133 research outputs found
MmWave Massive MIMO Based Wireless Backhaul for 5G Ultra-Dense Network
Ultra-dense network (UDN) has been considered as a promising candidate for
future 5G network to meet the explosive data demand. To realize UDN, a
reliable, Gigahertz bandwidth, and cost-effective backhaul connecting
ultra-dense small-cell base stations (BSs) and macro-cell BS is prerequisite.
Millimeter-wave (mmWave) can provide the potential Gbps traffic for wireless
backhaul. Moreover, mmWave can be easily integrated with massive MIMO for the
improved link reliability. In this article, we discuss the feasibility of
mmWave massive MIMO based wireless backhaul for 5G UDN, and the benefits and
challenges are also addressed. Especially, we propose a digitally-controlled
phase-shifter network (DPSN) based hybrid precoding/combining scheme for mmWave
massive MIMO, whereby the low-rank property of mmWave massive MIMO channel
matrix is leveraged to reduce the required cost and complexity of transceiver
with a negligible performance loss. One key feature of the proposed scheme is
that the macro-cell BS can simultaneously support multiple small-cell BSs with
multiple streams for each smallcell BS, which is essentially different from
conventional hybrid precoding/combining schemes typically limited to
single-user MIMO with multiple streams or multi-user MIMO with single stream
for each user. Based on the proposed scheme, we further explore the fundamental
issues of developing mmWave massive MIMO for wireless backhaul, and the
associated challenges, insight, and prospect to enable the mmWave massive MIMO
based wireless backhaul for 5G UDN are discussed.Comment: This paper has been accepted by IEEE Wireless Communications
Magazine. This paper is related to 5G, ultra-dense network (UDN), millimeter
waves (mmWave) fronthaul/backhaul, massive MIMO, sparsity/low-rank property
of mmWave massive MIMO channels, sparse channel estimation, compressive
sensing (CS), hybrid digital/analog precoding/combining, and hybrid
beamforming. http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=730653
Deep Reinforcement Learning for Multi-user Massive MIMO with Channel Aging
The design of beamforming for downlink multi-user massive multi-input
multi-output (MIMO) relies on accurate downlink channel state information (CSI)
at the transmitter (CSIT). In fact, it is difficult for the base station (BS)
to obtain perfect CSIT due to user mobility, latency/feedback delay (between
downlink data transmission and CSI acquisition). Hence, robust beamforming
under imperfect CSIT is needed. In this paper, considering multiple antennas at
all nodes (base station and user terminals), we develop a multi-agent deep
reinforcement learning (DRL) framework for massive MIMO under imperfect CSIT,
where the transmit and receive beamforming are jointly designed to maximize the
average information rate of all users. Leveraging this DRL-based framework,
interference management is explored and three DRL-based schemes, namely the
distributed-learning-distributed-processing scheme,
partial-distributed-learning-distributed-processing, and
central-learning-distributed-processing scheme, are proposed and analyzed. This
paper \textrm{1)} highlights the fact that the DRL-based strategies outperform
the random action-chosen strategy and the delay-sensitive strategy named as
sample-and-hold (SAH) approach, and achieved over 90 of the information
rate of two selected benchmarks with lower complexity: the zero-forcing
channel-inversion (ZF-CI) with perfect CSIT and the Greedy Beam Selection
strategy, \textrm{2)} demonstrates the inherent robustness of the proposed
designs in the presence of user mobility.Comment: submitted for publicatio
Cooperative Transmission for Downlink Distributed Antenna in Time Division Duplex System
Multi-user distributed antenna system (MU-DAS) systems play the
essential role in improving throughput performance in wireless communications. This improvement can be achieved by exploiting the spatial
domain and without the need of additional power and bandwidth. In
this thesis, three main issues which are of importance to the data rate
transmission have been investigated.
Firstly, user clustering in MU-DAS downlink systems has been considered, where this technique can be effciently used to reduce the complexity and cost caused by radio frequency chains, associated with antennas while keeping most of the diversity advantages of the system.
The proposed user clustering algorithm which can select an optimal set
of antennas for transmission. The capacity achieved by the proposed
algorithm is almost same as the capacity of the optimum search method,
with much lower complexity.
Secondly, interference alignment in MU-DAS downlink systems has
been studied. The inter-cluster interference is uncoordinated and limits
the system performance. The inter-cluster interference should be eliminated or minimized carefully. The interference alignment is proposed to
consolidate the strong inter-cluster interference into smaller dimensions
of signal space at each user and use the remaining dimensions to transmit
the desired signals without any interference. The performance of single
cluster is better than the proposed algorithm due to the absence of intercluster interference in the single cluster. The numerical shows that the
proposed algorithm is more suitable in multi-cell DAS environment due
to the presence of inter-cell interference.
Finally, the impact of different user mobility on TDD downlink MUDAS has been studied. The downlink data transmission in time division
duplex (TDD) systems is optimized according to the channel state information (CSI) which is obtained at the uplink time slot. However, the
actual channel at downlink time slot may be different from the estimated
channel due to channel variation in mobility environment. Based on mobility state information (MSI), an autocorrelation based feedback interval
adjustment technique is proposed. The proposed technique adjusts the
CSI update interval and mitigates the performance degradation imposed
by the user mobility and the transmission delay. Cooperative clusters are
formed to maximize sum rate. In order to reduce the computational complexity, a channel gain based antenna selection and signal-to-interference
plus noise ratio (SINR) based user clustering are developed. A downlink
ergodic capacity is derived in single user clustering. The derived analytical expressions of the downlink ergodic capacity are verified by system
simulations. Numerical results show that the proposed scheme can improved sum rate over the non cooperative system and no MSI knowledge.
The proposed technique has good performance for a wide range of user
speed and suitable for future wireless communications systems
Multiuser MIMO techniques with feedback
Kooperative Antennenanlagen haben vor kurzem einen heißen Forschungsthema geworden, da Sie deutlich höhere spektrale Effizienz als herkömmliche zelluläre Systeme versprechen. Der Gewinn wird durch die Eliminierung von Inter-Zelle Störungen (ICI) durch Koordinierung der-Antenne Übertragungen erworben. Vor kurzem, verteilte Organisation Methoden vorgeschlagen. Eine der größten Herausforderungen für das Dezentrale kooperative Antennensystem ist Kanalschätzung für den Downlink Kanal besonders wenn FDD verwendet wird. Alle zugehörigen Basisstationen im genossenschaftlichen Bereich müssen die vollständige Kanal Informationen zu Wissen, die entsprechenden precoding Gewicht Matrix zu berechnen. Diese Information ist von mobilen Stationen übertragen werden Stationen mit Uplink Ressourcen zu stützen. Wird als mehrere Basisstationen und mehreren mobilen Stationen in kooperativen Antennensysteme und jede Basisstation und Mobilstation beteiligt sind, können mit mehreren Antennen ausgestattet sein, die Anzahl der Kanal Parameter wieder gefüttert werden erwartet, groß zu sein. In dieser Arbeit wird ein effizientes Feedback Techniken der downlink Kanal Informationen sind für die Multi-user Multiple Input Multiple Output Fall vorgeschlagen, der insbesondere auf verteilte kooperative Antennensysteme zielt. Zuerst wird ein Unterraum-basiertes Kanalquantisierungsverfahren vorgeschlagen, das ein vorbestimmtes Codebuch verwendet. Ein iterativer Codebuchentwurfsalgorithmus wird vorgeschlagen, der zu einem lokalen optimalen Codebuch konvergiert. Darüber hinaus werden Feedback-Overhead-Reduktionsverfahren entwickelt, die die zeitliche Korrelation des Kanals ausnutzen. Es wird gezeigt, dass das vorgeschlagene adaptive Codebuchverfahren in Verbindung mit einem Datenkomprimierungsschema eine Leistung nahe an dem perfekten Kanalfall erzielt, was viel weniger Rückkopplungsoverhead im Vergleich zu anderen Techniken erfordert. Das auf dem Unterraum basierende Kanalquantisierungsverfahren wird erweitert, indem mehrere Antennen auf der Senderseite und/oder auf der Empfängerseite eingeführt werden, und die Leistung eines Vorcodierungs- (/Decodierungs-) Schemas mit regulierter Blockdiagonalisierung (RBD) wurde untersucht. Es wird ein kosteneffizientes Decodierungsmatrixquantisierungsverfahren vorgeschlagen, dass eine komplexe Berechnung an der Mobilstation vermeiden kann, während es nur eine leichte Verschlechterung zeigt. Die Arbeit wird abgeschlossen, indem die vorgeschlagenen Feedback-Methoden hinsichtlich ihrer Leistung, ihres erforderlichen Feedback-Overheads und ihrer Rechenkomplexität verglichen werden.Cooperative antenna systems have recently become a hot research topic, as they promise significantly higher spectral efficiency than conventional cellular systems. The gain is acquired by eliminating inter-cell interference (ICI) through coordination of the base antenna transmissions. Recently, distributed organization methods have been suggested. One of the main challenges of the distributed cooperative antenna system is channel estimation for the downlink channel especially when FDD is used. All of the associated base stations in the cooperative area need to know the full channel state information to calculate the corresponding precoding weight matrix. This information has to be transferred from mobile stations to base stations by using uplink resources. As several base stations and several mobile stations are involved in cooperative antenna systems and each base station and mobile station may be equipped with multiple antennas, the number of channel state parameters to be fed back is expected to be big. In this thesis, efficient feedback techniques of the downlink channel state information are proposed for the multi-user multiple-input multiple-output case, targeting distributed cooperative antenna systems in particular. First, a subspace based channel quantization method is proposed which employs a predefined codebook. An iterative codebook design algorithm is proposed which converges to a local optimum codebook. Furthermore, feedback overhead reduction methods are devised exploiting temporal correlation of the channel. It is shown that the proposed adaptive codebook method in conjunction with a data compression scheme achieves a performance close to the perfect channel case, requiring much less feedback overhead compared with other techniques. The subspace based channel quantization method is extended by introducing multiple antennas at the transmitter side and/or at the receiver side and the performance of a regularized block diagonalization (RBD) precoding(/decoding) scheme has been investigated as well as a zero-forcing (ZF) precoding scheme. A cost-efficient decoding matrix quantization method is proposed which can avoid a complex computation at the mobile station while showing only a slight degradation. The thesis is concluded by comparing the proposed feedback methods in terms of their performance, their required feedback overhead, and their computational complexity. The techniques that are developed in this thesis can be useful and applicable for 5G, which is envisioned to support the high granularity/resolution codebook and its efficient deployment schemes. Keywords: MU-MIMO, COOPA, limited feedback, CSI, CQ, feedback overhead reduction, Givens rotatio
D3.2 First performance results for multi -node/multi -antenna transmission technologies
This deliverable describes the current results of the multi-node/multi-antenna technologies
investigated within METIS and analyses the interactions within and outside Work Package 3.
Furthermore, it identifies the most promising technologies based on the current state of
obtained results. This document provides a brief overview of the results in its first part. The second part, namely the Appendix, further details the results, describes the simulation
alignment efforts conducted in the Work Package and the interaction of the Test Cases. The
results described here show that the investigations conducted in Work Package 3
are maturing resulting in valuable innovative solutions for future 5G systems.Fantini. R.; Santos, A.; De Carvalho, E.; Rajatheva, N.; Popovski, P.; Baracca, P.; Aziz, D.... (2014). D3.2 First performance results for multi -node/multi -antenna transmission technologies. http://hdl.handle.net/10251/7675
Uplink MIMO schemes in local area time division duplex system
One of 3rd Generation Partnership Projects's release 9 research areas is deployment and improvement of Long Term Evolutions's Evolved Universal Terrestrial Radio Access interface in local area cells, using time division duplex and 100MHz available bandwidth. For uplink part of this system, we revise and study MIMO algorithms considered in release 8's downlink (Cyclic Delay Diversity and Space-Frequency Block Codes open-loop schemes, Singular Value Decomposition and codebook-based closed-loop schemes), look for new alternatives, and simulate impacts of given scenario - reciprocity, correlated MIMO channels, slow fading etc. As a result, we draw conclusions about advantages of having multiple transmit antennas in User Equipment in contrast with higher price and power consumption
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