DYNAMIC POWER ALLOCATION SCHEME USING LOAD MATRIX TO CONTROL INTERFERENCE IN 4G MOBILE COMMUNICATION SYSTEMS
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1 DYNAMIC POWER ALLOCATION SCHEME USING LOAD MATRIX TO CONTROL INTERFERENCE IN 4G MOBILE COMMUNICATION SYSTEMS Srinivas karedla 1, Dr. Ch. Santhi Rani 2 1 Assistant Professor, Department of Electronics and Communications, GITAM University, Visakhapatnam, India. 2 Professor, Department of Electronics and Communications, DMSSVH College of Engineering, Machilipatnam, India Abstract- The aim of the paper is to interference in 4G mobile communication systems. In the past, Load Matrix with bifurcated Signal to noise plus interference ratio (LM-BFSNIR) is proposed to assign power to different users in multi carrier systems over a 3GPP-LTE standard network[6]. In this paper, the same scheme is applied to users in a multi-carrier system operated over a 4G standard network.the simulation results indicate that the BER in 4G network is better than 3GPP- LTE network. Keywords Power allocation, Interference, 3GPP- LTE standard,lm-bfsnir,4g standard. I. INTRODUCTION The aim of wireless communication systems is to offer secured transmission by maximizing the data rate. To realize this latest techniques are introduced in which multi-carrier communication is growing at a rapid rate. Usually, more band width is required for higher data rate transmission. Yet, because of spectral limitations, it is typically very expensive to raise bandwidth. The another way out for efficient utilization of available spectrum is to implement multiple transmit and receive antennas, implementation of multiple transmit and receive antennas forms a multi-carrier communication system. Quality of service,less number of dropped calls and more capacity are benefits of multi-carrier over single carrier system. By considering multiple transmit and receive antennas as multi carrier channels the network capacity can be improved [1]. Multi-carrier systems performance is better than single carrier in a Rayleigh flat fading environment as shown in [2]. In multi carrier [3] [5], the entire channel is divided into many narrow parallel sub channels, thereby increasing the symbol duration and reducing or eliminating the ISI caused by the multipath. A multi carrier system with adaptive resource allocation for co-channel interference suppression [6] and transmit diversity based on space time coding, delayed transmission, and permutation [7] [9] is evaluated. In particular, a channel parameter estimator for multi carrier systems with multiple transmit antennas was proposed in [7] and simplified in [9]. Load Matrix (LM) [10] is a resource allocation strategy that allocates the power to the base stations and users based on the SNIR to decrease inter cellular interference in turn increases throughput by reducing bit error rate as discussed in the section I and is applied only for single carrier systems. In [11] LM is evaluated for Multi- carrier systems using bifurcated SNIR i.e. LM-BFSNIR coding and ISSN All Rights Reserved 2014 IJEETE Page 22
2 verified over 3GPP-LTE standards. In this paper, bit error rate and throughput are analyzed for multi-carrier systems with 4G standards using LM-BFSNIR and compared with LM coding. II. SYSTEM OUTLINE Multi-Carrier technology has aroused much users concern because of its applications in mobile communication, digital television, wireless LAN s and MAN s. The number of transmit and receive antennas are increased in a multi-carrier system to enhance the capacity of a network. Second, system operation have been enhanced in multi-carrier system as a result it provides a spatial diversity in which each transmitting signal is received by the whole receiver array. This also reduces the SI (inter symbol interference) effect and impact of channel fading since each signal is determined based on P detected results i.e. spatial diversity offers P independent replicas of transmitted signal. A multi-carrier system for test estimation with four transmit and receive antennas is considered. The data block of transmitter can be given as, These signals are two different signals 1,2 ; =1,2 for a=1 and 2 sent through two space time encoders. The a th transmitting antenna signal is modulated by at the c th carrier of the d th data block. The signal at each receiving antenna is given by, For where is the Gaussian noise(additive and complex) at the b th receive antenna, and is of zero-mean with variance uncorrelated for different. The Channel frequency response related to the a th transmit and the b th receive antenna for the c th tone at time r is The vector form representation of the Multicarrier system relation shown in (1) can be given by Where (2) (3) To transmit over the channel the multiple power levels are provided to the different users in the network. The best exploitation of resources is due to the best possible utilization of transmitting power. For beat allocation of resources a resource allocation approach has been proposed which has been discussed in the following section. III. LOAD MATRIX [ 5] CODING (1) Load Matrix (LM) coding has the characteristic of controlling the interference by allocating radio resources to users and keeping Rise over thermal noise (RoT) outage intact by considering the inter cell interference ISSN All Rights Reserved 2014 IJEETE Page 23
3 information. The management of inter cell interference is the major difficulty for resource allocation in mobile communication system. LM is a best centralized scheduler which imparts radio resources to all users in the network by updating a database containing the active load part of all users in the network. The critical issue in the uplink scheduler is to properly impart transmission rate and time to all users, to result in best utilization of radio resources across the network while satisfying the QoS requirements of the users. The considerable issue in the resource allocation is the transmit power of the users. The following conditions are to be satisfied for a network of X users and Y base stations. the of cells can be estimated by using, which can be written as (6) Condition3 :The signal to noise plus interference ratio necessary at the c th serving base station if rate q is being assign to the user to attain a given frame error rate is. For each user, depending on its channel form and speed, each rate p has a least required called. This constraint satisfies only by taking as Condition 1: An active user i in the network the transmitted power must be in an acceptable region defined as (4) (7) LM is a best centralized scheduler assigns radio resources to all the X users and Y cells in the network, is the load factor contribution by user n at defined as Where is the maximum user power. condition 2: The total received power at base station must be set below a definite threshold which must be maintained by all the base stations. In the network RoT can be used as a sign of the interference constraints. (8) Where is the channel gain from user n to BSc averaged over scheduling period, is the thermal noise and u n is the transmitted power. The LM n,c values stored in column c of LM database, RoT of cell c can be written as (5) Where is the total band received power, preset target value to maintain uplink interference level at the base station c (BS c ) over thermal noise. For a network containing X dynamic users can be written as (9 ISSN All Rights Reserved 2014 IJEETE Page 24
4 (10) The necessary transmitted power for user n at rate q is, (12) In equation (12), the SNIR used in single carrier systems is bifurcated in terms of SNR and SIR (11) If above all conditions are satisfied then only power is acceptable and user n will be scheduled for transmission. After that LM elements are updated and is calculated for each cell using equation (10).The performance of the LM scheduling has the optimum RoT over other algorithms because this scheduler considerably decreases the probability of the RoT getting over its target. The Load matrix approach considered in the previous section is able to allocate the power efficiently for a single cell users based on SNIR and RoT concepts, considering only signal to noise ratio for power allocation for single carrier communication. IV. LM BFSNIR APPROACH In Multi-carrier communication system the Signal to interference ratio is affected distinctly in each carrier hence a single SNIR for allocation is not optimal. Also, since due to usage of orthogonally modulated signals for transmission over narrow band channels the interference between them is decreased. Hence SIR which is distinct in each channels is almost maximized,for the optimization of power allocation the total SIR in Multi carrier system is sum of SIR s in individual channels which greater than the SNIR obtained in single carrier system. This can be mathematically expressed as Where denotes the background signal-to-noise ratio. SIR is the signal-tointerference ratio evaluated for in every narrow channel by doing so the (12) can be rewritten as shown (13) Where BFSNIR is called as bifurcated SNIR evaluated for multi-carrier system designed with four transmit and receive antennas(i.e. =4), substituting the above equation (13) for the conventional LM approach, the proposed get modified as (14) The required transmitted power for user i at rate p is then defined as, (15) The allocable power to each user with rate q is then defined as; ISSN All Rights Reserved 2014 IJEETE Page 25
5 BER amplitude International Journal of Exploring Emerging Trends in Engineering (IJEETE) 6 Channel Urban Urban Else user will be in queue and scheduled for transmission next Transmission time interval(tti) (16) condition 7 Channel Delay Factor 8 Channel Nature Micro 1.627e- 8sec Additive,Random Micro 1.627e- 8sec Additive,Random V. SIMULATION AND RESULTS For the simulation of the planned work a 4G standard and 3GPP-LTE wireless communication model is considered. The considered communication parameters for the evaluation are given as in Table 1; Orthogonally Modulated Signals for Transmission The proposed work is evaluated using MATLAB and the simulated results are as follows Table S.No Parameter 3GPP- LTE 4G -2 1 Category Uplink data 5 Mbps 20 Mbps rate(ul-dr _peak ) 3 Down link 10Mbps(u 100 Mbps data rate (DL- DR _peak) sed 5mbps) 4 Modulation Uplink-16 QAM Uplink-16 QAM time Figure 1: Plot of orthogonally modulated signals used for transmission 10-2 SNIR v/s BER LM-BFSNIR Approach(3G STANDARD) Downlink -16QAM 5 Architecture Uplink- MIMO 4x4 (OFDM) Downlink -16QAM Uplink- MIMO 4x4 (OFDM) SNIR in db Figure 2: SNIR vs. BER plot for the multi Carrier system using LM BFSNIR coding using 3GPP-LTE Standards ISSN All Rights Reserved 2014 IJEETE Page 26
6 BER International Journal of Exploring Emerging Trends in Engineering (IJEETE) Figure 3: SNIR vs. BER plot for the multi Carrier system using LM BFSNIR coding using 4G Standards VI. CONCLUSION In this paper, LM coding is evaluated for multi-carrier mobile communication system. In past work Load matrix approach is applied for single carrier system and the power is allocated to the users by considering SNIR.By considering the bifurcated SNIR in multi-carrier system it is observed that the inter cellular interference is reduced better than the single carrier systems and in turn reduces the bit error rate. VII SNIR v/s BER SNIR in db REFERENCES LM-BFSNIR Approach(4G STANDARD) [1]R.R.Chen and Y.Lin. Optimal power Control for Multiple Access Channel and Average Power Constraints..In proceedings of IEEE International Conference on Wireless Networks, Communication and Mobile Computing, pp [2].J.H Winters On the Capacity of radio communication systems with diversity in a Rayleigh fading environment. IEEE J. Select. Areas Communication, vol.sa-5,pp ,june [3] G. J. Foschini, Layered space time architecture for wireless communication in a fading environment when using multi-element antennas, Bell Labs Tech. J., pp , Autumn [4] X Wang, GB Giannakis, Resource allocation for wireless multiuser OFDM networks. IEEE Trans. Inf. Theory Vol. 7,pp ,2011. [5] Y Hu, A Ribeiro, Optimal wireless networks based on local channel state information. IEEE Trans. Signal Process Vol. 9,pp ,Sept [6]Y Hu, A Ribeiro, Optimal transmission over a fading channel with imperfect channel state information. Global Tele communication. Conf., vol. 1, 2011 [7] Y Hu, A Ribeiro, Adaptive distributed algorithms for optimal random access channels. IEEE Trans. Wireless Communication, 2011 [8] MJ Neely, E Modiano, CE Rohrs, Dynamic power allocation and routing for time-varying wireless networks, IEEE J. Sel. Areas Communication, pp ,2005. [9] Y. Li, Simplified channel estimation for OFDM systems with multiple transmit antennas, IEEE Trans. Wireless Commun., vol. 1, pp , Jan [10] Mohammad Abaii, Yajian Liu, and Rahim Tafazolli, An Efficient Resource Allocation Strategy forfuture Wireless Cellular Systems, IEEE Transactions on Wireless Communications, Vol. 7, No. 8, August [11] Srinivas karedla, Dr.Ch.Santhi Rani An Approach to control inter cellular interference using Load Matrix in Multi-carrier mobile communication ystems,ijret,vol.4,no.2,february ISSN All Rights Reserved 2014 IJEETE Page 27
7 AUTHOR S BIBLOGRAPHY Srinivas karedla, received his B.Tech Degree in Electronics and Communication Engineering from Acharya Nagarjuna University in 2004 and M.Tech degree in Computers and Communication from JNTUK,Kakinada,in 2010.He is presently working as an Assistant Professor in ECE engineering department, GIT, GITAM University, Visakhapatnam, Andhra Pradesh. His total experience in teaching is 7 years.his areas of interest are Wireless communications and Networks, Signal processing and Spread spectrum systems. He has published 8 papers in various international and national conferences and journals. Dr Santhi Rani Ch, received her B. Tech Degree in Electronics and Communication Engineering from Acharya Nagarjuna University in 1993 and M.Tech degree from JNTU College of Engineering, Ananthapur, Andhra Pradesh. She earned her PhD degree from JNTUH Hyderabad. She is presently working as a Professor, Department of ECE, DMS SVHCE, Machilipatnam, affiliated to JNTUK, Kakinada, Andhra Pradesh. Her total experience in teaching is 18 years. Her areas of interest are Mobile and Cellular Communication, Smart Antennas, VLSI Design, Wireless Sensor Networks.. She has published 23 papers in various international and national conferences and journals. ISSN All Rights Reserved 2014 IJEETE Page 28
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