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MIMO Precoding Using Rotating Codebooks  [PDF]
C. Jiang,M. Wang,C. Yang
Mathematics , 2010,
Abstract: Next generation wireless communications rely on multiple input multiple output (MIMO) techniques to achieve high data rates. Feedback of channel information can be used in MIMO precoding to fully activate the strongest channel modes and improve MIMO performance. Unfortunately, the bandwidth of the control channel via which the feedback is conveyed is severely limited. An important issue is how to improve the MIMO precoding performance with minimal feedback. In this letter, we present a method that uses a rotating codebook technique to effectively improve the precoding performance without the need of increasing feedback overhead. The basic idea of the rotating codebook precoding is to expend the effective precoding codebook size via rotating multiple codebooks so that the number of feedback bits remains unchanged. Simulation results are presented to show the performance gain of the proposed rotating codebook precoding over the conventional precoding.
Diversity of MIMO Linear Precoding  [PDF]
Ahmed Hesham Mehana,Aria Nosratinia
Mathematics , 2012,
Abstract: Linear precoding is a relatively simple method of MIMO signaling that can also be optimal in certain special cases. This paper is dedicated to high-SNR analysis of MIMO linear precoding. The Diversity-Multiplexing Tradeoff (DMT) of a number of linear precoders is analyzed. Furthermore, since the diversity at finite rate (also known as the fixed-rate regime, corresponding to multiplexing gain of zero) does not always follow from the DMT, linear precoders are also analyzed for their diversity at fixed rates. In several cases, the diversity at multiplexing gain of zero is found not to be unique, but rather to depend on spectral efficiency. The analysis includes the zero-forcing (ZF), regularized ZF, matched filtering and Wiener filtering precoders. We calculate the DMT of ZF precoding under two common design approaches, namely maximizing the throughput and minimizing the transmit power. It is shown that regularized ZF (RZF) or Matched filter (MF) suffer from error floors for all positive multiplexing gains. However, in the fixed rate regime, RZF and MF precoding achieve full diversity up to a certain spectral efficiency and zero diversity at rates above it. When the regularization parameter in the RZF is optimized in the MMSE sense, the structure is known as the Wiener precoder which in the fixed-rate regime is shown to have diversity that depends not only on the number of antennas, but also on the spectral efficiency. The diversity in the presence of both precoding and equalization is also analyzed.
Layered Downlink Precoding for C-RAN Systems with Full Dimensional MIMO  [PDF]
Jinkyu Kang,Osvaldo Simeone,Joonhyuk Kang,Shlomo Shamai
Mathematics , 2015,
Abstract: The implementation of a Cloud Radio Access Network (C-RAN) with Full Dimensional (FD)-MIMO is faced with the challenge of controlling the fronthaul overhead for the transmission of baseband signals as the number of horizontal and vertical antennas grows larger. This work proposes to leverage the special low-rank structure of FD-MIMO channel, which is characterized by a time-invariant elevation component and a time-varying azimuth component, by means of a layered precoding approach, so as to reduce the fronthaul overhead. According to this scheme, separate precoding matrices are applied for the azimuth and elevation channel components, with different rates of adaptation to the channel variations and correspondingly different impacts on the fronthaul capacity. Moreover, we consider two different Central Unit (CU) - Radio Unit (RU) functional splits at the physical layer, namely the conventional C-RAN implementation and an alternative one in which coding and precoding are performed at the RUs. Via numerical results, it is shown that the layered schemes significantly outperform conventional non-layered schemes, especially in the regime of low fronthaul capacity and large number of vertical antennas.
Optimal Multiuser MIMO Linear Precoding with LMMSE Receiver  [cached]
Shu Fang,Gang Wu,Shao-Qian Li
EURASIP Journal on Wireless Communications and Networking , 2009,
Abstract: The adoption of multiple antennas both at the transmitter and the receiver will explore additional spatial resources to provide substantial gain in system throughput with the spatial division multiple access (SDMA) technique. Optimal multiuser MIMO linear precoding is considered as a key issue in the area of multiuser MIMO research. The challenge in such multiuser system is designing the precoding vector to maximize the system capacity. An optimal multiuser MIMO linear precoding scheme with LMMSE detection based on particle swarm optimization is proposed in this paper. The proposed scheme aims to maximize the system capacity of multiuser MIMO system with linear precoding and linear detection. This paper explores a simplified function to solve the optimal problem. With the adoption of particle swarm optimization algorithm, the optimal linear precoding vector could be easily searched according to the simplified function. The proposed scheme provides significant performance improvement comparing to the multiuser MIMO linear precoding scheme based on channel block diagonalization method.
Optimal Multiuser MIMO Linear Precoding with LMMSE Receiver  [cached]
Fang Shu,Wu Gang,Li Shao-Qian
EURASIP Journal on Wireless Communications and Networking , 2009, DOI: 10.1155/2009/197682
Abstract: The adoption of multiple antennas both at the transmitter and the receiver will explore additional spatial resources to provide substantial gain in system throughput with the spatial division multiple access (SDMA) technique. Optimal multiuser MIMO linear precoding is considered as a key issue in the area of multiuser MIMO research. The challenge in such multiuser system is designing the precoding vector to maximize the system capacity. An optimal multiuser MIMO linear precoding scheme with LMMSE detection based on particle swarm optimization is proposed in this paper. The proposed scheme aims to maximize the system capacity of multiuser MIMO system with linear precoding and linear detection. This paper explores a simplified function to solve the optimal problem. With the adoption of particle swarm optimization algorithm, the optimal linear precoding vector could be easily searched according to the simplified function. The proposed scheme provides significant performance improvement comparing to the multiuser MIMO linear precoding scheme based on channel block diagonalization method.
Limited Feedback Precoding for Massive MIMO  [PDF]
Xin Su,Jie Zeng,Jingyu Li,Liping Rong,Lili Liu,Xibin Xu,Jing Wang
International Journal of Antennas and Propagation , 2013, DOI: 10.1155/2013/416352
Abstract: The large-scale array antenna system with numerous low-power antennas deployed at the base station, also known as massive multiple-input multiple-output (MIMO), can provide a plethora of advantages over the classical array antenna system. Precoding is important to exploit massive MIMO performance, and codebook design is crucial due to the limited feedback channel. In this paper, we propose a new avenue of codebook design based on a Kronecker-type approximation of the array correlation structure for the uniform rectangular antenna array, which is preferable for the antenna deployment of massive MIMO. Although the feedback overhead is quite limited, the codebook design can provide an effective solution to support multiple users in different scenarios. Simulation results demonstrate that our proposed codebook outperforms the previously known codebooks remarkably. 1. Introduction High-rate data demand increases faster and faster with the new generation of devices (smart phones, tablets, netbooks, etc.). However, the huge increase in demand can be hardly met by current wireless systems. As is known to us, MIMO channels, created by deploying antenna arrays at the transmitter and receiver, promise high-capacity and high-quality wireless communication links by spatial multiplexing and diversity. Basically, the more antennas the transmitter or the receiver equipped with, the more degrees of freedom that the propagation channel can provide, and the higher data rate the system can offer. Therefore, there is significant effort within the community to research and develop massive MIMO technology, which is a hot topic nowadays [1]. For multiuser MIMO systems, we can utilize precoding to explore massive MIMO potentials. The essence of precoding techniques is to mitigate the interuser interference and to improve the effective received SNR. Herein, channel state information at the transmitter (CSIT) is an essential component when trying to maximize massive MIMO performance via precoding. In time division duplexing (TDD) system, channel reciprocity can be utilized for pilot training in the uplink to acquire the complete CSIT, but the pilot contamination and imperfect channel estimation based on uplink pilots would lead to inaccuracy of the CSIT. In frequency division duplexing (FDD) system, the CSIT shall be acquired via the feedback channel, which is usually limited in practice. Hence, a finite set of precoding matrices, named codebook, known to both the receiver and the transmitter should be predesigned. The receiver selects the optimal precoding matrix from the
Learning-Based Adaptive Transmission for Limited Feedback Multiuser MIMO-OFDM  [PDF]
Alberto Rico-Alvarino,Robert W. Heath Jr
Computer Science , 2013,
Abstract: Performing link adaptation in a multiantenna and multiuser system is challenging because of the coupling between precoding, user selection, spatial mode selection and use of limited feedback about the channel. The problem is exacerbated by the difficulty of selecting the proper modulation and coding scheme when using orthogonal frequency division multiplexing (OFDM). This paper presents a data-driven approach to link adaptation for multiuser multiple input mulitple output (MIMO) OFDM systems. A machine learning classifier is used to select the modulation and coding scheme, taking as input the SNR values in the different subcarriers and spatial streams. A new approximation is developed to estimate the unknown interuser interference due to the use of limited feedback. This approximation allows to obtain SNR information at the transmitter with a minimum communication overhead. A greedy algorithm is used to perform spatial mode and user selection with affordable complexity, without resorting to an exhaustive search. The proposed adaptation is studied in the context of the IEEE 802.11ac standard, and is shown to schedule users and adjust the transmission parameters to the channel conditions as well as to the rate of the feedback channel.
On the Optimality of Linear Precoding for Secrecy in the MIMO Broadcast Channel  [PDF]
Ali Fakoorian andA. Lee Swindlehurst
Mathematics , 2013,
Abstract: We study the optimality of linear precoding for the two-receiver multiple-input multiple-output (MIMO) Gaussian broadcast channel (BC) with confidential messages. Secret dirty-paper coding (SDPC) is optimal under an input covariance constraint, but there is no computable secrecy capacity expression for the general MIMO case under an average power constraint. In principle, for this case, the secrecy capacity region could be found through an exhaustive search over the set of all possible matrix power constraints. Clearly, this search, coupled with the complexity of dirty-paper encoding and decoding, motivates the consideration of low complexity linear precoding as an alternative. We prove that for a two-user MIMO Gaussian BC under an input covariance constraint, linear precoding is optimal and achieves the same secrecy rate region as S-DPC if the input covariance constraint satisfies a specific condition, and we characterize the corresponding optimal linear precoders. We then use this result to derive a closed-form sub-optimal algorithm based on linear precoding for an average power constraint. Numerical results indicate that the secrecy rate region achieved by this algorithm is close to that obtained by the optimal S-DPC approach with a search over all suitable input covariance matrices.
Multi-user Linear Precoding for Multi-polarized Massive MIMO System under Imperfect CSIT  [PDF]
Jaehyun Park,Bruno Clerckx
Computer Science , 2014,
Abstract: The space limitation and the channel acquisition prevent Massive MIMO from being easily deployed in a practical setup. Motivated by current deployments of LTE-Advanced, the use of multi-polarized antennas can be an efficient solution to address the space constraint. Furthermore, the dual-structured precoding, in which a preprocessing based on the spatial correlation and a subsequent linear precoding based on the short-term channel state information at the transmitter (CSIT) are concatenated, can reduce the feedback overhead efficiently. By grouping and preprocessing spatially correlated mobile stations (MSs), the dimension of the precoding signal space is reduced and the corresponding short-term CSIT dimension is reduced. In this paper, to reduce the feedback overhead further, we propose a dual-structured multi-user linear precoding, in which the subgrouping method based on co-polarization is additionally applied to the spatially grouped MSs in the preprocessing stage. Furthermore, under imperfect CSIT, the proposed scheme is asymptotically analyzed based on random matrix theory. By investigating the behavior of the asymptotic performance, we also propose a new dual-structured precoding in which the precoding mode is switched between two dual-structured precoding strategies with 1) the preprocessing based only on the spatial correlation and 2) the preprocessing based on both the spatial correlation and polarization. Finally, we extend it to 3D dual-structured precoding.
Linear precoding in distributed MIMO systems with partial CSIT
Chongbin Xu, Jianwen Zhang, Fuchun Zheng and Li Ping
EURASIP Journal on Advances in Signal Processing , 2013, DOI: 10.1186/1687-6180-2013-22
Abstract: We study the transmission problem in a distributed multiple-input multiple-output (MIMO) system consisting of several distributed transmitters and a common receiver. Assuming partial channel state information at the transmitter (CSIT), we propose a low-cost weighted channel matching and scattering (WCMS) linear precoding strategy. The proposed precoder can be decomposed into two parallel modules: channel matching (CM) and energy scattering. The signals generated by the CM modules from different transmitters provide a coherent gain with improved power efficiency. The use of the scattering modules provides robustness against CSIT uncertainty. By properly combining these two modules, WCMS can achieve coherent gain proportional to the accuracy of the available CSIT as well as robustness against CSIT error. WCMS is simple and fully decentralized and thus is highly suitable for a distributed MIMO system. Numerical results demonstrate that WCMS indeed achieves significant gains in distributed MIMO environments with partial CSIT.
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