170 research outputs found
AirSync: Enabling Distributed Multiuser MIMO with Full Spatial Multiplexing
The enormous success of advanced wireless devices is pushing the demand for
higher wireless data rates. Denser spectrum reuse through the deployment of
more access points per square mile has the potential to successfully meet the
increasing demand for more bandwidth. In theory, the best approach to density
increase is via distributed multiuser MIMO, where several access points are
connected to a central server and operate as a large distributed multi-antenna
access point, ensuring that all transmitted signal power serves the purpose of
data transmission, rather than creating "interference." In practice, while
enterprise networks offer a natural setup in which distributed MIMO might be
possible, there are serious implementation difficulties, the primary one being
the need to eliminate phase and timing offsets between the jointly coordinated
access points.
In this paper we propose AirSync, a novel scheme which provides not only time
but also phase synchronization, thus enabling distributed MIMO with full
spatial multiplexing gains. AirSync locks the phase of all access points using
a common reference broadcasted over the air in conjunction with a Kalman filter
which closely tracks the phase drift. We have implemented AirSync as a digital
circuit in the FPGA of the WARP radio platform. Our experimental testbed,
comprised of two access points and two clients, shows that AirSync is able to
achieve phase synchronization within a few degrees, and allows the system to
nearly achieve the theoretical optimal multiplexing gain. We also discuss MAC
and higher layer aspects of a practical deployment. To the best of our
knowledge, AirSync offers the first ever realization of the full multiuser MIMO
gain, namely the ability to increase the number of wireless clients linearly
with the number of jointly coordinated access points, without reducing the per
client rate.Comment: Submitted to Transactions on Networkin
Dexterity for Channel Capacity Enhancement in MU-MIMO by Abrogating Interference
The looming field of Multi user Multiple-input Multiple-output (MU-MIMO) communication system has faced a challenge with precoding techniques for achieving increased channel capacity of their less inhaling of signals, imperfect knowing of channel state information, loss of signals by noise ,time complexity etc. in downlink systems which results in interference to the users. Hence straight forwarding from the issues, the paper newly introduce2LB-FR precoding technique which holds Linde-Lyold’s (LL)algorithm to increase data transmission by consuming large amount of signals with space and the Bernoulli distribution with Bayes decision (BB) to allot the perfect channel state; l information during transmission that eliminates co-interference. Holding Floyd Rasta (FR) algorithm expels the noise if added and takes the shortest required path by acquiring all the possible routes available in single execution which decreases delay. By the overall implementation, the proposed work pomped that in short time ,the capacity of the channel get enhanced with interference cancellation
Hardware Precoding Demonstration in Multi-Beam UHTS Communications under Realistic Payload Characteristics
In this paper, we present a new hardware test-bed to demonstrate closed-loop precoded communications for interference mitigation in multi-beam ultra high throughput satellite systems under realistic payload and channel impairments. We build the test-bed to demonstrate a real-time channel aided precoded transmission under realistic conditions such as the power constraints and satellite-payload non-linearities. We develop a scalable architecture of an SDR platform with the DVB-S2X piloting. The SDR platform consists of two parts: analog-to-digital (ADC) and digital-to-analog (DAC) converters preceded by radio frequency (RF) front-end and Field-Programmable Gate Array (FPGA) backend. The former introduces realistic impairments in the transmission chain such as carrier frequency and phase misalignments, quantization noise of multichannel ADC and DAC and non-linearities of RF components. It allows evaluating the performance of the precoded transmission in a more realistic environment rather than using only numerical simulations. We benchmark the performance of the communication standard in realistic channel scenarios, evaluate received signal
SNR, and measure the actual channel throughput using LDPC codes
A Practical Cooperative Multicell MIMO-OFDMA Network Based on Rank Coordination
An important challenge of wireless networks is to boost the cell edge
performance and enable multi-stream transmissions to cell edge users.
Interference mitigation techniques relying on multiple antennas and
coordination among cells are nowadays heavily studied in the literature.
Typical strategies in OFDMA networks include coordinated scheduling,
beamforming and power control. In this paper, we propose a novel and practical
type of coordination for OFDMA downlink networks relying on multiple antennas
at the transmitter and the receiver. The transmission ranks, i.e.\ the number
of transmitted streams, and the user scheduling in all cells are jointly
optimized in order to maximize a network utility function accounting for
fairness among users. A distributed coordinated scheduler motivated by an
interference pricing mechanism and relying on a master-slave architecture is
introduced. The proposed scheme is operated based on the user report of a
recommended rank for the interfering cells accounting for the receiver
interference suppression capability. It incurs a very low feedback and backhaul
overhead and enables efficient link adaptation. It is moreover robust to
channel measurement errors and applicable to both open-loop and closed-loop
MIMO operations. A 20% cell edge performance gain over uncoordinated LTE-A
system is shown through system level simulations.Comment: IEEE Transactions or Wireless Communications, Accepted for
Publicatio
Sum-Rate Maximization for Linearly Precoded Downlink Multiuser MISO Systems with Partial CSIT: A Rate-Splitting Approach
This paper considers the Sum-Rate (SR) maximization problem in downlink
MU-MISO systems under imperfect Channel State Information at the Transmitter
(CSIT). Contrary to existing works, we consider a rather unorthodox
transmission scheme. In particular, the message intended to one of the users is
split into two parts: a common part which can be recovered by all users, and a
private part recovered by the corresponding user. On the other hand, the rest
of users receive their information through private messages. This
Rate-Splitting (RS) approach was shown to boost the achievable Degrees of
Freedom (DoF) when CSIT errors decay with increased SNR. In this work, the RS
strategy is married with linear precoder design and optimization techniques to
achieve a maximized Ergodic SR (ESR) performance over the entire range of SNRs.
Precoders are designed based on partial CSIT knowledge by solving a stochastic
rate optimization problem using means of Sample Average Approximation (SAA)
coupled with the Weighted Minimum Mean Square Error (WMMSE) approach. Numerical
results show that in addition to the ESR gains, the benefits of RS also include
relaxed CSIT quality requirements and enhanced achievable rate regions compared
to conventional transmission with NoRS.Comment: accepted to IEEE Transactions on Communication
Modeling and Compensation of Transceiver Non-Reciprocity in TDD Multi-Antenna Base-Station
Due to the increasing demands for higher system capacity, higher data rates and better quality of service in wireless networks, advanced techniques that improve wireless link reliability and spectral efficiency are introduced. This includes different multi-antenna technologies, in particular multi-user (MU) MIMO-OFDM. In MU MIMO-OFDM systems, base-station with multiple antennas communicates simultaneously with multiple users over a given time-frequency resource. In downlink transmission, base-station transmits multiple data streams through its antennas towards the user devices. In uplink transmission, the user equipment send in parallel multiple data streams towards the base-station. In general, channel non-reciprocity is a very important factor in cellular communications, in particular in precoded MU MIMO-OFDM systems adopting time division duplexing (TDD). Based on the channel reciprocity principle, the channel state information at base-station for the downlink transmission can be determined through estimating the uplink channels. In practice, however, there are always unavoidable frequency mismatch characteristics between transmitter and receiver. Frequency response mismatch can thus change the reciprocal nature of downlink and uplink channels. The impact of transceiver non-reciprocity at equipment on user side causes inter-stream interference which can be compensated using detection processing. The impact of transceiver non-reciprocity at base-station causes inter-user interference and degrades the system performance of MU MIMO-OFDM systems.
To ensure the system reliability and high performance in case of transceiver non-reciprocity, some non-reciprocity estimation and compensation methods are required. The previous work has proposed the estimation-compensation framework that gives a flexible solution to restore the channel reciprocity. But there is a need to validate the findings and performance of the proposed estimation-compensation framework. The modeling of transceiver frequency response mismatch characteristics using actual measurement data has been carried out in this thesis research work. The actual measurement data comprises of one base-station with two antennas and two user equipment devices with single antenna. The estimated uplink and downlink channels from measurement data are used to compute the non-reciprocity matrix at base-station and at the equipment on user side after mathematical calculations. The normalized parameters for transceiver non-reciprocity matrices are extracted subcarrier-wise. The frequency-domain normalized non-reciprocity parameters are modeled as a FIR filter in the time-domain and the most energy concentrates then on few time-domain taps. The extracted parameters are mildly frequency-selective. The impact of extracted transceiver non-reciprocity is then analyzed by implementing a simulator of TDD precoded MU MIMO-OFDM system.
In general, the frequency-selectivity implies that the reciprocity estimation and compensation is needed subcarrier-wise. The pilot-based estimation of non-reciprocity parameters at base-station is carried out in order to enhance the system performance. To estimate channel non-reciprocity parameters, a link between base-station and one of user equipment devices is assumed. The right choice of selecting the user is also important for noise reduction in estimation. For estimation, the DL transmission channel is modeled as a Rayleigh fading multipath channel with a given 7-tap channel power delay profile. The downlink data including sparsely located pilots at selected subcarriers is transmitted to the user through downlink channel without precoding. The downlink channel is then estimated at the user equipment side. This provides estimates only at the pilot subcarriers. Therefore, linear interpolation is used to obtain channel response estimates at the actual data subcarriers. The uplink pilot data is transmitted to base-station from user equipment through uplink channel. The uplink channel is obtained by estimated downlink channel in case of non-reciprocity parameters. Then, estimate of non-reciprocity at base-station is computed by using inverse processing and an interpolator. The estimated parameters are used as a compensator filter in order to compensate the channel non-reciprocity in the system.
The simulated results show that the performance deviates from the ideal linear precoded MU MIMO-OFDM system because of non-reciprocity in case of both error control coded and uncoded channels. The compensated results in terms of coded and uncoded channel schemes have been evaluated which are closer to ideal linear precoded MU-MIMO OFDM system. These results show that the impact of non-reciprocity on system performance is less severe when a coded channel is deployed as compared to uncoded channel. The modeling of transceiver frequency response mismatch characteristics using actual measurement data proves that the proposed non-reciprocity model in the previous research work is close to reality
Linear Transmit-Receive Strategies for Multi-user MIMO Wireless Communications
Die Notwendigkeit zur Unterdrueckung von Interferenzen auf der einen Seite
und zur Ausnutzung der durch Mehrfachzugriffsverfahren erzielbaren Gewinne
auf der anderen Seite rueckte die raeumlichen Mehrfachzugriffsverfahren
(Space Division Multiple Access, SDMA) in den Fokus der Forschung. Ein
Vertreter der raeumlichen Mehrfachzugriffsverfahren, die lineare
Vorkodierung, fand aufgrund steigender Anzahl an Nutzern und Antennen in
heutigen und zukuenftigen Mobilkommunikationssystemen besondere Beachtung,
da diese Verfahren das Design von Algorithmen zur Vorcodierung
vereinfachen. Aus diesem Grund leistet diese Dissertation einen Beitrag zur
Entwicklung linearer Sende- und Empfangstechniken fuer MIMO-Technologie mit
mehreren Nutzern. Zunaechst stellen wir ein Framework zur Approximation des
Datendurchsatzes in Broadcast-MIMO-Kanaelen mit mehreren Nutzern vor. In
diesem Framework nehmen wir das lineare Vorkodierverfahren regularisierte
Blockdiagonalisierung (RBD) an. Durch den Vergleich von Dirty Paper Coding
(DPC) und linearen Vorkodieralgorithmen (z.B. Zero Forcing (ZF) und
Blockdiagonalisierung (BD)) ist es uns moeglich, untere und obere Schranken
fuer den Unterschied bezueglich Datenraten und bezueglich Leistung zwischen
beiden anzugeben. Im Weiteren entwickeln wir einen Algorithmus fuer
koordiniertes Beamforming (Coordinated Beamforming, CBF), dessen Loesung
sich in geschlossener Form angeben laesst. Dieser CBF-Algorithmus basiert
auf der SeDJoCo-Transformation und loest bisher vorhandene Probleme im
Bereich CBF. Im Anschluss schlagen wir einen iterativen CBF-Algorithmus
namens FlexCoBF (flexible coordinated beamforming) fuer
MIMO-Broadcast-Kanaele mit mehreren Nutzern vor. Im Vergleich mit bis dato
existierenden iterativen CBF-Algorithmen kann als vielversprechendster
Vorteil die freie Wahl der linearen Sende- und Empfangsstrategie
herausgestellt werden. Das heisst, jede existierende Methode der linearen
Vorkodierung kann als Sendestrategie genutzt werden, waehrend die Strategie
zum Empfangsbeamforming frei aus MRC oder MMSE gewaehlt werden darf. Im
Hinblick auf Szenarien, in denen Mobilfunkzellen in Clustern
zusammengefasst sind, erweitern wir FlexCoBF noch weiter. Hier wurde das
Konzept der koordinierten Mehrpunktverbindung (Coordinated Multipoint
(CoMP) transmission) integriert. Zuletzt stellen wir drei Moeglichkeiten
vor, Kanalzustandsinformationen (Channel State Information, CSI) unter
verschiedenen Kanalumstaenden zu erlangen. Die Qualitaet der
Kanalzustandsinformationen hat einen starken Einfluss auf die Guete des
Uebertragungssystems. Die durch unsere neuen Algorithmen erzielten
Verbesserungen haben wir mittels numerischer Simulationen von Summenraten
und Bitfehlerraten belegt.In order to combat interference and exploit large multiplexing gains of the
multi-antenna systems, a particular interest in spatial division multiple
access (SDMA) techniques has emerged. Linear precoding techniques, as one
of the SDMA strategies, have obtained more attention due to the fact that
an increasing number of users and antennas involved into the existing and
future mobile communication systems requires a simplification of the
precoding design. Therefore, this thesis contributes to the design of
linear transmit and receive strategies for multi-user MIMO broadcast
channels in a single cell and clustered multiple cells. First, we present a
throughput approximation framework for multi-user MIMO broadcast channels
employing regularized block diagonalization (RBD) linear precoding.
Comparing dirty paper coding (DPC) and linear precoding algorithms (e.g.,
zero forcing (ZF) and block diagonalization (BD)), we further quantify
lower and upper bounds of the rate and power offset between them as a
function of the system parameters such as the number of users and antennas.
Next, we develop a novel closed-form coordinated beamforming (CBF)
algorithm (i.e., SeDJoCo based closed-form CBF) to solve the existing open
problem of CBF. Our new algorithm can support a MIMO system with an
arbitrary number of users and transmit antennas. Moreover, the application
of our new algorithm is not only for CBF, but also for blind source
separation (BSS), since the same mathematical model has been used in BSS
application.Then, we further propose a new iterative CBF algorithm (i.e.,
flexible coordinated beamforming (FlexCoBF)) for multi-user MIMO broadcast
channels. Compared to the existing iterative CBF algorithms, the most
promising advantage of our new algorithm is that it provides freedom in the
choice of the linear transmit and receive beamforming strategies, i.e., any
existing linear precoding method can be chosen as the transmit strategy and
the receive beamforming strategy can be flexibly chosen from MRC or MMSE
receivers. Considering clustered multiple cell scenarios, we extend the
FlexCoBF algorithm further and introduce the concept of the coordinated
multipoint (CoMP) transmission. Finally, we present three strategies for
channel state information (CSI) acquisition regarding various channel
conditions and channel estimation strategies. The CSI knowledge is required
at the base station in order to implement SDMA techniques. The quality of
the obtained CSI heavily affects the system performance. The performance
enhancement achieved by our new strategies has been demonstrated by
numerical simulation results in terms of the system sum rate and the bit
error rate
Asymptotic Behavior of Zero-Forcing Precoding based on Imperfect Channel Knowledge for Massive MISO FDD Systems
In this work, we study the asymptotic behavior of the zero-forcing precoder
based on the least squares (LS) and the linear minimum mean-square error
(LMMSE) channel estimates for the downlink (DL) of a frequency-division-duplex
(FDD) massive multiple-input-single-output (MISO) system. We show analytically
the rather surprising result that zero-forcing precoding based on the LS
estimate leads asymptotically to an interference-free transmission, even if the
number of pilots used for DL channel training is less than the number of
antennas available at the base station (BS). Although the LMMSE channel
estimate exhibits a better quality in terms of the MSE due to the exploitation
of the channel statistics, we show that in the case of contaminated channel
observations, zero-forcing based on the LMMSE is unable to eliminate the
inter-user interference in the asymptotic limit of high DL transmit powers. In
order for the results to hold, mild conditions on the channel probing phase are
assumed. The validity of our analytical results is demonstrated through
numerical simulations for different scenarios
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