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Adaptive power & SUBCARRIER allocation algorithm to support absolute proportional rates constraint for scalable MULTIUSER MIMO OFDM systems Presented By:

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1 Adaptive power & SUBCARRIER allocation algorithm to support absolute proportional rates constraint for scalable MULTIUSER MIMO OFDM systems Presented By: MOHAMMED AKBER ALI, G KING FAHD UNIVERSITY OF PETROLEUM & MINERALS

2 PROBLEM STATEMENT The Task is to find an optimal solution for sub-channel and power allocation for a multiuser MIMO-Orthogonal Frequency Division Multiplexing (OFDM) system that maximizes the overall system capacity given the proportional rate constraint…………!!!

3 References & Previous Works: [1]. Ashraf S. Mahmoud, Ali Y. Al-Rayyah, and Tarek R. Sheltami - “Adaptive Power Allocation Algorithm to Support Absolute Proportional Rates Constraint for Scalable OFDM Systems”. IEEE 71st VTC-Spring May This paper presents an efficient algorithm inorder to solve subchannel and power allocation for a multiuser OFDM system. The solution utilizes a sub-channel allocation to compute the optimal power allocation for the given sub-channel distribution (without making any assumptions regarding the channel characteristics and for arbitrary proportional rate constraint.) The algorithm proposed guarantees a solution that satisfies the proportional rate constraint in the strictest sense.

4 References & Previous Works: [2 ]. Ying Jun Zhang and Khaled Ben - “An Efficient Resource-Allocation Scheme for Spatial Multiuser Access in MIMO/OFDM Systems”. This paper proposed an adaptive resource-allocation algorithm for spatial multiuser-access MIMO/OFDM systems. A reduced-complexity algorithm, which decouples the multiuser joint-optimization problem into single-user bit-and-power- allocation problems, is developed. Numerical results show that tremendous power gain and diversity gain is achieved, compared with nonadaptive transmission. Moreover, the proposed system is able to multiplex a number of users in the space domain without sacrificing the diversity order.

5 References & Previous Works: [3]. Peerapong Uthansakul and Marek E. Bialkowski - “An Efficient Adaptive Power and Bit Allocation Algorithm for MIMO OFDM System Operating in a Multi User Environment”. The close-form solution for allocating loaded bits according to an assumed BER constraint has been presented. A one-step (non-iterative) adaptive solution is based on the application of a Lagrange method. It has been shown that the adaptive algorithm can achieve successful performance by maintaining the minimum transmitted power for a given BER target value. Because, this algorithm is based on a one step procedure it is very fast in terms of its execution time.

6 References & Previous Works: [4]. Zhenping Hu, Guangxi Zhu, Yuan Xia, Gan Liu - “Multiuser subcarrier and bit allocation for MIMO-OFDM systems with perfect and partial channel information”. In this paper, design of a downlink adaptive multiuser MIMO- OFDM transmit schemes is proposed in which adaptation occurs in three levels: adaptive subcarrier assignment among users, adaptive modulation across OFDM subcarriers and adaptive beamforming for each subcarrier. With the goal of minimizing the total transmit power for they derive the criteria(of subcarrier allocation used in MIMO- OFDM scenarios)based on perfect and partial channel information.

7 References & Previous Works: [5]. Yang Hu, Changchuan Yin and Guangxin Yue - “ Multiuser MIMO-OFDM with Adaptive Antenna and Subcarrier Allocation”. The proposed algorithms aim towards maximizing the rank & Eigen values of the channel response matrix(Hn), given correlation matrices at the receiver and transmitter end. In particular the paper aims for maximizing system capacity, using SVD(singular value decomposition).

8 EXPECTED OUTCOME Insha- Allah, –We hope to come out with an efficient and optimal adaptive power & subcarrier allocation scheme for a multi user MIMO-OFDM system which satisfies the proportional rate constraint in strict sense and maximizes the system throughput.

9 Total Capacity For SISO, For MMO,


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