Efficient channel quantization scheme for multi-user MIMO broadcast channels with RBD precoding (original) (raw)
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Block diagonalization (BD) based precoding techniques are well-known linear transmit strategies for multiuser MIMO (MU-MIMO) systems. By employing BD-type precoding algorithms at the transmit side, the MU-MIMO broadcast channel is decomposed into multiple independent parallel single user MIMO (SU-MIMO) channels and achieves the maximum diversity order at high data rates. The main computational complexity of BD-type precoding algorithms comes from two singular value decomposition (SVD) operations, which depend on the number of users and the dimensions of each user's channel matrix. In this work, low-complexity precoding algorithms are proposed to reduce the computational complexity and improve the performance of BD-type precoding algorithms. We devise a strategy based on a common channel inversion technique, QR decompositions, and lattice reductions to decouple the MU-MIMO channel into equivalent SU-MIMO channels. Analytical and simulation results show that the proposed precoding algorithms can achieve a comparable sum-rate performance as BD-type precoding algorithms, substantial bit error rate (BER) performance gains, and a simplified receiver structure, while requiring a much lower complexity.
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Recently, a number of techniques have been introduced to exploit multiuser diversity of a wireless multiple-input multiple-output (MIMO) broadcast channel (BC) that consists of a base station with t transmit antennas and K users with multiple antennas. However, prior works have ignored the rate overhead associated with feedback of MIMO BC channel state information at transmitter (CSIT), which is roughly K times larger than single-user MIMO CSIT (i.e., it is O(tr) where r = K k=1 r k and r k is the number of antennas at the kth user). Considering the amount of feedback signaling, quantization is a necessity for effective feedback transmission as a form of partial CSIT. In this paper, we propose the greedy multi-channel selection diversity (greedy MCSD) scheme based on block MMSE QR decomposition with dirty paper coding (block MMSE-DP), where partial CSIT is almost sufficient. The sum-rate performance of our novel scheme approaches extremely close to the sum capacity of MIMO BC as the number of users increases, whereas the feedback overhead is reduced by a factor of 2t 3 /L(t 2 −t), in which L is the number of active channel vectors. Simulation results validate the expectation from the analysis. In addition, the proposed scheme is shown to be appropriate for reconfigurable implementation.
International Journal of Engineering Research and Technology (IJERT), 2013
https://www.ijert.org/an-efficient-linear-precoding-scheme-based-on-block-diagonalization-for-multiuser-mimo-downlink-system https://www.ijert.org/research/an-efficient-linear-precoding-scheme-based-on-block-diagonalization-for-multiuser-mimo-downlink-system-IJERTV2IS100931.pdf Block diagonalization (BD) based on singular value decomposition (SVD) is a well-known precoding method that eliminates inter user interference in multiuser multi-input multi-output (MIMO) broadcast channels, but it is computationally inefficient. In this paper we examine the use of generalized singular value decomposition (GSVD) for coordinated beam-forming in MIMO systems. GSVD facilitates joint decomposition of a class of matrices from source to destination MIMO broadcast scenarios. GSVD allows two channels of suitable dimensionality to be jointly diagonalized, through the use of jointly determined transmit precoding and receiver reconstruction matrices. Simulation results demonstrate that the proposed GSVD technique achieves considerable gains in terms of bit error rate (BER) over SVD technique with traditional interference aware block diagonalization (BD) scheme. Analysis and simulation results show that our proposal has lower complexity than the conventional BD method, with a significant increase there in sum throughput.
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We consider a multiuser MIMO-OFDM downlink system with single antenna mobile terminals (MTs) where channel state information at the base station is provided through limited uplink feedback (FB). In order to reduce the FB rate and signal processing complexity, the available bandwidth is divided into resource blocks (RBs) whose number of subcarriers reflects the coherence bandwidth of the channel. This approach is very common in the standardization of 4th generation wireless communication systems and justifies an independent channel quantization per RB. The paper has two main contributions: firstly we show conditions on the coherence bandwidth of the channel and the FB rate per RB that allow for a simpler characterization of the RB channel matrix by a space vector, causing negligible performance loss. This is accomplished after deriving a new performance metric for RB channel quantization that exploits spatial and frequency correlation. As a second contribution we investigate the trade-off between accurate channel knowledge and frequency/multiuser diversity. It is seen that even for a moderate number of MTs in the network, concentrating all the available FB bits in characterizing only one RB provides a significant gain in system throughput over a more classical distributed approach and this result is validated both analytically and by simulations.