Relevant bibliographies by topics / MIMO multi users

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'MIMO multi users'

Author: Grafiati
Published: 25 May 2024

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Consult the lists of relevant articles, books, theses, conference reports, and other scholarly sources on the topic 'MIMO multi users.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Journal articles on the topic "MIMO multi users"

1

Sheu, Jeng-Shin, and Kuan-Ming Huang. "Performance Comparison for Single-User and Multi-User Network MIMO Cellular Systems with Power Management." Applied Sciences 11, no. 21 (November 2, 2021): 10298. http://dx.doi.org/10.3390/app112110298.

Full text
Abstract:
Cellular mobile systems aim at aggressive spectrum reuse to achieve high spectral efficiency. Unfortunately, this leads to unacceptable interference near cell borders. To control this, network multi-input multiple-output (MIMO) can be adopted to improve coverage and cell-edge throughput through multi-cell cooperation. With network MIMO, multiple geographically separated base stations (BSs) cooperatively serve their cell-edge users (CEUs) using their antennas, acting together as a network of distributed antenna array. It can be single-user (SU) or multi-user (MU) network MIMO by coordinating channel allocation in adjacent cells. In this paper, we make a capacity comparison of SU- and MU-network MIMO. In network MIMO, a collaborative BS simultaneously serves its own cell-center users (CCUs) and CEUs, and the CEUs of other partner BSs under a power constraint. As a result, power management among three types of users (intra-cell CCUs/CEUs, inter-cell CEUs) becomes necessary. Accordingly, we propose power management methods to help raise the signal strength of inter-cell CEUs and in the meantime gratify the performance of intra-cell users. Simulation results show that MU-network MIMO with superposition coding offers much better CEU capacity than SU-network MIMO. As for the CCU capacity, MU-network MIMO is generally better than SU-network MIMO.
APA, Harvard, Vancouver, ISO, and other styles
2

Zhong, Shida, Haogang Feng, Peichang Zhang, Jiajun Xu, Lei Huang, Tao Yuan, and Yongkai Huo. "User Oriented Transmit Antenna Selection in Massive Multi-User MIMO SDR Systems." Sensors 20, no. 17 (August 28, 2020): 4867. http://dx.doi.org/10.3390/s20174867.

Full text
Abstract:
A transmit antenna selection (TxAS) aided multi-user multiple-input multiple-output (MU-MIMO) system is proposed for operating in the MIMO downlink channel environments, which shows significant improvement in terms of higher data rate when compared to the conventional MU-MIMO systems operating without adopting TxAS, while maintaining low hardware costs. We opt for employing a simple yet efficient zero-forcing beamforming (ZFBF) linear precoding scheme at the transmitter in order to reduce the decoding complexity when considering users’ side. Moreover, considering that users within the same cell may require various qualities of service (QoS), we further propose a novel user-oriented smart TxAS (UOSTxAS) scheme, of which the main idea is to carry out AS based on the QoS requirements of different users. At last, we implement the proposed UOSTxAS scheme in the software defined radio (SDR) MIMO communication hardware platform, which is the first prototype hardware system that runs the UOSTxAS MU-MIMO scheme. Our results show that, by employing TxAS, the proposed UOSTxAS scheme is capable of offering higher data rates for priority users, while reasonably ensuring the performance of the common users requiring lower rates both in simulation and in the implemented SDR MIMO communication platform.
APA, Harvard, Vancouver, ISO, and other styles
3

Naeem, Muddasar, Antonio Coronato, Zaib Ullah, Sajid Bashir, and Giovanni Paragliola. "Optimal User Scheduling in Multi Antenna System Using Multi Agent Reinforcement Learning." Sensors 22, no. 21 (October 28, 2022): 8278. http://dx.doi.org/10.3390/s22218278.

Full text
Abstract:
Multiple Input Multiple Output (MIMO) systems have been gaining significant attention from the research community due to their potential to improve data rates. However, a suitable scheduling mechanism is required to efficiently distribute available spectrum resources and enhance system capacity. This paper investigates the user selection problem in Multi-User MIMO (MU-MIMO) environment using the multi-agent Reinforcement learning (RL) methodology. Adopting multiple antennas’ spatial degrees of freedom, devices can serve to transmit simultaneously in every time slot. We aim to develop an optimal scheduling policy by optimally selecting a group of users to be scheduled for transmission, given the channel condition and resource blocks at the beginning of each time slot. We first formulate the MU-MIMO scheduling problem as a single-state Markov Decision Process (MDP). We achieve the optimal policy by solving the formulated MDP problem using RL. We use aggregated sum-rate of the group of users selected for transmission, and a 20% higher sum-rate performance over the conventional methods is reported.
APA, Harvard, Vancouver, ISO, and other styles
4

Handayani, Puji, and Beny Burhanusshomad. "Kinerja Multi-user MIMO OFDM dengan Block-Diagonalization Precoding." Jurnal JEETech 4, no. 1 (February 6, 2023): 15–19. http://dx.doi.org/10.32492/jeetech.v4i1.4103.

Full text
Abstract:
Multiple-input multiple-output (MIMO) is a transmission technology that uses more than one antenna both on the transmitter side and on the receiver side. In the communication services, the system will involve more than one active user who uses one base station (BS) together so that it is called multi-user MIMO (MU-MIMO). This paper discusses the performances of MU-MIMO when it uses block diagonalization (BD) precoding and applies minimum mean squared error (MMSE) detector. As a comparison we also apply zero-forcing (ZF) detector. From the simulations that have been done, it is found that the MMSE had better performances than the ZF detector in terms of BER. We also consider the performance when users are moving. The simulation results show that BER performances are decrease slowly when users are moving.
APA, Harvard, Vancouver, ISO, and other styles
5

Raviv, Li-on, and Amir Leshem. "Scheduling for Multi-User Multi-Input Multi-Output Wireless Networks with Priorities and Deadlines." Future Internet 11, no. 8 (August 5, 2019): 172. http://dx.doi.org/10.3390/fi11080172.

Full text
Abstract:
The spectral efficiency of wireless networks can be significantly improved by exploiting spatial multiplexing techniques known as multi-user MIMO. These techniques enable the allocation of multiple users to the same time-frequency block, thus reducing the interference between users. There is ample evidence that user groupings can have a significant impact on the performance of spatial multiplexing. The situation is even more complex when the data packets have priority and deadlines for delivery. Hence, combining packet queue management and beamforming would considerably enhance the overall system performance. In this paper, we propose a combination of beamforming and scheduling to improve the overall performance of multi-user MIMO systems in realistic conditions where data packets have both priority and deadlines beyond which they become obsolete. This method dubbed Reward Per Second (RPS), combines advanced matrix factorization at the physical layer with recently-developed queue management techniques. We demonstrate the merits of the this technique compared to other state-of-the-art scheduling methods through simulations.
APA, Harvard, Vancouver, ISO, and other styles
6

VijayaLakshmi, Dr M., and C. Anisha. "Massive MIMO-OFDM Transmission Without Cellular Networks Using Frequency - Selective Fading Channels." International Journal for Research in Applied Science and Engineering Technology 11, no. 10 (October 31, 2023): 1410–17. http://dx.doi.org/10.22214/ijraset.2023.56225.

Full text
Abstract:
Abstract: For cell-free massive multi-input multi-output (CF-m-MIMO) across frequency-selective fading channels, this system introduces and determines the effectiveness of the orthogonal frequency-division multiplexing (OFDM)-based multi-carrier transmission. The CF-m-MIMO-OFDM system can accommodate a substantial user base and is flexible enough to offer a range of data rates for usage in a variety of contexts. With its scalability and flexibility, the CF-m-MIMO-OFDM transmission network can serve a large number of users at variable data rates. It is proposed to beamform in the frequency-domain conjugate, to choose a pilot, and to allocate resources differently for each user. User-specific resource allocation, pilot selection, and frequency-domain conjugate beamforming are all suggested. The CF-m-MIMO-OFDM system can support a large number of users and can offer varying data rates to accommodate a wide range of applications.
APA, Harvard, Vancouver, ISO, and other styles
7

Dai, Jian Xin, Jun Zhou, Jie Qi, Ming Chen, Tao Yuan, and Jun Zhao. "Optimal Power Analysis of Downlink Multi-User SA-MIMO Systems Use." Applied Mechanics and Materials 614 (September 2014): 530–34. http://dx.doi.org/10.4028/www.scientific.net/amm.614.530.

Full text
Abstract:
This paper investigated the problem of transmit power minimization to meet the users’ outage probability constraints in downlink smart antennas-MIMO (SA-MIMO) systems. Firstly, a downlink multi-user SA-MIMO system model is established, and the transmit power optimization problem is formulated. The optimization problem jointly optimizes the beam-forming vectors and user outage probability. Then, the outage-based optimization problem is transformed into a geometric programming problem in which the beam forming vectors were obtained by maximum diagonal element (MDE) rule. Some numerical results show that the proposed method in this paper is viable and the transmit power in downlink SA-MIMO systems significantly descreases relative to traditional MIMO systems.
APA, Harvard, Vancouver, ISO, and other styles
8

Zhu, Mengyu, Shaoshuai Gao, Guofang Tu, and Deyuan Chen. "Multi-Access Edge Computing (MEC) Based on MIMO: A Survey." Sensors 23, no. 8 (April 11, 2023): 3883. http://dx.doi.org/10.3390/s23083883.

Full text
Abstract:
With the rapid development of wireless communication technology and the emergence of intelligent applications, higher requirements have been put forward for data communication and computing capacity. Multi-access edge computing (MEC) can handle highly demanding applications by users by sinking the services and computing capabilities of the cloud to the edge of the cell. Meanwhile, the multiple input multiple output (MIMO) technology based on large-scale antenna arrays can achieve an order-of-magnitude improvement in system capacity. The introduction of MIMO into MEC takes full advantage of the energy and spectral efficiency of MIMO technology, providing a new computing paradigm for time-sensitive applications. In parallel, it can accommodate more users and cope with the inevitable trend of continuous data traffic explosion. In this paper, the state-of-the-art research status in this field is investigated, summarized and analyzed. Specifically, we first summarize a multi-base station cooperative mMIMO-MEC model that can easily be expanded to adapt to different MIMO-MEC application scenarios. Subsequently, we comprehensively analyze the current works, compare them to each other and summarize them, mainly from four aspects: research scenarios, application scenarios, evaluation indicators and research issues, and research algorithms. Finally, some open research challenges are identified and discussed, and these indicate the direction for future research on MIMO-MEC.
APA, Harvard, Vancouver, ISO, and other styles
9

Fang, Tianhao, Yangyang Gao, Chaoju Suo, Gangle Sun, Pengyu Chen, Wei Xiao, and Wenjin Wang. "A Multi-Beam XL-MIMO Testbed Based on Hybrid CPU-FPGA Architecture." Electronics 12, no. 2 (January 11, 2023): 380. http://dx.doi.org/10.3390/electronics12020380.

Full text
Abstract:
To support more users and higher data rates in future communication networks, the extremely large-scale massive multiple-input multiple-output (XL-MIMO) is considered a promising technique. The booming research on XL-MIMO necessitates a reconfigurable XL-MIMO testbed that can be used to validate new research ideas in real wireless environments and collect data for XL-MIMO channel characteristics analysis. To provide such a reliable and convenient testbed, we designed a multi-beam XL-MIMO testbed based on the hybrid CPU-FPGA architecture and channel calibration schemes. The ability to customize modules makes our testbed a convenient verification platform for future communication systems. Moreover, numerous trial measurement results in the indoor near-field scenario with moderate user equipment (UE) mobility are presented, and the excellent performance indicates that our testbed is an ideal platform for the evaluation of XL-MIMO-related algorithms.
APA, Harvard, Vancouver, ISO, and other styles
10

Stankovic, Veljko. "Iterative successive MMSE multi-user MIMO transmit filtering." Facta universitatis - series: Electronics and Energetics 20, no. 1 (2007): 45–55. http://dx.doi.org/10.2298/fuee0701045s.

Full text
Abstract:
In this paper we introduce a novel linear preceding technique. It was previously reported in the literature that when the user terminals are equipped with one antenna, minimum mean-squared-error (MMSE) in combination with successive interference cancellation is optimum on the uplink, while MMSE preceding in combination with Tomlinson-Harashima preceding (THP) is optimum on the downlink. The linear preceding technique introduced in this paper is based on the modified MSB criterion. It can serve the users that are equipped with arbitrary number of antennas with only limitation that the total number of users in the system has to be less than or equal to the rank of the combined multiple-input multiple-output (MIMO) channel matrix of all users. It was shown in the simulations that it extracts very high diversity gain and at low signal-to-noise ratios, when the total number of antennas at the user terminals is greater than the number of antennas at the base station, it approaches the maximum sum rate capacity of the broadcast channel. The technique introduced in this paper is favorable for practical implementation since it requires by an order of magnitude less operations than the techniques based on the singular value decomposition.
APA, Harvard, Vancouver, ISO, and other styles
More sources

Dissertations / Theses on the topic "MIMO multi users"

1

Ghamnia, Imène. "Rate balancing methods for multi-user MIMO systems with perfect or partial CSIT." Electronic Thesis or Diss., Sorbonne université, 2021. https://accesdistant.sorbonne-universite.fr/login?url=https://theses-intra.sorbonne-universite.fr/2021SORUS234.pdf.

Full text
Abstract:
Avec la progression de l'utilisation des smartphones, les modèles de systèmes ont rapidement évolué pour répondre aux besoins croissants en terme de capacité dans les réseaux sans fil. En effet, les progrès technologiques ont été considérables, depuis les communications point à point mono-utilisateur et mono-antenne jusqu'aux réseaux cellulaires multi-cellules et multi-antennes. Depuis la 3G, la technologie MIMO (multiple-input multiple-output) pour les communications sans fil est désormais intégrée aux normes de la large bande sans fil. L'ajout de plusieurs antennes, tant du côté de l'émetteur que du côté du récepteur, permet le multiplexage spatial (c'est-à-dire l'envoi simultané de plusieurs flux de données), qui permet d'augmenter les débits de données, et l'exploitation de la diversité spatiale, améliorant considérablement la qualité des liaisons. MIMO Multi-Utilisateurs (MU) a été un sujet bien étudié dans le domaine des communications sans fil en raison du grand potentiel qu'il offre pour améliorer le débit du système. Par conséquent, différents critères de conception pour les communications MIMO MU ont été étudiés dans la littérature. La plupart des conceptions de liaisons descendantes prennent en compte les problèmes d'optimisation de la capacité totale de tous les utilisateurs. D'autre part, la principale limitation des communications sans fil modernes est l'interférence (intracellulaire et intercellulaire) due à la réutilisation des fréquences. Ainsi, dans un scénario MIMO MU, lors de l'optimisation de l'efficacité globale, l'allocation de puissance se concentre sur les bons canaux, c'est-à-dire que les utilisateurs soumis à une forte interférence (e.g., les utilisateurs en bordure de cellule) sont délaissés. Il en résulte une répartition inéquitable de puissance entre les utilisateurs. Pour pallier ce problème, différentes notions d'équité sont introduites, comme l'équité max-min, l'équité pondérée ou l'équité proportionnelle. Dans cette thèse, nous nous concentrons sur l'équité max-min pondérée. En particulier, nous étudions le problème de l'équilibrage du débit pondéré par utilisateur dans un système MIMO multi-cellules MU. Nous abordons ce dernier dans le cadre d'une formulation conjointe du problème de beamforming et d'allocation de puissance, visant à satisfaire l'exigence d'équité. Dans la première partie, nous considérons la connaissance parfaite du canal pour résoudre le problème. Dans ce cas, nous maximisons le débit minimum pondéré via i) la dualité liaison montante/descendante et ii) la dualité Lagrangienne. Dans la deuxième partie, nous considérons la connaissance partielle du canal. Nous optimisons le problème d'équilibrage de débit ergodique via i) l'erreur quadratique moyenne pondérée (EQM) en exploitant la relation débit - EQM, et ii) deux approximations du débit estimé comme le débit de signal et de puissance d'interférence estimés (ESIP) au niveau du flux et du signal reçu. Par ailleurs, nous proposons une stratégie d'efficacité énergétique au moyen des approches d'équilibrage des débits proposées
With the rise in smartphone usage, the system models have rapidly evolved to meet ever-growing needs for capacity in wireless networks. Indeed, there have been large advances in technology, from single-user single-antenna point-to-point communications to multi-cell multi-antenna cellular networks. In fact, multiple-input multiple-output (MIMO) technology for wireless communications is now incorporated into wireless broadband standards since 3G. Adding multiple antennas at both the transmitter and the receiver sides enables spatial multiplexing (i.e. sending multiple data streams simultaneously), which allows to increase data rates, and spatial diversity exploitation, which allows to greatly improve link quality. The multi-user MIMO downlink (so-called Broadcast Channel (BC)) has been a well investigated subject in wireless communications because of the high potential it offers in improving the system throughput. Therefore, different design criteria for multi-user MIMO communication have been investigated in the literature. Most of the downlink designs consider optimization problems w.r.t. the sum-capacity of all users. On the other hand, the major bottleneck of modern wireless communication is the interference (intracell and intercell) due to frequency reuse. Thus, in a multi-user MIMO scenario, when optimizing the overall efficiency, the power allocation is focused on the good channels, i.e., users that are subject to strong interference (e.g. cell-edge users) are neglected. The result is an unfair distribution of rate among users. In order to avoid this effect, different fairness notions have been introduced, like max-min fairness, weighted fairness, or proportional fairness. In this thesis, we focus on the weighted max-min fairness. In particular, we study the (weighted) user rate balancing problem in a multi-cell multi-user MIMO system. We address this problem by joint beamforming and power allocation optimization, aiming to satisfy the fairness requirements. In the first part, we consider perfect knowledge of the channel to solve the problem. Therein, we maximize the minimum (weighted) rate via i) weighted user Mean Square Error (MSE) uplink/downlink duality and ii) Lagrangian duality. In the second part, we consider partial knowledge of the channel. We optimize the ergodic rate balancing problem via i) weighted expected MSE by exploiting the rate – MSE relation, and ii) two approximations of the expected rate as the Expected Signal and Interference Power (ESIP) rate at the stream level and the received signal level. Furthermore, we study the transmit power minimization problem with fixed user-rate targets and provide a strategy exploiting the proposed rate balancing approaches
APA, Harvard, Vancouver, ISO, and other styles
2

Choi, Lai U. "Multi-user MISO and MIMO transmit signal processing for wireless communication /." View Abstract or Full-Text, 2003. http://library.ust.hk/cgi/db/thesis.pl?ELEC%202003%20CHOI.

Full text
Abstract:
Thesis (Ph. D.)--Hong Kong University of Science and Technology, 2003.
Includes bibliographical references (leaves 167-170). Also available in electronic version. Access restricted to campus users.
APA, Harvard, Vancouver, ISO, and other styles
3

Stanković, Veljko. "Multi-user MIMO wireless communications." [S.l.] : [s.n.], 2007. http://deposit.ddb.de/cgi-bin/dokserv?idn=985258039.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Wei, Chun-Yi. "Iterative downlink multi-user MIMO systems." Thesis, University of Southampton, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.485522.

Full text
Abstract:
In this treatise, we explore diverse multi-user transmission techniques and joint detection-decoding schemes designed for downlink multi-user transmissions, while maintaining a low complexity, a high throughput and a high integrity. More specifically, in Chapter 2 we will introduce various Multi-User Transmission (MUT) techniques for the Space Division Multiple Access Down-Link (DL-SDMA) employing the sophisticated linear SpatioTemporal Pre-processing (STP) schemes, which are capable of eliminating the multi-user interference at the Base Station (BS) and increase the transmission integrity at the Mobile Sta,ions (MS). Additionally, we will design signal detection techniques for the DL-SDMA system, which achieves a near-Maximum Likelihood (ML) performance at a fraction of the ML detector's complexity. In Chapter 3 we extend our research to a joint iterative detection and decoding based DL-SDMA system. We will introduce a precoder aided iterative DL-SDMA system, which is designed with the aid of Extrinsic Information Transfer (EXIT) charts and has an improved iterative decoding gain. Finally, we will characterize the impact of imperfect Channel State Information (CSI) on the proposed iterative DL-SDMA and introduce sophisticated IrRegular Convolutional Codes (IRCC) for improving the integrity of the iterative DL-SDMA system. In order to reduce the complexity of the iterative receivers, in Chapter 4 we will introduce a novel detection algorithm, which is referred to as the Irregular Generic Detection (IrGD) algorithm. The IrGD has a tunable • complexity and it was particularly designed for redUcing the complexity of the iterative decoding aided system. Furthermore, we will demonstrate the impact of imperfect CSI with the aid of EXIT charts. In addition, we will introduce an EXIT-Chart Optimized CSI Quantizer (ECO-CQ) for the iterative DL-SDMA system, which is capable of reducing CSI-related feedback overhead. In Chapter 5 we will introduce an advanced space-time signaling technique aided MUT designed for the DL-SDMA system, which results in an improved capacity. Furthermore, we will propose a low-complexity Irregular Sphere Detection (IrSD) scheme designed for approaching the capacity DL-SDMA systems, which is capable of maintaining a near-ML performance. Additionally, we will characterize our pilot assisted channel prediction aided DL-SDMA system using limited CSI feedback.
APA, Harvard, Vancouver, ISO, and other styles
5

Wang, Cheng. "Adaptive downlink multi-user MIMO wireless systems /." View abstract or full-text, 2007. http://library.ust.hk/cgi/db/thesis.pl?ECED%202007%20WANG.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Keskin, Faruk. "Precoding for MIMO multi-user mobile radio downlinks." [Kaiserslautern] : [Universitätsbibliothek], 2007. http://d-nb.info/989961354/34.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Anderson, Adam L. "Correlation-based beamforming for multi-user MIMO channels." Diss., Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC campuses, 2008. http://wwwlib.umi.com/cr/ucsd/fullcit?p3331446.

Full text
Abstract:
Thesis (Ph. D.)--University of California, San Diego, 2008.
Title from first page of PDF file (viewed December 16, 2008). Available via ProQuest Digital Dissertations. Vita. Includes bibliographical references (p. 144-151).
APA, Harvard, Vancouver, ISO, and other styles
8

Patcharamaneepakorn, Piya. "Precoding designs for multi-user MIMO and multi-cell cooperative systems." Thesis, University of Bristol, 2014. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.649371.

Full text
Abstract:
In this thesis, linear precoding designs and scheduling algorithms are studied based on the maximum Signal-to-Leakage-plus-Noise Ratio (SLNR) criteria in single-cell Multi-user MIMO (MU-MIMO) systems as well as in multi-cell MIMO cooperative networks. The conventional SLNR precoding scheme is firstly investigated. Analytic expressions of the conventional SLNR-based solution are derived and are shown to be a generalised form of regularised channel inversion techniques. Consequently, equivalence between the SLNR and other regularised channel inversion schemes for the case of single-antenna and multi-antenna receivers can be established. This provides an alternative view of the conventional SLNR precoding design and leads to several useful implications in terms of possible exchange of relevant algorithms and performance analysis among these linear precoding schemes. One of the main issues of the conventional SLNR precoding design for the case that all available eignmodes are not fully transmitted is then addressed. Enhanced leakage-based precoding designs are proposed and are thoroughly studied in single-cell MU-MIMO based on two main approaches, i.e. the receive antenna selection and the enhanced receive subspace estimation. The latter is seen to be superior to the former and, as a result, serves as an underlying technique for subsequent studies. The proposed leakage-based precoding designs with receive subspace estimation techniques are further applied to the transceiver design for achieving the maximum Weighted Sum Rate (WSR) in single-cell MU-MIMO systems. Based on the proposed trallsceiver structure, the problem call be simplified into two different problems, i.e. the power allocation and the data stream selection problems, to which the solutions are separately proposed. The resulting precoding designs are shown to have comparable performance to existing joint Transmit (TX)-Receive (RX) filter designs despite requiring simpler receiver structures. The enhanced leakage-based transceiver designs are also extended from the single-cell MU-MIMO systems to multi-cell coordinated beamforming scenarios. Further, the resulting transceiver designs are applied to the WSR maximisation problem in the multi-cell case by extending the power allocation and the data stream selection approaches as previously studied in the single-cell case to the multi-cell coordinated beamforming systems.
APA, Harvard, Vancouver, ISO, and other styles
9

Tervo, O. (Oskari). "Effective channel state acquisition in multi-cell multi-user MIMO system." Master's thesis, University of Oulu, 2013. http://urn.fi/URN:NBN:fi:oulu-201306011414.

Full text
Abstract:
In a cellular network with small cells, where all the communication resources are shared, the inter-cell interference becomes a limiting factor of performance. The strategies for mitigating the inter-cell interference has been quite extensively studied lately. One of the promising candidates is coordinated beamforming/scheduling, where a certain number of cells is allowed to cooperate such that the transmission from each cell takes into account the interference it would cause to the users of other cells. In this thesis, the performances of different signaling strategies which perform the weighted sum rate maximization in time division duplex multi-cell multi-user MIMO downlink system are studied. The strategies consist of iterative decentralized algorithms, aiming at reduced pilot signaling overhead and faster convergence. The required control information between the cells is provided via uplink reference signals and a backhaul. Uplink reference signals include sounding reference signals and busy bursts. Based on the earlier work, the strategies have now been extended to a larger cellular system in which the frequency selectivity and the uncertainty of the channel information are also taken into account. The ability of the strategies to handle the large network can be seen from the simulation results. It is shown that even when there is strong inter-cell interference, the strategies utilizing parallel cell-specific iterations offer practical convergence speed. It is also noticed that the joint optimization over many frequency blocks brings a minor improvement on the sum rate performance, meaning that it could also be utilized with the same order of computational complexity compared to the frequency flat case. Finally, the robustness of the centralized strategy to the imperfect channel state information is shown and the trade-off between the CSI uncertainty and multi-user diversity is stated
Solukkoverkossa, jossa solujen koot ovat pieniä ja kaikki käyttävät samoja taajuuksia, solujen välinen häiriö rajoittaa verkon suorituskykyä. Viime aikoina on laajasti tutkittu strategioita, joilla häiriötä saataisiin vähennettyä. Yksi lupaavista menetelmistä tähän tarkoitukseen on koordinoitu keilanmuodostus/skedulointi, jossa tietty ryhmä soluja voi koordinoida keskenään ja näin ottaa huomioon lähetyksestä aiheutuvan häiriön toisia soluja kohtaan. Tässä diplomityössä tutkitaan erilaisten painotetun summadatanopeuden maksimoivien signalointistrategioiden suorituskykyä aikajakodupleksoidussa usean solun ja käyttäjän moniantenniverkossa, jossa dataa lähetetään tukiasemasta käyttäjille. Strategiat perustuvat iteratiivisiin hajautettuihin algoritmeihin, joiden tarkoituksena on vähentää opetussignaloinnista aiheutuvaa kuormitusta ja nopeuttaa suppenemista. Kontrolli-informaation signaloimiseen verkossa käytetään käyttäjiltä tukiasemille lähetettäviä opetussignaaleja ja taustayhteyttä tukiasemien välillä. Työ perustuu aiemmin tehtyyn tutkimukseen, josta strategiat on nyt laajenettu suurempaan solukkojärjestelmään, ottaen huomioon myös taajuusselektiivisyyden ja kanavainformaation epävarmuuden vaikutukset. Simulointitulosten perusteella voidaan sanoa, että strategiat toimivat usean käyttäjän ja solun verkossa. Tuloksista nähdään, että rinnakaisia solukohtaisia iteraatioita hyödyntävillä strategioilla voidaan saavuttaa käytännöllinen suppenemisnopeus, vaikka solujen välinen häiriö on voimakasta. Taajuusselektiivisen kanavan tuloksista huomataan, että yhteisoptimointi usean taajuuslohkon yli parantaa vähän suorituskykyä verrattuna yhden taajuuden tapaukseen. Yhteisoptimointia voitaisiin siis myös hyödyntää, koska laskennallinen monimutkaisuus on samaa suuruusluokkaa verrattuna yhden taajuuden tilanteeseen. Epävarman kanavatiedon vaikutusta tutkitaan keskitetyllä optimointimenetelmällä, joka selvästi laskee suorituskykyä verrattuna täydellisen kanavan tapaukseen, mutta antaa kuitenkin selkeän parannuksen alkuperäiseen algoritmiin verrattuna. Koska opetussignaalien teho jaetaan käyttäjien kesken, tulokset näyttävät kompromissin kanavatiedon epävarmuuden ja monikäyttäjädiversiteetin välillä
APA, Harvard, Vancouver, ISO, and other styles
10

Chen, Chiang-Yu. "Optimized resource allocation for MIMO multi-carrier multi-user communication systems /." May be available electronically:, 2008. http://proquest.umi.com/login?COPT=REJTPTU1MTUmSU5UPTAmVkVSPTI=&clientId=12498.

Full text
APA, Harvard, Vancouver, ISO, and other styles
More sources

Books on the topic "MIMO multi users"

1

Ben Zid, Maha, ed. Recent Trends in Multi-user MIMO Communications. InTech, 2013. http://dx.doi.org/10.5772/3306.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

MIMO Wireless Networks: Channels, Techniques and Standards for Multi-Antenna, Multi-User and Multi-Cell Systems. Elsevier Science & Technology Books, 2013.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
3

Oestges, Claude, and Bruno Clerckx. MIMO Wireless Networks: Channels, Techniques and Standards for Multi-Antenna, Multi-User and Multi-Cell Systems. Elsevier Science & Technology Books, 2013.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
4

Ho, Lok Pan. MIMO multi-user precoding with and without channel estimation errors. 2007, 2007.

Find full text
APA, Harvard, Vancouver, ISO, and other styles

Book chapters on the topic "MIMO multi users"

1

Tufvesson, Fredrik, Katsuyuki Haneda, and Veli-Matti Kolmonen. "Multi-User MIMO Channels." In LTE-Advanced and Next Generation Wireless Networks, 187–213. Chichester, UK: John Wiley & Sons, Ltd, 2012. http://dx.doi.org/10.1002/9781118410998.ch7.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Rupp, Markus, Stefan Schwarz, and Martin Taranetz. "Advanced Multi User MIMO Concepts." In The Vienna LTE-Advanced Simulators, 143–76. Singapore: Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-0617-3_7.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Sanguinetti, Luca, and H. Vincent Poor. "Fundamentals of Multi-User MIMO Communications." In New Directions in Wireless Communications Research, 139–73. Boston, MA: Springer US, 2009. http://dx.doi.org/10.1007/978-1-4419-0673-1_6.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Prasad, Ramjee, Suvra Sekhar Das, and Muhammad Imadur Rahman. "MIMO Precoding in Multi-User Scenarios." In Adaptive PHY-MAC Design for Broadband Wireless Systems, 307–19. New York: River Publishers, 2022. http://dx.doi.org/10.1201/9781003336969-11.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Speidel, Joachim. "Principles of Multi-user MIMO Transmission." In Signals and Communication Technology, 269–91. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-00548-1_24.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Speidel, Joachim. "Principles of Multi-user MIMO Transmission." In Signals and Communication Technology, 305–27. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-67357-4_20.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Mielczarek, B., and W. A. Krzymien. "Throughput of Heterogeneous Multi-Cell Multi-User MIMO-OFDM Systems." In Multi-Carrier Spread-Spectrum, 127–36. Dordrecht: Springer Netherlands, 2006. http://dx.doi.org/10.1007/1-4020-4437-2_13.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Zhang, Chenxin, Liang Liu, and Viktor Öwall. "Future Multi-User MIMO Systems: A Discussion." In Heterogeneous Reconfigurable Processors for Real-Time Baseband Processing, 155–69. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-24004-6_7.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Bilenne, Olivier, Panayotis Mertikopoulos, and E. Veronica Belmega. "Derivative-Free Optimization over Multi-user MIMO Networks." In Network Games, Control and Optimization, 17–24. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-87473-5_3.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Yuan, Weijie, Nan Wu, and Jingming Kuang. "Downlink Multi-user Detection for MIMO-SCMA System." In Receiver Design for High Spectral Efficiency Communication Systems in Beyond 5G, 29–57. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-8090-9_3.

Full text
APA, Harvard, Vancouver, ISO, and other styles

Conference papers on the topic "MIMO multi users"

1

Bandemer, Bernd, Martin Haardt, and Samuli Visuri. "Linear MMSE Multi-User MIMO Downlink Precoding for Users with Multiple Antennas." In 2006 IEEE 17th International Symposium on Personal, Indoor and Mobile Radio Communications. IEEE, 2006. http://dx.doi.org/10.1109/pimrc.2006.254439.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Li, Xueru, Emil Bjornson, Shidong Zhou, and Jing Wang. "Massive MIMO with multi-antenna users: When are additional user antennas beneficial?" In 2016 23rd International Conference on Telecommunications (ICT). IEEE, 2016. http://dx.doi.org/10.1109/ict.2016.7500452.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Mai, Trang C., Hien Quoc Ngo, and Trung Q. Duong. "CELL-FREE MASSIVE MIMO SYSTEMS WITH MULTI-ANTENNA USERS." In 2018 IEEE Global Conference on Signal and Information Processing (GlobalSIP). IEEE, 2018. http://dx.doi.org/10.1109/globalsip.2018.8646330.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Flordelis, Jose, Xiang Gao, Ghassan Dahman, Fredrik Rusek, Ove Edfors, and Fredrik Tufvesson. "Spatial separation of closely-spaced users in measured massive multi-user MIMO channels." In 2015 IEEE International Conference on Signal Processing for Communications (ICC). IEEE, 2015. http://dx.doi.org/10.1109/icc.2015.7248526.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Jie Liu and Qiang Gao. "User pairing and resource allocation for multi-antenna users in uplink multiuser MIMO system." In 2015 10th International Conference on Communications and Networking in China (ChinaCom). IEEE, 2015. http://dx.doi.org/10.1109/chinacom.2015.7497940.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Dovelos, Konstantinos, Michail Matthaiou, Hien Quoc Ngo, and Boris Bellalta. "Massive MIMO with Multi-Antenna Users under Jointly Correlated Ricean Fading." In ICC 2020 - 2020 IEEE International Conference on Communications (ICC). IEEE, 2020. http://dx.doi.org/10.1109/icc40277.2020.9148706.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Taygur, Mehmet Mert, and Thomas F. Eibert. "Investigations on Massive MIMO Performance with Multi-Antenna Users by Ray-Tracing." In 2019 IEEE 30th Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC). IEEE, 2019. http://dx.doi.org/10.1109/pimrc.2019.8904315.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Dandan Fan, Liang Jin, and Jing Wang. "A decorrelation technology based on eigen-beamforming in multi-users MIMO systems." In IET International Conference on Wireless Mobile and Multimedia Networks Proceedings (ICWMMN 2006). IEE, 2006. http://dx.doi.org/10.1049/cp:20061357.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Mai, Trang C., Hien Quoc Ngo, and Trung Q. Duong. "Uplink Spectral Efficiency of Cell-free Massive MIMO with Multi-Antenna Users." In 2019 3rd International Conference on Recent Advances in Signal Processing, Telecommunications & Computing (SigTelCom). IEEE, 2019. http://dx.doi.org/10.1109/sigtelcom.2019.8696221.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Li, Xiran, Fanggang Wang, Zhihao Yang, and Qianhua Li. "Uplink Precoding Design for Coherent Paired Users in Multi-cell MIMO Systems." In 2023 IEEE Globecom Workshops (GC Wkshps). IEEE, 2023. http://dx.doi.org/10.1109/gcwkshps58843.2023.10464920.

Full text
APA, Harvard, Vancouver, ISO, and other styles
You might also be interested in the extended bibliographies on the topic 'MIMO multi users' for particular source types:
Journal articles Dissertations / Theses
We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!

To the bibliography