Advances in Science, Technology and Engineering Systems Journal Vol. 2, No. 3, 138-145 (2018) www.astesj.com Special Issue on Advancement in Engineering Technology ASTES Journal ISSN: 2415-6698 Efficient Limited Feedback Technique for FDD MIMO Sys- tems Papis Ndiaye, Moussa Diallo, Idy Diop Department of Computer Science, Polytechnic Institute (ESP), Universit´ e Cheikh Anta Diop de Dakar, Senegal ARTICLEINFO ABSTRACT Article history: Received: 15 November, 2017 Accepted: 05 February, 2018 Online: 17 March, 2018 Keywords: MIMO OFDM Beamforming Feedback overhead In this paper an efficient feedback quantization technic for beamforming in MIMO systems is presented. The proposed technic named time domain quantization TD-Q is based on the feedback of time domain parameters necessary for the reproduction of the beamforming matrix at the trans- mitter. This TD-Q presents the same performance than the conventional Givens rotation quantization GR-Q approach which is adopted in IEEE 802.11ac standardand. The performance and amount of feedback of the proposed TD-Q are studied and compared with the GR-Q in IEEE 802.11ac context. 1 Introduction The combination of Multiple-Input Multiple-Output (MIMO) and Orthogonal Frequency Division Multi- plexing (OFDM) technologies (MIMO-OFDM) is now adopted in several communication standards, includ- ing the 5 th generation of mobile communication net- work (5G) [1], the IEEE WLAN 802.11ac [2] and the IEEE 802.16 standards (WiMax)[3]. On the one hand, OFDM is a worthwhile trade- off between bit-error rate performance and spectral efficiency. OFDM consumes part of the channel band- width, but it is robust to frequency selective fading environment. In addition, it enables the use of sev- eral advanced technics to further enhance the system throughput, as for instance the bit loading technic [4] and the subcarriers allocation in orthogonal frequency division multiple access (OFDMA) [5]. On the other hand, the MIMO system has the potential to improve the system capacity. In IEEE 802.11ac wireless local area network (WLAN) stan- dard, there are five transmit and receive MIMO tech- nics: Cyclic Shift Diversity (CSD), Space Time Block Coding (STBC), Spatial Division Multiplexing (SDM), Maximal Rotation Combining (MRC) and Transmit Beamforming (TxBF) [2]. Among these five technics, this is the Transmit Beamforming which can maximize the system capacity. Indeed, the Beamforming with precoding and postcoding eliminates the co-channel interferences (CCI) which are the fundamental prob- lem faced by the practical MIMO system [6-8]. However, in beamforming technic the channel state information (CSI) must be available at the transmitter and the receiver. This CSI is estimated at the receiver and fed back to the transmitter. The CSI, which indi- cates amplitude and phase for each transmit antenna, receive antenna, and each OFDM subcarrier in the RF channel may reduce the overall throughput. To reduce the feedback amount, the receiver computes the beam- forming matrix (precoding matrix) which is an unitary matrix and compresses it before sending back to the transmitter. There are several proposals in the literature for the beamforming matrix compression. Many authors pro- pose codebook based approach. In codebooks based technics, the channel distribution is taken into account during the codebook design. Instead of sending the precoding matrix, only the index of the selected pre- coding matrix (after channel estimation and SVD de- composition) is sent. Intrinsically, the codebook is restricted to have fixed cardinality. Thereby, the se- lected pre-coding matrix, which is the most similar is not necessarily the most optimal. Unfortunately, the codebook size has an impact on the system per- formance and requires high storage. For traditional MIMO systems, several codebooks have been proposed, such as Kerdock codebook [9], codebooks based on vector quantization [10], Grassmannian packing [11], discrete Fourier transform (DFT) [12] and quadrature amplitude modulation [13]. The coodbook principle is adopted in LTE [14]. In [15], the codebook was de- signed and optimized by selecting matrices having 8 phase-shift keying (PSK) entries and coping with a large range of propagation conditions. However the cost of this scheme is that the performance gain de- creases dramatically due to the channel quantized er- www.astesj.com 138 https://dx.doi.org/10.25046/aj030216