Qos In Wireless Communication Computer Science Essay

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In Wireless/Mobile networks various kinds of encoding schemes were used for transmission of data over a bandwidth. In wireless network bandwidth is a scare resource, the system may need to block incoming user if all of the bandwidth has been used to provide highest quality of service to existing users. However, bandwidth resource planning may be unacceptable for larger application. A degradable approach to multiple users can be made on bandwidth allocation to reduce the blocking probability without degrading the quality of service to existing users.

This paper aims towards a realization of a wireless/mobile network using W-CDMA multi access technique supporting multilevel quality of services. The bandwidth allocation to multiple users is adjusted dynamically according to the required network condition so as to increase bandwidth utilization and analyzes the performance of a wireless network.

Index Terms- Band width, W-CDMA, Multi access technique


Cellular wireless technology today has become the prevalent technology for wireless networking. Not only mobile phones but also other types of devices such as laptops and Personal Digital Assistant (PDA) can connect to Internet via cellular infrastructure. These mobile devices are often capable of running multimedia applications (e.g., video, images). Therefore, cellular networks need to provide quality of service (QOS) [1]guarantee to different types of data traffic in a mobile environment. A call admission control (CAC) scheme aims at maintaining the delivered QOS[3] to the different calls (or users) at the target level by limiting the number of ongoing calls in the system. One major challenge in designing a CAC arises due to the fact that the cellular network has to service two major types of calls: new calls and handoff call. The QOS performances related to these two types of calls are generally measured by new call blocking probability and handoff call dropping probability. In general, users are more sensitive to dropping of an ongoing and handed over call than blocking a new call. Therefore, a CAC scheme needs to prioritize handoff calls over new calls by minimizing handoff-dropping probability.

Again, bandwidth adaptation and scheduling are necessary mechanisms for achieving high utilization of the wireless resources (e.g., channel bandwidth) while satisfyig the QOS requirements for the users. These two techniques are closely related to call admission control, and in fact these three mechanisms jointly determine the call-level and the packet-level QoS for the different types of traffic in the cellular wireless air interface. For example, upon arrival of a new call or handoff call, bandwidth adaptation[5] can be performed to degrade the channel allocations for some calls (still maintaining the QOS requirements) so that the new call can be admitted. Scheduling mechanisms impact the packet-level system dynamics (e.g., queuing behavior), and therefore, packet-level QOS. The packet-level dynamics can be exploited for designing efficient call admission control methods. The call admission control (CAC) and the adaptive channel adaptation (ACA) mechanisms are generally treated as the network layer (above layer-2) functionalities in the wireless transmission protocol stack. The scheduling and the adaptive modulation and coding (AMC) are layer-2 and layer-1 (i.e., physical functionalities, respectively.


Guaranteeing the QOS requirements is a challenging task with wireless communication[2]. One of the key elements in providing QOS is an effective resource allocation policy, which not only ensures meeting QOS of newly arriving calls, if accepted but also not deteriorating the existing on-going services.These enhancements will enable a better mobile user experience and will make more efficient use of the wireless channel.

As the performance of a system with given physical resources(e.g., the available bandwidth of radio spectrum) depends heavily on resource management schemes including multiple access techniques, the call admission control policies and the congestion control schemes, to make efficient use of the available bandwidth while providing high quality of service(QOS) to simultaneous services with different requirements, efficient resource management schemes have to be devised.


The capacity of any communications channel is defined by CE Shannon’s channel capacity formula …….

C=BW log2 [1+S/N]

Where BW = bandwidth in hertz

C = channel capacity in bits per second,

S = signal power, and N = noise power.

Eqn3.1 gives the relationship between the theoretical ability of a channel to transmit information without errors for a given SNR and a given bandwidth of a channel. Channel capacity is increased by increasing the channel bandwidth, the transmitted power, or a combination of both. Shannon modeled the channel at baseband. However the above equation is applicable to a radio frequency (RF) channel by assuming that the intermediate frequency (IF) filter has an ideal (flat) band-pass response with a bandwidth that is at least 2 x Bw. This bound assumes that channel noise is Additive White Gaussian Noise[5]. AWGN is often adopted in modeling of a RF channel. This assumption is justified since the total noise is generated by random electron fluctuations.

An analog cellular system is typically engineered to have an SNR of 17 Decibels or more. CDMA systems can be engineered to operate at much lower SNRs since the channel bandwidth can be traded for the SNR to achieve good performance at very low SNR.

Now if we write eqn 3.1 as

C/BW = 1.44loge [1+S/N]

Which is equivalent to

BW = C/1.44 x N/S

For any given SNR we can have a low information error rate by increasing the bandwidth used to transmit the information. Information can be modulated into the spread spectrum signal by several methods. The most common method is to add the information to the spectrum-spreading code before it is used for modulating the carrier frequency.


Let wallc and ballc denote the expected band-width for an incoming call and the bandwidth vector of ongoing calls, respectively. When a call arrives, the cell performs admission control[7] by checking whether the total number of ongoing calls is less than the threshold t. If this condition is satisfied or if the incoming call is a handoff call[6], the cell tries to allocate maximum bandwidth to the incoming call; otherwise, the incoming new call is blocked. However, if the available bandwidth is not enough to allocate maximum bandwidth to an incoming call, the adaptation algorithm[4] is invoked. The adaptation algorithm will randomly select an ongoing call with the current maximum bandwidth (i.e., max (ballc)) and de-grade allocated bandwidth of that call one step. At this point, expected bandwidth for incoming call increases one step. This operation is iteratively performed until the expected bandwidth for an incoming call is equal to the current minimum bandwidth of all ongoing calls (i.e., min (ballc)). In contrast, if every call has the minimum band-width b1, none of the ongoing call can be degraded. Therefore, an incoming call is dropped. For call thinning scheme, line 1 of this algorithm would be changed to admit the user

If ((incoming is a new call) and (number of ongoing calls <K)


If (available bandwidth > or = bmax)

Then assign bmax to incoming call



ballocated = 0

for (t=1,t<N, t++)

While (ballocated <bmin and nt >0)


randomly degrade one of nt connections by amount of bdegrade

bdegrade= min (bmin, bt- bmin)

ballocated = ballocated + bdegrade }



Else reject incoming call


Fig.1 WCDMA Transmitter


Fig.2 WCDMA Receiver


Fig.3 connection state diagram

Fig.3 indicates different users are in different users are in different level based on bandwidth allocation[8] .The level1 has highest bandwidth .When group1 (G1) enters into

network the level 1 users are falls into level 4 .This bandwidth degradation is applicable to existing users reaches to minimum bandwidth for a call to be continued.


Fig.4 First gold code plot

Fig.4 shows the gold code generator due to correlation value obtained from comparison of two pn sequences with one varying in time shift version. The code generated is used as a spread code and is used for user1

Fig.5 second gold code plot

Fig.5 shows the gold code generator due to correlation value obtained from comparison of two pn sequences with one varying in time shift version. The code generated is used as a spread code for user2

Fig.6 Third gold code plot

Fig.6 shows the gold code generator due to correlation value obtained from comparison of two pn sequences with one varying in time shift version.

The code generated is used as a spread code and is used for user3

Fig.7 Bpsk modulated output

Fig.7 shows the bpsk modulated data bundled with various power levels used before transmission. The three user data are modulated with sinusoidal carrier of o to (2*pi) sampled at 100 points. The user bandwidth data are processed for transmission over th wire less channel.

Fig.8 Bandwidth Degradation plot for the communication system

Fig.8 illustrates the performance plot for degradation in bandwidth allocated with respect to increase in number of users for fixed bandwidth allocation technique (fbat),adaptive bandwidth allocation technique (abat).The plot illustrates with increase in number of users the degradation eventually increases number for abat where as the fbat method the degradation is not applicable

Fig.9 Degradation ratios for the implemented communication system

Fig.9 shows the degradation the proposed two methods abat, fbat with respect to group of users in the plot it is observed that the degradation for abat system varies where as remain constant in case of fbat system.

Fig.10 Throughput plot for the FBAT and ABAT system

Fig.10 shows the throughput analysis for two systems namely abat,fbat methods.

Incase of abat method, it could be observed that the throughput remains decreased with increment in number of users where as it could be completely eliminated in case of fbat system.

Fig.11 Propagation Delay comparison plot for the two implemented system

Figure.11 shows the propagation delay observed for the two systems fbat and abat systems the propagation delay is considerably less for 12 users over constraint bandwidth. There is a decrement of about 40% in propagation delay comapared to fbat system.


In this paper, an analytical model for a wireless network which uses adaptive bandwidth allocation to provide users multilevel QOS. The performance plots obtained gives that with increase in load with respect to time the throughput level falls down because of increase in compression level which could be controlled by adaptive band width allocation method and an approach is made to overcome the resource constraint by degrading the bandwidth where each cell constitute of 3 users communicating simultaneously.

The performance is evaluated over wcdma architecture by adding or removing different group of users to evaluate the algorithm efficiency.