76 research outputs found
Advanced Quantizer Designs for FDD-Based FD-MIMO Systems Using Uniform Planar Arrays
Massive multiple-input multiple-output (MIMO) systems, which utilize a large
number of antennas at the base station, are expected to enhance network
throughput by enabling improved multiuser MIMO techniques. To deploy many
antennas in reasonable form factors, base stations are expected to employ
antenna arrays in both horizontal and vertical dimensions, which is known as
full-dimension (FD) MIMO. The most popular two-dimensional array is the uniform
planar array (UPA), where antennas are placed in a grid pattern. To exploit the
full benefit of massive MIMO in frequency division duplexing (FDD), the
downlink channel state information (CSI) should be estimated, quantized, and
fed back from the receiver to the transmitter. However, it is difficult to
accurately quantize the channel in a computationally efficient manner due to
the high dimensionality of the massive MIMO channel. In this paper, we develop
both narrowband and wideband CSI quantizers for FD-MIMO taking the properties
of realistic channels and the UPA into consideration. To improve quantization
quality, we focus on not only quantizing dominant radio paths in the channel,
but also combining the quantized beams. We also develop a hierarchical beam
search approach, which scans both vertical and horizontal domains jointly with
moderate computational complexity. Numerical simulations verify that the
performance of the proposed quantizers is better than that of previous CSI
quantization techniques.Comment: 15 pages, 6 figure
Massive MIMO Performance - TDD Versus FDD: What Do Measurements Say?
Downlink beamforming in Massive MIMO either relies on uplink pilot
measurements - exploiting reciprocity and TDD operation, or on the use of a
predetermined grid of beams with user equipments reporting their preferred
beams, mostly in FDD operation. Massive MIMO in its originally conceived form
uses the first strategy, with uplink pilots, whereas there is currently
significant commercial interest in the second, grid-of-beams. It has been
analytically shown that in isotropic scattering (independent Rayleigh fading)
the first approach outperforms the second. Nevertheless there remains
controversy regarding their relative performance in practice. In this
contribution, the performances of these two strategies are compared using
measured channel data at 2.6 GHz.Comment: Submitted to IEEE Transactions on Wireless Communications,
31/Mar/201
Recent Advances in Acquiring Channel State Information in Cellular MIMO Systems
In cellular multi-user multiple input multiple output (MU-MIMO) systems the quality of the available channel state information (CSI) has a large impact on the system performance. Specifically, reliable CSI at the transmitter is required to determine the appropriate modulation and coding scheme, transmit power and the precoder vector, while CSI at the receiver is needed to decode the received data symbols. Therefore, cellular MUMIMO systems employ predefined pilot sequences and configure associated time, frequency, code and power resources to facilitate the acquisition of high quality CSI for data transmission and reception. Although the trade-off between the resources used user data transmission has been known for long, the near-optimal configuration of the vailable system resources for pilot and data transmission is a topic of current research efforts. Indeed, since the fifth generation of cellular systems utilizes heterogeneous networks in which base stations are equipped with a large number of transmit and receive antennas, the appropriate configuration of pilot-data resources becomes a critical design aspect. In this article, we review recent advances in system design approaches that are designed for the acquisition of CSI and discuss some of the recent results that help to dimension the pilot and data resources specifically in cellular MU-MIMO systems
Joint Port Selection Based Channel Acquisition for FDD Cell-Free Massive MIMO
In frequency division duplexing (FDD) cell-free massive MIMO, the acquisition
of the channel state information (CSI) is very challenging because of the large
overhead required for the training and feedback of the downlink channels of
multiple cooperating base stations (BSs). In this paper, for systems with
partial uplink-downlink channel reciprocity, and a general spatial domain
channel model with variations in the average port power and correlation among
port coefficients, we propose a joint-port-selection-based CSI acquisition and
feedback scheme for the downlink transmission with zero-forcing precoding. The
scheme uses an eigenvalue-decomposition-based transformation to reduce the
feedback overhead by exploring the port correlation. We derive the sum-rate of
the system for any port selection. Based on the sum-rate result, we propose a
low-complexity greedy-search-based joint port selection (GS-JPS) algorithm.
Moreover, to adapt to fast time-varying scenarios, a supervised deep
learning-enhanced joint port selection (DL-JPS) algorithm is proposed.
Simulations verify the effectiveness of our proposed schemes and their
advantage over existing port-selection channel acquisition schemes.Comment: 30 pages, 9 figures. The paper has been submitted to IEEE journal for
possible publicatio
A survey on hybrid beamforming techniques in 5G : architecture and system model perspectives
The increasing wireless data traffic demands have driven the need to explore suitable spectrum regions for meeting the projected requirements. In the light of this, millimeter wave (mmWave) communication has received considerable attention from the research community. Typically, in fifth generation (5G) wireless networks, mmWave massive multiple-input multiple-output (MIMO) communications is realized by the hybrid transceivers which combine high dimensional analog phase shifters and power amplifiers with lower-dimensional digital signal processing units. This hybrid beamforming design reduces the cost and power consumption which is aligned with an energy-efficient design vision of 5G. In this paper, we track the progress in hybrid beamforming for massive MIMO communications in the context of system models of the hybrid transceivers' structures, the digital and analog beamforming matrices with the possible antenna configuration scenarios and the hybrid beamforming in heterogeneous wireless networks. We extend the scope of the discussion by including resource management issues in hybrid beamforming. We explore the suitability of hybrid beamforming methods, both, existing and proposed till first quarter of 2017, and identify the exciting future challenges in this domain
Digital and Mixed Domain Hardware Reduction Algorithms and Implementations for Massive MIMO
Emerging 5G and 6G based wireless communications systems largely rely on multiple-input-multiple-output (MIMO) systems to reduce inherently extensive path losses, facilitate high data rates, and high spatial diversity. Massive MIMO systems used in mmWave and sub-THz applications consists of hundreds perhaps thousands of antenna elements at base stations. Digital beamforming techniques provide the highest flexibility and better degrees of freedom for phased antenna arrays as compared to its analog and hybrid alternatives but has the highest hardware complexity.
Conventional digital beamformers at the receiver require a dedicated analog to digital converter (ADC) for every antenna element, leading to ADCs for elements. The number of ADCs is the key deterministic factor for the power consumption of an antenna array system. The digital hardware consists of fast Fourier transform (FFT) cores with a multiplier complexity of (N log2N) for an element system to generate multiple beams. It is required to reduce the mixed and digital hardware complexities in MIMO systems to reduce the cost and the power consumption, while maintaining high performance.
The well-known concept has been in use for ADCs to achieve reduced complexities. An extension of the architecture to multi-dimensional domain is explored in this dissertation to implement a single port ADC to replace ADCs in an element system, using the correlation of received signals in the spatial domain. This concept has applications in conventional uniform linear arrays (ULAs) as well as in focal plane array (FPA) receivers.
Our analysis has shown that sparsity in the spatio-temporal frequency domain can be exploited to reduce the number of ADCs from N to where . By using the limited field of view of practical antennas, multiple sub-arrays are combined without interferences to achieve a factor of K increment in the information carrying capacity of the ADC systems. Applications of this concept include ULAs and rectangular array systems. Experimental verifications were done for a element, 1.8 - 2.1 GHz wideband array system to sample using ADCs.
This dissertation proposes that frequency division multiplexing (FDM) receiver outputs at an intermediate frequency (IF) can pack multiple (M) narrowband channels with a guard band to avoid interferences. The combined output is then sampled using a single wideband ADC and baseband channels are retrieved in the digital domain. Measurement results were obtained by employing a element, 28 GHz antenna array system to combine channels together to achieve a 75% reduction of ADC requirement.
Implementation of FFT cores in the digital domain is not always exact because of the finite precision. Therefore, this dissertation explores the possibility of approximating the discrete Fourier transform (DFT) matrix to achieve reduced hardware complexities at an allowable cost of accuracy. A point approximate DFT (ADFT) core was implemented on digital hardware using radix-32 to achieve savings in cost, size, weight and power (C-SWaP) and synthesized for ASIC at 45-nm technology
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