Remarkable research activities and major advances have been occurred over the past decade in multiuser multiple-input multiple-output (MU-MIMO) systems. Several transmission technologies and precoding techniques have been developed in order to exploit the spatial dimension so that simultaneous transmission of independent data streams reuse the same radio resources. The achievable performance of such techniques heavily depends on the channel characteristics of the selected users, the amount of channel knowledge, and how efficiently interference is mitigated. In systems where the total number of receivers is larger than the number of total transmit antennas, user selection becomes a key approach to benefit from multiuser diversity and achieve full multiplexing gain. The overall performance of MU-MIMO systems is a complex joint multi-objective optimization problem since many variables and parameters have to be optimized, including the number of users, the number of antennas, spatial signaling, rate and power allocation, and transmission technique. The objective of this literature survey is to provide a comprehensive overview of the various methodologies used to approach the aforementioned joint optimization task in the downlink of MU-MIMO communication systems.

An Overview on Resource Allocation Techniques for Multi-User MIMO Systems

Long term evolution advanced (LTE-A) has emerged as a promising mobile broadband access technology aiming to cope with the increasing traffic demand in wireless networks. However, the enhanced spectral efficiency offered by LTE-A may become futile without a better management of scarce and overcrowded electromagnetic spectrum. In this sense, cognitive radio (CR) has been proposed as a potential solution to the problem of spectrum scarcity. Among all the mechanisms provided by CR, opportunistic spectrum access (OSA) aims at a dynamic and seamless use of certain licensed bands provided the licensee is not harmfully affected. This operation requires spectral awareness in order to avoid interferences with licensed systems. In spite of implementing some spectrum sensing mechanisms, LTE-A technology lacks other tools that are needed in order to improve the knowledge of the radio environment. This work studies the adoption of a Geo-located data base (Geo-DB) that cooperatively retrieves and maintains information regarding the location of unutilized portions of spectrum potentially available for OSA. Moreover, the potential benefit of this LTE-compliant OSA solution is evaluated using a calibrated simulation tool, by which numerical results allow us to optimally configure the system and show that the proposed opportunistic system is able to significantly improve its performance.

/pdf/implementing-opportunistic-spectrum-access-in-lte-advanced-1bmrtdhtn3.pdf

Implementing opportunistic spectrum access in LTE-advanced

The present disclosure provides an orthogonal codes based code division multiplexing method of performing the code division multiplexing of demodulation reference signals in multiple layers of resource blocks by using orthogonal matrices, the method comprising: changing the order of chips in particular rows of a first orthogonal matrix to obtain a second orthogonal matrix with the changed order of chips; and multiplying the chips in respective rows of the second orthogonal matrix by the demodulation reference signals in corresponding layers of resource blocks correspondingly in the time direction to obtain code division multiplexing signals. The technical scheme of the present disclosure can improve the power jitter situation of downlink signals on the time, thereby the usage efficiency of the power amplifier at the base station side can be improved.

Orthogonal codes based code division multiplexing method, multiplexing device, and de-multiplexing device

In accordance with an embodiment, a method of operating a base station configured to communicate with at least one user device includes transmitting a reference signal to the at least one user device, receiving channel quality information from the at least one user device, and forming a beam based on the channel quality information received from the at least one user device.

System and method for downlink channel sounding in wireless communications systems

Rank-specific feedback for improved mimo support

PROBLEM TO BE SOLVED: To provide an MIMO precoding method and an apparatus for the method. SOLUTION: In the method, an equivalent channel matrix is obtained using respective precoding matrixes in a prescribed code book and a channel state information matrix, the obtained equivalent channel matrix is decomposed to obtain a triangle matrix corresponding to the respective precoding matrixes, the precoding matrix corresponding to the triangle matrix for which the minimum value of the absolute value of diagonal elements is the largest is selected, and precoding is executed to signals to be transmitted after removing interference between streams using the precoding matrix. The precoding apparatus includes a precoding matrix selection module and a precoding module. Signal transmission quality in the MIMO system of a single user and multiple users can be effectively improved. COPYRIGHT: (C)2010,JPO&INPIT

Multiple-input and multiple-output precoding method and apparatus for the method

The invention discloses a multiple-input and multiple-output precoding method and device. In the method, an equivalent channel matrix is obtained by each precoding matrix and each channel state information matrix in a predetermined codebook; after the equivalent channel matrix is analyzed, a triangular matrix corresponding to each precoding matrix is obtained; a precoding matrix with a maximal minimum value of diagonal element absolute values is selected, and a pre-transmitting signal with eliminated inter-stream interference is precoded by using the precoding matrix. The precoding device comprises a codebook selecting module and a precoding module. The invention can effectively improve the signal transmission quality in a single-user and multi-user MIMO system.

Multiple-input and multiple-output precoding method and device

The invention provides a precoding transmission method for a multi-input and multi-output system, which comprises: a mobile station supposes an emission matrix as a unitary matrix, an MMSE receiver is used for signal combination, an equative channel is calculated, CQI and CDI are obtained and are fed back a base station; according to a channel direction index and channel quality information fed by the mobile station, the base station obtains a zero-forcing precoding emission matrix or a regulated zero-forcing precoding emission matrix corresponding to partial or total possible user combination, carries out multiuser scheduling operation and determines the scheduled user combination; and the base station utilizes the zero-forcing precoding emission matrix or the regulated zero-forcing precoding emission matrix corresponding to the scheduled user combination to carry out precoding and emission; and a scheduled user carries out MMSE receiving The method reduces error of channel feedback, therefore effectively promoting the utilization ratio of frequency spectrum of the system

Pre-encoded transmission method for MIMO system

The invention provides an uplink precoding method and a base station. The uplink precoding method is applied to a multi-mobile-station multi-input multi-output system and includes that the base station receives reference signals respectively sent by each of at least two mobile stations; aiming at each mobile station, the base station performs channel estimation according to corresponding reference signals to obtain channel response matrixes corresponding to each mobile station; the base station obtains indexes of precoders corresponding to each data stream to be sent of each mobile station, and the indexes of the precoders of the data streams to be sent of at least one mobile station are obtained according to the channel response matrixes of the mobile stations and channel response matrixes of the mobile stations corresponding to other data streams to be sent; the base station sends the indexes to corresponding mobile stations; and the base station performs operation of receiving matrixes, thereby working out useful signals. The uplink precoding method and the base station improve throughput of a system.

Uplink precoding method and base station

This paper proposes new limited-feedback Channel State Information (CSI) calculation schemes for Zero Forcing (ZF)-precoded downlink Multi-User Multiple-Input Multiple-Output (MU-MIMO) systems. It is a common understanding that the feedback quantized by the codebook limits the performance of MU-MIMO. In this paper, through a quasi-ZF or a quasi-Minimum Mean-Squared Error (MMSE) weight, the channel matrix is transferred to one of the codebook vectors, based on which, the CSI is calculated. Thus, the quantization error is minimized. Meanwhile, the selection for the codebook vector guarantees the maximizing of the estimated Signal to Interference plus Noise Ratio (SINR). We verify that the proposed scheme obtains accurate feedback information, and the predicted weight can be the same as the optimal linear decoder as if the receiver knew all the precoder information that is fed-forward from the BS, as long as the number of antennas for each receiver equals that for the transmitter, and equals that for the total transmit data streams. Compared to the commonly used Precoding Matrix Index (PMI) based method, which uses rank-one single user (SU)-MIMO feedback, simulation results show that the proposed schemes achieve higher sum capacities in different scenarios. Moreover, since the weight can be directly used as the decoder, the feed-forward overhead is reduced.

Enhanced Limited Feedback Schemes for DL MU-MIMO ZF Precoding

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Wei Wang

Author Tools

Chat about Author