45 research outputs found
Quantized Multimode Precoding in Spatially Correlated Multi-Antenna Channels
Multimode precoding, where the number of independent data-streams is adapted
optimally, can be used to maximize the achievable throughput in multi-antenna
communication systems. Motivated by standardization efforts embraced by the
industry, the focus of this work is on systematic precoder design with
realistic assumptions on the spatial correlation, channel state information
(CSI) at the transmitter and the receiver, and implementation complexity. For
spatial correlation of the channel matrix, we assume a general channel model,
based on physical principles, that has been verified by many recent measurement
campaigns. We also assume a coherent receiver and knowledge of the spatial
statistics at the transmitter along with the presence of an ideal, low-rate
feedback link from the receiver to the transmitter. The reverse link is used
for codebook-index feedback and the goal of this work is to construct precoder
codebooks, adaptable in response to the statistical information, such that the
achievable throughput is significantly enhanced over that of a fixed,
non-adaptive, i.i.d. codebook design. We illustrate how a codebook of
semiunitary precoder matrices localized around some fixed center on the
Grassmann manifold can be skewed in response to the spatial correlation via
low-complexity maps that can rotate and scale submanifolds on the Grassmann
manifold. The skewed codebook in combination with a lowcomplexity statistical
power allocation scheme is then shown to bridge the gap in performance between
a perfect CSI benchmark and an i.i.d. codebook design.Comment: 30 pages, 4 figures, Preprint to be submitted to IEEE Transactions on
Signal Processin
Receive Combining vs. Multi-Stream Multiplexing in Downlink Systems with Multi-Antenna Users
In downlink multi-antenna systems with many users, the multiplexing gain is
strictly limited by the number of transmit antennas and the use of these
antennas. Assuming that the total number of receive antennas at the
multi-antenna users is much larger than , the maximal multiplexing gain can
be achieved with many different transmission/reception strategies. For example,
the excess number of receive antennas can be utilized to schedule users with
effective channels that are near-orthogonal, for multi-stream multiplexing to
users with well-conditioned channels, and/or to enable interference-aware
receive combining. In this paper, we try to answer the question if the data
streams should be divided among few users (many streams per user) or many users
(few streams per user, enabling receive combining). Analytic results are
derived to show how user selection, spatial correlation, heterogeneous user
conditions, and imperfect channel acquisition (quantization or estimation
errors) affect the performance when sending the maximal number of streams or
one stream per scheduled user---the two extremes in data stream allocation.
While contradicting observations on this topic have been reported in prior
works, we show that selecting many users and allocating one stream per user
(i.e., exploiting receive combining) is the best candidate under realistic
conditions. This is explained by the provably stronger resilience towards
spatial correlation and the larger benefit from multi-user diversity. This
fundamental result has positive implications for the design of downlink systems
as it reduces the hardware requirements at the user devices and simplifies the
throughput optimization.Comment: Published in IEEE Transactions on Signal Processing, 16 pages, 11
figures. The results can be reproduced using the following Matlab code:
https://github.com/emilbjornson/one-or-multiple-stream
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
Hybrid MIMO Architectures for Millimeter Wave Communications: Phase Shifters or Switches?
Hybrid analog/digital MIMO architectures were recently proposed as an
alternative for fully-digitalprecoding in millimeter wave (mmWave) wireless
communication systems. This is motivated by the possible reduction in the
number of RF chains and analog-to-digital converters. In these architectures,
the analog processing network is usually based on variable phase shifters. In
this paper, we propose hybrid architectures based on switching networks to
reduce the complexity and the power consumption of the structures based on
phase shifters. We define a power consumption model and use it to evaluate the
energy efficiency of both structures. To estimate the complete MIMO channel, we
propose an open loop compressive channel estimation technique which is
independent of the hardware used in the analog processing stage. We analyze the
performance of the new estimation algorithm for hybrid architectures based on
phase shifters and switches. Using the estimated, we develop two algorithms for
the design of the hybrid combiner based on switches and analyze the achieved
spectral efficiency. Finally, we study the trade-offs between power
consumption, hardware complexity, and spectral efficiency for hybrid
architectures based on phase shifting networks and switching networks.
Numerical results show that architectures based on switches obtain equal or
better channel estimation performance to that obtained using phase shifters,
while reducing hardware complexity and power consumption. For equal power
consumption, all the hybrid architectures provide similar spectral
efficiencies.Comment: Submitted to IEEE Acces