A SUBCARRIER AND BIT ALLOCATION ALGORITHM FOR MOBILE OFDMA SYSTEMS Anderson Daniel Soares 1 , Luciano Leonel Mendes 1 and Rausley A. A. Souza 1 1 Inatel Electrical Engineering Department – P.O. BOX 35, Santa Rita do Sapucaí, MG, Brazil – 37540-000 adsoares@inatel.br, luciano@inatel.br, rausley@inatel.br Abstract – OFDMA technique is becoming a popular solution to increase the spectral efficiency of multi-user wireless digital communication standards, such as WiMAX, LTE and IEEE 802.22. The flexibility of this technique, allied with its robustness against frequency selective time variant channels, makes it a suitable solution for high data rate mobile communication systems. However, there are several challenges that must be overcome in order to achieve high spectrum efficiency. One of these challenges is the bit and subcarrier allocation for each user. There are a lots of algorithms described in literature, ones that only consider the channels conditions, which means that the QoS of each user does not play a rule in the resource allocation process. Such algorithm may result in an unfair distribution of the resources between the users. Others algorithms take into account both the QoS and the channel conditions, but that employ several steps algorithms that may increase the complexity. The aim of this paper is to present a simple subcarrier and bit allocation algorithm that uses the individual channel conditions and QoS to distribute the system resources between the users. If the number of necessary subcarriers is smaller than the total number of available subcarriers, than it is possible to use three different priority approaches to distribute the extra subcarriers between the users. The spectral efficiency of each priority approach will be analyzed by using computational simulation. Keywords – Bit Allocation, Power Allocation, OFDM. 1. INTRODUCTION Today, personal mobile data communication systems require high spectrum efficiency in a frequency selective time variant channel. Orthogonal Frequency Division Multiplexing (OFDM) [1] is being used to combat the effects of a multipath channel, but in a multiuser environment, it is inefficient to allocate an entire OFDM symbol to a single user because usually a single user does not require all subcarriers to transmit its own information. One solution to increase the data transmission efficiency is to share the subcarriers with multiple users. This technique is called Orthogonal Frequency Division Multiple Access (OFDMA) [2] and it is being used in several modern mobile communication systems, such as Long Term Evolution (LTE) and Worldwide Interoperability for Microwave Access (WiMAX) [3]. In order to obtain the best results, the conditions of the propagation channel of each user must be considered during the subcarrier allocation process, which means that the Channel State Information (CSI) of each user must be known [4]. There are different resource allocation algorithms and adaptive modulation techniques for OFDMA systems available in literature [4] [5] [6] [7]. The authors in [4] analyze the resource allocation problem for the uplink in a mobile communication system that employs OFDMA. Three algorithms are used to maximize the total data rate between users: the first algorithm defines the number of carriers for each user; the second algorithm performs the subcarrier allocation considering the CSI of each user and; the last performs the power allocation using the Water-filling Theorem [8] approach. In [5], the authors proposes an approach based on changing the number of bits per symbol transmitted in each subcarrier as a function of the average bit error rate (BER) evaluated over all subcarriers. Basically, the algorithm computes the best modulation order for each subcarrier based on the received signal to noise ratio (SNR), aiming to keep the quality of service constant. The authors in [6] present a computational efficient algorithm to allocate resources for different users in an OFDM system. The main idea in this proposal is to divide the resource allocation process in two steps: first, the number of subcarriers for each user are estimated; second, the subcarriers are distributed to them. The performance of this approach is slightly worse than the classical solution but the complexity and required time to process the resource allocation algorithm is significantly reduced. To distribute the bits for the allocated subcarriers is done by a classical power and bit allocation algorithm for single user. The same authors presented a variant of this approach in [9], where a multi-user power allocation algorithm based on Water- filling Theorem has been used instead the single-user resource allocation algorithm. As one can see, the major objectives in the resource allocation algorithms presented in literature are to maximize the overall throughput of the system or