54 research outputs found
Channel Estimation for mmWave Massive MIMO Based Access and Backhaul in Ultra-Dense Network
Millimeter-wave (mmWave) massive MIMO used for access and backhaul in
ultra-dense network (UDN) has been considered as the promising 5G technique. We
consider such an heterogeneous network (HetNet) that ultra-dense small base
stations (BSs) exploit mmWave massive MIMO for access and backhaul, while
macrocell BS provides the control service with low frequency band. However, the
channel estimation for mmWave massive MIMO can be challenging, since the pilot
overhead to acquire the channels associated with a large number of antennas in
mmWave massive MIMO can be prohibitively high. This paper proposes a structured
compressive sensing (SCS)-based channel estimation scheme, where the angular
sparsity of mmWave channels is exploited to reduce the required pilot overhead.
Specifically, since the path loss for non-line-of-sight paths is much larger
than that for line-of-sight paths, the mmWave massive channels in the angular
domain appear the obvious sparsity. By exploiting such sparsity, the required
pilot overhead only depends on the small number of dominated multipath.
Moreover, the sparsity within the system bandwidth is almost unchanged, which
can be exploited for the further improved performance. Simulation results
demonstrate that the proposed scheme outperforms its counterpart, and it can
approach the performance bound.Comment: 6 pages, 5 figures. Millimeter-wave (mmWave), mmWave massive MIMO,
compressive sensing (CS), hybrid precoding, channel estimation, access,
backhaul, ultra-dense network (UDN), heterogeneous network (HetNet). arXiv
admin note: substantial text overlap with arXiv:1604.03695, IEEE
International Conference on Communications (ICC'16), May 2016, Kuala Lumpur,
Malaysi
Millimeter Wave Systems for Wireless Cellular Communications
This thesis considers channel estimation and multiuser (MU) data transmission
for massive MIMO systems with fully digital/hybrid structures in mmWave
channels. It contains three main contributions. In this thesis, we first
propose a tone-based linear search algorithm to facilitate the estimation of
angle-of-arrivals of the strongest components as well as scattering components
of the users at the base station (BS) with fully digital structure. Our results
show that the proposed maximum-ratio transmission (MRT) based on the strongest
components can achieve a higher data rate than that of the conventional MRT,
under the same mean squared errors (MSE). Second, we develop a low-complexity
channel estimation and beamformer/precoder design scheme for hybrid mmWave
systems. In addition, the proposed scheme applies to both non-sparse and sparse
mmWave channel environments. We then leverage the proposed scheme to
investigate the downlink achievable rate performance. The results show that the
proposed scheme obtains a considerable achievable rate of fully digital
systems. Taking into account the effect of various types of errors, we
investigate the achievable rate performance degradation of the considered
scheme. Third, we extend our proposed scheme to a multi-cell MU mmWave MIMO
network. We derive the closed-form approximation of the normalized MSE of
channel estimation under pilot contamination over Rician fading channels.
Furthermore, we derive a tight closed-form approximation and the scaling law of
the average achievable rate. Our results unveil that channel estimation errors,
the intra-cell interference, and the inter-cell interference caused by pilot
contamination over Rician fading channels can be efficiently mitigated by
simply increasing the number of antennas equipped at the desired BS.Comment: Thesi
FDD Channel Estimation Via Covariance Estimation in Wideband Massive MIMO Systems
[Abstract] A method for channel estimation in wideband massive Multiple-Input Multiple-Output systems using hybrid digital analog architectures is developed. The proposed method is useful for Frequency-Division Duplex at either sub-6 GHz or millimeter wave frequency bands and takes into account the beam squint effect caused by the large bandwidth of the signals. To circumvent the estimation of large channel vectors, the posed algorithm relies on the slow time variation of the channel spatial covariance matrix, thus allowing for the utilization of very short training sequences. This is possibledue to the exploitation of the channel structure. After identifying the channel covariance matrix, the channel is estimated on the basis of the recovered information. To that end, we propose a novel method that relies on estimating the tap delays and the gains as sociated with each path. As a consequence, the proposed channel estimator achieves low computational complexity and significantly reduces the training overhead. Moreover, our numerical simulations show better performance results compared to the minimum mean-squared error solution.Xunta de Galicia; ED431G2019/01Agencia Estatal de Investigación de España; TEC2016-75067-C4-1-RAgencia Estatal de Investigación de España; RED2018-102668-TAgencia Estatal de Investigación de España; PID2019-104958RB-C4
RIS-Aided Cell-Free Massive MIMO Systems for 6G: Fundamentals, System Design, and Applications
An introduction of intelligent interconnectivity for people and things has
posed higher demands and more challenges for sixth-generation (6G) networks,
such as high spectral efficiency and energy efficiency, ultra-low latency, and
ultra-high reliability. Cell-free (CF) massive multiple-input multiple-output
(mMIMO) and reconfigurable intelligent surface (RIS), also called intelligent
reflecting surface (IRS), are two promising technologies for coping with these
unprecedented demands. Given their distinct capabilities, integrating the two
technologies to further enhance wireless network performances has received
great research and development attention. In this paper, we provide a
comprehensive survey of research on RIS-aided CF mMIMO wireless communication
systems. We first introduce system models focusing on system architecture and
application scenarios, channel models, and communication protocols.
Subsequently, we summarize the relevant studies on system operation and
resource allocation, providing in-depth analyses and discussions. Following
this, we present practical challenges faced by RIS-aided CF mMIMO systems,
particularly those introduced by RIS, such as hardware impairments and
electromagnetic interference. We summarize corresponding analyses and solutions
to further facilitate the implementation of RIS-aided CF mMIMO systems.
Furthermore, we explore an interplay between RIS-aided CF mMIMO and other
emerging 6G technologies, such as next-generation multiple-access (NGMA),
simultaneous wireless information and power transfer (SWIPT), and millimeter
wave (mmWave). Finally, we outline several research directions for future
RIS-aided CF mMIMO systems.Comment: 30 pages, 15 figure
Physical Layer Techniques for Massive MIMO Sub-6 GHz LoS and Millimetre-Wave Transmission
The explosive growth in data demand requires solutions with higher system throughput, lower energy consumption, and simultaneous support for many users. Massive multiple-input multiple-output (MIMO) and millimetre-wave (mmWave) techniques are promising candidates for next-generation wireless systems.
This thesis focuses on sub-6 GHz line-of-sight (LoS) transmissions in massive MIMO systems, which not only fulfil a variety of applications, such as small-cell back-haul but also provide a longer coherent time as the LoS channel varies more slowly and can be readily estimated compared with fading channels. This thesis also focuses on mmWave transmissions in massive MIMO systems since a large-scale antenna array can compensate for the strong pathloss of mmWave transmissions whilst the mmWave carrier frequencies enable compact BS configurations.
In this thesis, the fundamentals of the massive MIMO technique are studied comprehensively through theoretical analysis and simulations. The representative sub-6 GHz channel models of LoS and fading channels are considered. The characteristics of the LoS channel and the system performance of LoS transmissions are investigated and compared with fading channels along with the key factors that impact performance. The effective SINR expressions of the linear precoding schemes for LoS transmissions are presented. It is illustrated that the system performance of massive MIMO LoS transmissions is robust when the angles of departure are distributed within a wide range and the power of the LoS channel component is high.
The mmWave channel model and technical challenges are studied. The mmWave massive MIMO precoding problem is transformed into a beam-selecting problem. A novel channel deconstruction algorithm is proposed that enables the estimation of each received paths’ parameters from the perfect or Gaussian-perturbed channel state information. Utilising the estimated path parameters, new analogue and hybrid beam-selecting (ABS and HBS) linear precoding schemes are proposed that contribute substantially to system performance. The corresponding hardware architectures for the proposed schemes are demonstrated, which exploit low-complexity and low-cost signal processing with high energy efficiency. An enhanced hybrid beam-selecting precoding (E-HBS) scheme and hardware configuration are further proposed to achieve the optimal and near-optimal performance of digital baseband signal processing with low cost and high energy efficiency in massive MIMO systems. With E-HBS, the number of RF chains and the dimension of the baseband digital control is independent of the number of base station antennas, which is vital for massive MIMO systems.
Novel spatial user scheduling (SUS) schemes for sub-6 GHz LoS massive MIMO transmissions are proposed along with a capacity-enhancement check (CEC) scheme to further improve the system performance by mitigating the LoS channel cross-correlation
Limited Feedback Techniques in Multiple Antenna Wireless Communication Systems
Multiple antenna systems provide spatial multiplexing and diversity benefits.These systems also offer beamforming and interference mitigation capabilities in single-user (SU) and multi-user (MU) scenarios, respectively. Although diversity can be achieved without channel state information (CSI) at the transmitter using space-time codes, the knowledge of instantaneous CSI at the transmitter is essential to the above mentioned gains. In frequency division duplexing (FDD) systems, limited feedback techniques are employed to obtain CSI at the transmitter from the receiver using a low-rate link. As a consequence, CSI acquired by the transmitter in such manner have errors due to channel estimation and codebook quantization at the receiver, resulting in performance degradation of multi-antenna systems. In this thesis, we examine CSI inaccuracies due to codebook quantization errors and investigate several other aspects of limited feedback in SU, MU and multicell wireless communication systems with various channel models.
For SU multiple-input multiple-output (MIMO) systems, we examine the capacity loss using standard codebooks. In particular, we consider single-stream and two-stream MIMO transmissions and derive capacity loss expressions in terms of minimum squared chordal distance for various MIMO receivers. Through simulations, we investigate the impact of codebook quantization errors on the capacity performance in uncorrelated Rayleigh, spatially correlated Rayleigh and standardized MIMO channels. This work motivates the need of effective codebook design to reduce the codebook quantization errors in correlated channels.
Subsequently, we explore the improvements in the design of codebooks in temporally and spatially correlated channels for MU multiple-input single-output (MISO) systems, by employing scaling and rotation techniques. These codebooks quantize instantaneous channel direction information (CDI) and are referred as differential codebooks in the thesis. We also propose various adaptive scaling techniques for differential codebooks where packing density of codewords in the differential codebook are altered according to the channel condition, in order to reduce the quantization errors. The proposed differential codebooks improve the spectral efficiency of the system by minimizing the codebook quantization errors in spatially and temporally correlated channels.
Later, we broaden the scope to massive MISO systems and propose trellis coded quantization (TCQ) schemes to quantize CDI. Unlike conventional codebook approach, the TCQ scheme does not require exhaustive search to select an appropriate codeword, thus reducing computational complexity and memory requirement at the receiver. The proposed TCQ schemes yield significant performance improvements compared to the existing TCQ based limited feedback schemes in both temporally and spatially correlated channels.
Finally, we investigate interference coordination for multicell MU MISO systems using regularized zero-forcing (RZF) precoding. We consider random vector quantization (RVQ) codebooks and uncorrelated Rayleigh channels. We derive expected SINR approximations for perfect CDI and RVQ codebook-based CDI. We also propose an adaptive bit allocation scheme which aims to minimize the network interference and moreover, improves the spectral efficiency compared to equal bit allocation and coordinated zero-forcing (ZF) based adaptive bit allocation schemes
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