranging between the coder of channel and the corresponding decoder (figure 1)








Figure 1 : Description of Binary Symmetric Channel

We note ak and yk respectively the elements at the entry and the exit of the CBS. If the noise and other disturbances cause statistically independent errors in the binary sequence transmitted with a probability p, then:

Pr(yk = 0|ak = 1) = Pr(yk = 1|ak = 0) = p

Pr(yk = 1|ak = 1) = Pr(yk = 0|ak = 0) = 1-p

The functioning of the BSC is summarized in the form of diagram on figure 2. Each binary character at the exit of the channel depending only on the binary character entering corresponding, the channel is called memoryless.

Figure 2: Binary Symmetric Channel diagram

Additive White Gaussian Noise AWGN

Additive white Gaussian noise (AWGN) is the commonly used to transmit signal while signals travel from the channel and simulate background noise of channel. The mathematical expression in received signal is

r(t) = s(t) + n(t); that passed through the AWGN channel where s(t) is transmitted signal and n(t) is background noise.

An AWGN channel adds white Gaussian noise to the signal that passes through it. It is the basic communication channel model and used as a standard channel model.

Figure 3 : Block diagram of AWGN channel model

Received signals :


Transmitted signal :



Evaluation of BER for AWGN, Rayleigh and Rician Fading Channels under Various Modulation Schemes

A. Sudhir Babu Associate Professor, Department of CSE, PVP Siddhartha Institute of Technology, Vijayawada, India

Dr. K.V Sambasiva Rao Professor and Principal MVR College of Engineering and Technology, Paritala, Vijayawada, India

Fading channels

In wireless communications, fading is deviation of the attenuation affecting a signal. The fading may vary with many factors such as geographical position, radio frequency or delay and is modeled as stochastic processes. We can simply say that a fading channel is a communication channel includes fading.

Causes of fading

In wireless systems, fading may be caused by different physical phenomenon:

Doppler Shift:

When a mobile is moving at a constant velocity Vs along a path, f' is the observed frequency and f is the emitted frequency. All these terms will be related by the following equation:

Missed equation

. Fumiyaki Adachi, "error Rate Analysis of Differentially Encoded and detected 16-APSK under Rician fading", IEEE Transactions on Vehicular Technology, Vol. 45, No. 1, February 1996.

We can say after the above equation that the detected frequency increases when the mobile is moving towards the observer and decreases as the source moves away, this is called the Doppler Effect


Reflection occurs when the electromagnetic wave encounters an object while propagating and generating a subsequent long wavelength compared to wavelength of the propagating wave.

As a result, signal can taking a large number of different path.


Diffraction takes place because of the obstacles of the path radio and irregular edges of a surface between the transmitter and the receiver, even when a Line of Sight does not exist between transmitter and receiver the secondary waves will be spread over the space.


Scattering will be produced when the wave is propagated through a medium consisting of objects of dimension smaller than the wavelength and having larger volumes of obstacles per unit volume.

The scattered waves are produced due to irregularities in the channel and rough surfaces of small objects.

For the different causes of fading, there are panoply types of fading.

Types of fading

We can make out several types of fading according to effect of multipath, effect of Doppler Spread and delay Spread.

According to Doppler Spread

Slow fading

The slow fading can be caused by the large difference between the coherence time of the channel and the delay constraint of the channel.

A large building that obscures the signal path between the transmitter and the receiver can also cause a slow fading.

The amplitude and phase imposed by the channel remain constant over the period of use.

Fast fading

When the coherence time of the channel is smaller than the delay constraint of the channel causes the fast fading. The amplitude and phase change imposed by the channel varies considerably over the period of use.

According to delay spread

There are two types of fading according to the effect of Delay Spread. These are

Flat Fading and Frequency Selective Fading

Flat Fading

We called flat fading the fading that occurs when the band length of the mobile channel is greater than the length of the transmission channel band.

Among the characteristics of such fading is that frequency components of a received radio signal vary in the same proportion simultaneously

Frequency Selective Fading

Partial cancellation of a radio signal by itself causes frequency selective fading.

Indeed, the signal comes through two different paths and at least one of them undergoes a lengthening or shortening.

View that the effect of constellation is deeper at a particular frequency that is constantly changing, the fading frequency selective then appears as a slow cyclic perturbation.

According to multipath

According to the effect of multipath, there are two types of fading:

Large Scale Fading

This type of fading is caused by the gradual variation of the power of the received signal caused by the attenuation of the signal determined by the geometry of the path profile.

Small Scale Fading

Small changes (even smaller than half the wavelength) in the position in the space between the transmitter and the receiver can cause dramatic changes in the amplitude and phase of the signal.

This is called Small-Scale Fading.

There are many models that describe the phenomenon of small scale fading. Out of these models, Rayleigh fading, Ricean fading and Nakagami fading models are most widely used.

Types of Small Scale Fading

Rayleigh fading model

The Rayleigh fading is mainly caused by multipath reception. Rayleigh fading is most applicable when there is no line of sight between the transmitter and receiver.

Ricean fading model

This model seems a lot of Rayleigh model except the strong presence of dominant component is a stationary signal known as LOS (Line Of Sight).

Nakagami fading model

Apparaition of instances of multipath scattering with relatively large delay-time spread, with different clusters of reflected waves encourages the use of Nakagami fading channel.

Always, we find Nakagami m-fading, the parameter m is called the 'shape factor' of the Nakagami.

In the special case m = 1, Rayleigh fading is recovered, with an exponentially distributed instantaneous power

For m > 1, the fluctuations of the signal strength reduce compared to Rayleigh fading.


Diversity techniques can be used to improve system performance in fading channels i.e instead of transmitting and receiving the desired signal through a single channel, there is obtained L copies of the desired signal by M different channels and if some copies may undergo deep fades, others do not.

We might then be able to get enough energy to make the right decision on the transmitted symbol. There are several types of diversity are used in wireless communication systems.

Frequency Diversity

Frequency diversity is the use of multiple frequencies for transmitting the signal. It is a technique used to overcome the effects of multipath fading, At the receiver, the L independently faded copies are combined to give a statistic for decision.

Time Diversity

Another approach to overcome the effect of fading and achieve diversity is to send the same signal in different time periods i.e. each symbol is transmitted repeatedly. The intervals between transmissions of the same symbol should be at least the coherence time so that different copies of the same symbol undergo independent fading.

Spatial diversity

Diversity can also be expected from the use of M antennas are used to receive the M copies of the transmitted signal, this is called MIMO system. The antennae should be spaced far enough apart so that different received copies of the signal undergo independent fading.

This technique does not need additional work at the reception or bandwidth or transmission time additional

Presently, two different forms of MIMO system:

Multi-antenna types

Multi-antenna MIMO technology has been developed and implemented in some standards, e.g. 802.11n products.


A communication model SISO (single input single output) makes it clear that spatial diversity cannot be applied.

However, this case is included to assess its performance in fading channels and to show clearly the advantage of spatial diversity.


SIMO-communication systems (Single Input Multiple Output) use one antenna to the transmitter and multiple antennas at the receiver. Thus, any signal transmitted from the single antenna transmission arrives at all the antennas of the receiver by the various sub-channels. It is assumed that the sub-channels are completely uncorrelated we obtain therefore several independent copies of the same signal arrive at the receiver.


MISO (Multiple Input Single Output) is a special mode of operation of MIMO devices. It is used in NLOS conditions or in a noisy RF. the source antennas are combined to minimize errors and optimize data speed.

MISO technology is used in widespread applications such as digital television (DTV), wireless local area networks (WLANs), metropolitan area networks (MAN) and mobile communications


Technology Multiple-input multiple-output (MIMO) has recently emerged as one of the most important techniques of modern digital communications thanks to its promise of very high data rates, free additional spectrum and transmission power. Wireless communication can be benefited from MIMO in two different ways:

Spatial multiplexing and diversity. In the first case, the data is transmitted from separate antennas in order to maximize throughput. In the second case, the same signal is transmitted along multiple paths fade independently with the aim to improve the robustness of the link BER at each user.

Multi-user types

Multi-user MIMO (MU-MIMO)

Multi-user MIMO (MU-MIMO) is a set of advanced MIMO technologies that exploit the availability of multiple independent radio terminals in order to enhance the communication capabilities of each individual terminal. To contrast, single-user MIMO only considers access to the multiple antennas that are physically connected to each individual terminal. MU-MIMO can be seen as the extended concept of space-division multiple access (SDMA) which allows a terminal to transmit (or receive) signal to (or from) multiple users in the same band simultaneously.

Claude Oestges, Bruno Clerckx, MIMO Wireless Communications: From Real-world Propagation to Space-time Code Design, Academic, 2007.07.16, 448p

MIMO Routing

Routing a cluster by a cluster in each hop, where the number of nodes in each cluster is larger or equal to one. MIMO routing is different from conventional (SISO) routing since conventional routing protocols route a node by a node in each hop.

 S. Cui, A. J. Goldsmith, and A. Bahai (August, 2004). "Energy-efficiency of MIMO and Cooperative MIMO in Sensor Networks". IEEE J. Select. Areas of Commun. 22 

Cooperative MIMO (CO-MIMO)

CO-MIMO, also known as Network MIMO (Net-MIMO), or Ad-hoc MIMO, utilizes distributed antennas which belong to other users.

A cooperative communication system is therefore constituted by distributed wireless nodes interact to transmit information jointly.

Indeed, several terminals radio relaying signals to each other to form a virtual network of antennae, and their collaboration allows exploiting the space diversity of fading channels, which takes then the name of cooperative diversity.

In many wireless applications, users may not be able to support multiple antennas due to size, complexity, power, or other constraints. The wireless medium brings along its unique challenges such as fading and multiuser interference, which can be mitigated with cooperative diversity.

Cooperative communication for wireless networks

Because of its ability to mitigate fading in wireless networks through achieving spatial diversity and resolving the difficulties of installing multiple antennas on small communication terminals, cooperative communications in wireless networks have gained much interest.

Cooperative communication is based on grouping several nodes (each with only one antenna) together into a cluster to form a large transmit or/and receive antenna array. Collaborative clusters are formed in an "ad hoc" fashion by negotiations among neighboring nodes without centralized control. Cooperative diversity naturally arises in ad hoc networks as it enables great power savings with cheap, simple, and mobile nodes, while supporting decentralized routing and control algorithms.

Vladimir Stankovic´, Anders Høst-Madsen, and Zixiang Xiong

Cooperative Diversity for Wireless Ad Hoc Networks [Capacity bounds and code designs]


In traditional cooperative diversity setups, a user is unilaterally designated to act as a relay for the benefit of another one, at least for a given period of time. In [J. N. Laneman and G. W. Womell, "Distributed space-time-coded protocols for exploiting cooperative diversity in wireless networks,"

IEEE Trans. Inform. Theory, vol. 49, no. 10, pp. 2415-2425, Oct. 2003.], Laneman and Wornell proposed different cooperation protocols including fixed and adaptive relaying protocols. In the fixed relaying protocol, such as the amplify-and-forward and decode-and-forward protocols, the relays always help in forwarding the source information.

Wireless Transmission With Cooperation On Demand for Slow and Fast Fading Environments

Kamel Tourki, Mohamed-Slim Alouini, Mazen Omar Hasna. IEEE Trans 2008

The cooperative transmission protocols used in the relay station are either Amplify and Forward (AF) or Decode and Forward (DF). These protocols describe how the received data is processed at the relay station before the data is sent to the destination.

3.1 Amplify and Forward (AF)

This method is often used when the relay has only limited computing time/power available or the time delay has to be minimized. The signal received by the relay is attenuated and needs to be amplified before it can be sent again, and the noise in the signal is also amplified as well, which is the major drawback of this protocol.

//Cooperative Diversity in Wireless Networks

//Erasmus Project at the University of Edinburgh

//Andreas Meier Supervisor: Dr John Thompson

//- March 2004 -

Indeed, the signal amplification is done in block.

Figure 4: Amplify and forward technique

Performance Analysis of Cooperative Communication System with a SISO system in Flat Fading Rayleigh channel Sara Viqar , Shoab Ahmed , Zaka ul Mustafa and Waleed Ejaz National University of Sciences and Technology, Islamabad, Pakistan Sejong University, Seoul, Republic of Korea

3.2 Decode and forward (DF)

Nowadays, relay has enough computing power, so DF is more preferred method to process data in the relay.

In Decode end Forward protocol, the relay decodes the received packet and transmits a fresh codeword using either the same code as the one used at the source or a new one.

So there is no amplified noise in the sent signal, as is the case using AF protocol.

The relay can decode the original message completely. This requires a lot of computing time, but has numerous advantages. If the source message contains an error correcting code, received bit errors might be corrected at the relay station. Or if there is no such code implemented a checksum allows the relay to detect if the received signal contains errors. Depending on the implementation an erroneous message might not be sent to the destination. But it is not always possible to fully decode the source message. The additional delay caused to fully decode and process the message is not acceptable, the relay might not have enough computing capacity or the source message could be coded to protect sensitive data. In such a case, the incoming signal is just decoded and re-encoded symbol by symbol. So neither an error correction can be performed nor a checksum calculated.

Performance metrics

Signal to noise ratio (SNR) and bit error rate (BER) and/or symbole error rate (SER) are common performance metrics for assessing the quality of communication.

4.1 Signal to Noise Ratio SNR

Signal to noise ratio is a relative measure of the signal power compared to the noise power. Assuming gaussian noise model for wireless channels and complex signals, SNR can be defined as

Missed equation 1

[S. Forestier, P. Bouysse, R. Quere, A. Mallet, J. Nebus, and L. Lapierre.

"Joint optimization of the power-aided efficiency and error vector mea-surement of 20-GHz pHEMT amplifier through a new dynamic bias-control method". IEEE Transactions on Microwave Theory and Tech-niques, vol.52(no.4):pp.1132-1140, Apr. 2004.]

Here It and Qt are the in-phase and quadrature signal amplitudes of the M-ary modulations, nI,t and nQ,t are the in-phase and quadrature noise amplitudes of the complex noise being considered

4.2 Bit to Noise Ratio BER

Bit Error Rate (BER) is a commonly used performance metric which describes the probability of error in terms of number of erroneous bits per bit transmitted. BER is a direct effect of channel noise for Gaussian noise channel models. For fading channels, BER performance of any communication system is worse and can be directly related to that of the Gaussian noise channel performance

[L. Hanzo, W. Webb, and T. Keller. Single- and Multi-Carrier Quadrature Amplitude Modulation. Wiley, Chichester, 2nd edition, 2000].

Considering M-ary modulation with coherent detection in Gaussian noise channel and perfect recovery of the carrier frequency and phase, it can be shown that. [L. Hanzo, W. Webb, and T. Keller. Single- and Multi-Carrier Quadrature Amplitude Modulation. Wiley, Chichester, 2nd edition, 2000]

Missed equation2

[K. Ghairabeh, K. Gard, and M. Steer. "Accurate Estimation of Digital

Communication System Metrices - SNR, EVM and ρ in a Nonlinear

Amplifier Environment". IEEE Transactions on Communications, pages

pp.734-739, Sept. 2005.]

where L is the number of levels in each dimension of the M-ary modulation system, Eb is the energy per bit and N0 /2 is the noise power spectral density. Q[.] is the Gaussian co-error function and is given by[A. Goldsmith. Wireless Communications. Cambridge University Press, Stanford University, 1st edition edition, 2005.]

Missed equation3

Assuming raised cosine pulses with sampling at data rate, Equation 2 also gives the bit error rate in terms of signal to noise ratio as


Chapter 2


The relay channel was introduced by van der Meulen [1]E. C. van der Meulen, "Transmission of information in a T -terminal discrete memoryless channel," Ph.D. dissertation, Univ. California,

Berkeley, CA, Jun. 1968.

[2] , "Three-terminal communication channels," Adv. Appl. Probab.,

vol. 3, pp. 120-154, 1971.

, Relay channel model helps a pair of terminal to communicate. This might occur, for example, in a multi-hop wireless network or a sensor network where nodes have limited power to transmit data.

Typical example: Wireless Mesh Network and Relaying


Wireless Mesh Networking known as WMN is originated from the Advanced Tactics Communication System (ATCS) that was proposed jointly by the Defense Advanced Research Projects Agency (DARPA) of the United States Department of Defense and ITT Corporation in 1977, and that integrated wireless networking, routing and positioning functions into one system.

The IEEE 802.11 Working Group set up the Mesh Networking Task Group (802.11s) in January 2004, which marked the beginning of WMN standardization. As an important solution to the "last mile" problem of radio access, the WMN technology is attracting increasing attention. 

Mesh-Based Network Convergence and Cooperation


      Author:Tian Feng, Yang Zhen


The term 'mesh' originally used to suggest that all nodes were connected to all other nodes, but most modern meshes connect only a sub-set of nodes to each other.

Each node operates not only as a host but also as a router, forwarding packets on behalf of other nodes that may not be within direct wireless transmission range of their destinations.

A WMN is dynamically self-organized and self-configured, with the nodes in the network automatically establishing and maintaining mesh connectivity among themselves.

WMNs consist of two types of nodes: mesh routers and mesh clients. Other than the routing capability for gateway/repeater functions as in a conventional wireless router, a wireless mesh router contains additional routing functions to support mesh networking. To further improve the

¬‚exibility of mesh networking, a mesh router is usually equipped with multiple wireless interfaces built on either the same or di¬€erent wireless access technologies. Compared with a conventional wireless router, a wireless mesh router can achieve the same coverage with much lower transmission power through multi-hop communications.

Optionally, the medium access control (MAC) protocol in a mesh router is enhanced with better scalability in a multi-hop mesh environment.

In spite of all these di¬€erences, mesh and conventional wireless routers are usually built based on a similar hardware platform. Mesh routers can be built based on dedicated computer systems

(e.g., embedded systems) and look compact. They can also be built based on general-purpose computer systems (e.g., laptop/ desktop PC).

Mesh clients also have necessary functions for mesh networking, and thus, can also work as a router. However, gateway or bridge functions do not exist in these nodes. In addition, mesh clients usually have only one wireless interface. As a consequence, the hardware platform and the software for mesh clients can be much simpler than those for mesh routers. Mesh clients have a higher variety of devices compared to mesh routers. They can be a laptop/desktop PC, pocket PC, PDA, IP phone, RFID reader, BACnet (building automation and control networks) controller, etc...

Wireless mesh networks: a survey

Ian F. Akyildiz, Xudong Wang, Weilin Wang

Broadband and Wireless Networking (BWN) Lab, School of Electrical and Computer Engineering,

Georgia Institute of Technology, Atlanta, GA 30332, USA

Kiyon, Inc., 4225 Executive Square, Suite 290, La Jolla, CA 92037, USA

Received 1 June 2004; received in revised form 1 November 2004; accepted 20 December 2004

Architectures of WMN

The architecture of WMNs can be classi¬ed into three main groups based on the functionality of the nodes:

Infrastructure/Backbone WMNs

This type of WMNs includes mesh routers forming an infrastructure for clients that connect to them. The WMN infrastructure/backbone can be built using various types of radio technologies, in addition to the mostly used IEEE 802.11 technologies

With gateway functionality, mesh routers can be connected to the Internet. This approach, also referred to as infrastructure meshing, provides backbone for conventional clients and enables integration of WMNs with existing wireless networks, through gateway/bridge functionalities in mesh routers.

Wireless mesh networks: a survey

Ian F. Akyildiz, Xudong Wang, Weilin Wang

Broadband and Wireless Networking (BWN) Lab, School of Electrical and Computer Engineering,

Georgia Institute of Technology, Atlanta, GA 30332, USA

Kiyon, Inc., 4225 Executive Square, Suite 290, La Jolla, CA 92037, USA

Received 1 June 2004; received in revised form 1 November 2004; accepted 20 December 2004

Dash and solid lines indicate wireless and wired links, respectively

Client WMNs

Client meshing provides peer-to-peer networks among client devices. In this type of architecture, client nodes constitute the actual network to perform routing and con¬guration functionalities as well as providing end-user applications to customers. Hence, a mesh router is not required for these types of networks

The basic architecture is shown in Fig.4

Hybrid WMNs

This architecture is the combination of infrastructure and client meshing as shown in Fig. 5.

Mesh clients can access the network through mesh routers as well as directly meshing with other mesh clients. While the infrastructure provides connectivity to other networks such as the Internet, Wi-Fi, WiMAX, cellular, and sensor networks; the routing capabilities of clients provide improved connectivity and coverage inside the WMN. The hybrid architecture will be the most applicable case in our opinion.

One Way Relay


A one-way relay assisted system, in which there is a source, a relay and a destination, and the relay helps the source by forwarding the overheard message to the destination

Channel estimation and optimal resource allocation of relay assisted communication systems

Yupeng Jia - Author

Azadeh Vosoughi - Thesis Advisor

University of Rochester. Dept. of Electrical and Computer Engineering, 2012

Relay channel models

One relay

In this model we have three terminals: Source, destination and the relay node which handles the routing of information to the destination.

Multiple relays

It is known that multiple antennas can greatly increase the capacity and reliability of a wireless communication link in a fading environment.

So recently, it appeared architectures with multiple relays and selection strategies.

Indeed, the source sends the signal to multiple relays and a single relay will be selected to forwarder the message to its correct destination.

The selection procedure is generally based on a calculation of BER (or SER).

For example, we will select the relay that minimizes the BER or the one that minimizes the max of the BER (min max procedure).

Chapter 3


In this contribution we investigate the signal to noise ratios the

user experience in two-way relaying with MIMO amplify and for-ward relays. We derive explicit SNR expressions and study their