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2 edition of multiuser linear precoding for the downlink of MIMO-OFDM systems found in the catalog.

multiuser linear precoding for the downlink of MIMO-OFDM systems

Hassen Karaa

multiuser linear precoding for the downlink of MIMO-OFDM systems

by Hassen Karaa

  • 306 Want to read
  • 39 Currently reading

Published in 2007 .
Written in English


Edition Notes

Statementby Hassen Karaa.
ID Numbers
Open LibraryOL19904777M

[C5] H. Karaa, A. Tenenbaum and R. S. Adve, “ Linear precoding for multiuser MIMO-OFDM systems ”, IEEE International Conf. on Communications, June [C4] A. Khachan, A. Tenenbaum and R. S. Adve, “ Linear processing for the downlink in multiuser MIMO systems with multiple data streams ”, IEEE International Conf. on Communications. In Multiuser MIMO (MU-MIMO) systems, precoding is essential to eliminate or minimize the multiuser interference (MUI). However, the design of a suitable precoding algorithm with good overall performance and low computational complexity at the same time is quite challenging, especially with the increase of system dimensions.

  MIMO-OFDM Wireless Communications with MATLAB(R) is a key text for graduate students in wireless communications. Professionals and technicians in wireless communication fields, graduate students in signal processing, as well as senior undergraduates majoring in wireless communications will find this book a practical introduction to the MIMO 5/5(1). IEEE Commun Mag., 42(10), 54–59 Vishwanath, P and Tse, D () Sum capacity of the vector Gaussian broadcast channel and uplink-downlink duality IEEE Trans Info Theory, 49(8), – Yu, W and Cioffi, J () Sum capacity of a Gaussian vector broadcast channel IEEE Trans Info Theory, 50(9), – Vishwanath, S.

Miquel Payaro,, Antonio Pascual, J. Yuan, and Miguel Angel Lagunas, A Convex Optimization Approach for the Robust Design of Multiuser and Multiantenna Downlink Communication Systems, The Seventh IEEE International Workshop on Signal Processing Advances in Wireless Communications, K.   Understanding lte with matlab zarrinkoub, houman x Contents Verifying Transceiver Performance Adaptation Results Adaptive Precoding PMI-Based Adaptation Verifying Transceiver Performance Adaptation Results Adaptive MIMO RI-Based Adaptation Verifying.


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Multiuser linear precoding for the downlink of MIMO-OFDM systems by Hassen Karaa Download PDF EPUB FB2

Download Citation | Linear precoding for multiuser MIMO-OFDM systems | This paper develops linear preceding schemes for the downlink in multiuser multiple-input multiple-output (MIMO) orthogonal.

Throughput maximization in linear multiuser MIMO-OFDM downlink systems Article (PDF Available) in IEEE Transactions on Vehicular Technology 57(3) - June with 65 Reads. This paper proposes a peak-to-average power ratio (PAPR) reduction method that maintains an effect of linear precoding by block diagonalization (BD) for multiuser (MU) MIMO-OFDM systems.

In the downlink MU-MIMO-OFDM, BD orthogonalizes multiple signals of all users by the linear precoding using channel state information, but the transmitted signal still has high PAPR due to OFDM characteristics. In this paper, we extend a jointly optimized linear prefilter and nonlinear vector perturbation approach to the MIMO multiuser (MU) precoder system where each user has multiple antennas.

As a prefilter design, we use the weighted MMSE criterion. Based on the best weighting condition, we. Bandemer, B., Haardt, M.: Linear MMSE multi-user MIMO downlink precoding for users with multiple antenna.

In: The 17th Annual IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, pp. 1–5 () Google ScholarAuthor: Liu Haitao, Xiao Jing, Zhang Yongjian. In this paper, we have analyzed the PAPR performance of MU-MIMO systems with precoding and proposed two novel jointly linear precoding and PAPR reduction algorithms for MU-MIMO downlink scenarios.

The extra DoF of the precoding matrix enables us to design transmit signal with low PAPR without destroying the MUI free : Zhou Fang, Zhou Fang, Hua Qian, Kai Kang, Haifeng Wang, Yanliang Jin.

MIMO-OFDM is a keytechnology for next-generation cellular communications (3GPP-LTE, Mobile WiMAX, IMT-Advanced) as well as wireless LAN (IEEE a, IEEE n), wireless PAN (MB-OFDM), and broadcasting (DAB, DVB, DMB).

This book provides a comprehensive introduction to the basic theory and practice of wireless channel modeling. MIMO-OFDM Precoding with Phased Arrays How phased arrays are used in a MIMO-OFDM communication system employing beamforming.

Using components from Communications Toolbox™ and Phased Array System Toolbox™, it models the radiating elements that comprise a transmitter and the front-end receiver components, for a MIMO-OFDM communication annel: Filter input signal through MIMO multipath fading channel.

raeesi et al.: performance analysis of multi-user massive mimo downlink under channel non-reciprocity and imperfect csi 31 [24] J. Jose, A. Ashikhmin, T. Marzetta, and S. Vishwanath, “Pilot contamination and precoding in multi-cell TDD systems,” IEEE Transactions. 'The book Fundamentals of Massive MIMO elegantly combines the basic principles of large multi-user MIMO wireless systems with practical case studies, which makes it useful for both researchers and practitioners.

The fact that the book is fully self-contained also makes it an excellent teaching by: The accuracy of channel state information (CSI) available at a base station (BS) has a direct impact on the performance of precoding in wideband multi-user multiple input, multiple output-orthogonal frequency division multiplexing (MIMO-OFDM) systems and depends on many factors, including: the delay between estimation and beamforming at the BS (also called the CSI delay), Doppler spread, the Cited by: 4.

In Fig.we show ergodic sum-rate capacities for MF precoding and ZF precoding based on the expressions in Table As benchmark performance, we also plot the sum-rate capacity of an IF system. In all cases, K = 15 users are considered and we show results for N = 15,In all cases, it can be seen that ZF decisively outperforms : Muhammad R.A.

Khandaker, Kai-Kit Wong. MIMO-OFDM is a key technology for next-generation cellular communications (3GPP-LTE, Mobile WiMAX, IMT-Advanced) as well as wireless LAN (IEEE a, IEEE n), wireless PAN (MB-OFDM), and broadcasting (DAB, DVB, DMB). In MIMO-OFDM Wireless Communications with MATLAB®, the authors provide a comprehensive introduction to the theory and practice of wireless channel.

In the downlink MU-MIMO-OFDM transmission, inter-stream interference (ISI) is mitigated by pre-coding techniques, such as the linear processing approaches, including zero forcing (ZF) and block diagonalization (BD) [9,10], and the non-linear processing approaches, such as Tomlinson-Harashima precoding and vector perturbation [11,12].Conventional papers assume scenarios where the number Author: Tomoki Murakami, Yasushi Takatori, Fumiaki Maehara.

Per-user unitary rate control (PU 2 RC) is a multi-user MIMO (multiple-input and multiple-output) scheme. PU 2 RC uses both transmission pre-coding and multi-user scheduling. By doing that, the network capacity is further enhanced than the capacity of the single-user MIMO scheme.

Background technologies: A single-user MIMO was initially developed to improve the spectral efficiency of point-to. In this paper, a channel estimation (CE) and precoding scheme by using H-infinity (H-inf) criterion for mitigation of pilot contamination (PC) in massive multiple input multiple output (MIMO) orthogonal frequency division multiplexing (OFDM) systems is investigated.

Firstly, different thresholds in H-inf CE and precoding are considered. S. Jacobsson, G. Durisi, M. Coldrey, C. Studer, Linear precoding with low-resolution DACs for massive MU-MIMO-OFDM downlink.

IEEE Trans. Wireless Commun. 18(3), – () CrossRef Google ScholarAuthor: Fernando Gregorio, Gustavo González, Christian Schmidt, Juan Cousseau. My Google Scholar Citations Book.

Duy H. Nguyen and Tho Le-Ngoc, Wireless Coordinated Multicell Systems: Architectures and Precoding Designs, SpringerBriefs in Computer Science, SpringerISBNpp.

1– Book Chapter. Duy T. Ngo, Duy H. Nguyen, and Tho Le-Ngoc, “Intercell interference coordination: Towards a greener cellular network,” Chapter 6 in Handbook.

Björn Ottersten received the M.S. degree in electrical engineering and applied physics from Linkoping University, Linkoping, Sweden and the Ph.D. degree in electrical engineering from Stanford University, Stanford, CA. Ottersten has held research positions at the Department of Electrical Engineering, Linkoping University, the Information Systems Laboratory, Stanford University, and the.

MIMO technology has been standardized for wireless LANs, 3G mobile phone networks, and 4G mobile phone networks and is now in widespread commercial use.

Greg Raleigh and V. Jones founded Airgo Networks in to develop MIMO-OFDM chipsets for wireless LANs. The Institute of Electrical and Electronics Engineers (IEEE) created a task group in late to develop a wireless LAN standard.

Massive multiple-input-multiple-output (MIMO) systems use few hundred antennas to simultaneously serve large number of wireless broadband terminals.

It has been incorporated into standards like long term evolution (LTE) and IEEE (Wi-Fi). Basically, the more the antennas, the better shall be the performance.

Massive MIMO systems envision accurate beamforming and decoding with simpler and Cited by:   signal detection for spatially-multiplexed MIMO systems, precoding and antenna selectiontechniques, and multiuser MIMO MATLABÒprograms are presented in a complete form so that the readers with noprogramming skill can run them instantly and focus on understanding the concepts andcharacteristics of MIMO-OFDM systems.

The contents of.MIMO-OFDM is a key technology for next-generation cellular communications (3GPP-LTE, Mobile WiMAX, IMT-Advanced) as well as wireless LAN (IEEE a, IEEE n), wireless PAN (MB-OFDM), and broadcasting (DAB, DVB, DMB).

using MATLAB® programs to simulate the various techniques on MIMO-OFDM systems. as well as senior undergraduates.