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This paper designs efficient feedback mechanisms to help enable massive MIMO in frequency division multiplexing (FDD) bands. By exploiting possible device-to-device (D2D) coordination and using a team decision approach, a scheme is developed to bridge the feedback in the channel space and that in the precoder space. It is found that the desired feedback and precoding vectors take similar forms as...
Consensus-based algorithms are a welcome approach to establish cooperative communication systems. In this work, it has been utilized to present a hardware architecture for distributed data detection in a receiver with several sensor nodes on an easily scalable regular network. Additionally, it is capable to detect the transmitted message even if a single sensor node fails to operate. On top of that,...
In this paper1 we consider the Network MIMO channel under the so-called Distributed Channel State Information at the Transmitters (D-CSIT) configuration where the precoder is designed in a distributed manner at each Transmitter (TX) on the basis of local versions of Channel State information (CSI) of various quality. In that setting, a novel transmission scheme has been developed in [1] and surprisingly...
A new signaling concept, known as unique word — orthogonal frequency division multiplexing (UW-OFDM), has been introduced recently. It has been shown that UW-OFDM has better spectral properties and also a superior bit error ratio (BER) performance over conventional cyclic prefix (CP) based OFDM. In UW-OFDM, the CPs are replaced by deterministic sequences, the so-called unique words (UWs). This is...
Massive multiple-input multiple-output (MIMO) systems are one of key technologies for next generation cellular providing high spectral efficiency. While the effect of most interference and noise vanishes as the number of antennas increases, performance of massive MIMO systems is limited by pilot contamination caused by correlated pilot. Pilot reuse, allowing users in distant cells to use the same...
Three prominent features of massive MIMO are studied using channel measurements. Those features are extensively exploited in signal processing methods for massive MIMO and have been only partially, or not at all, validated. First, channel hardening is characterized as a function of the number of antennas. Second, user decorrelation is evaluated as a function of the distance between users. At last,...
In this work, we consider a two-channel multiple-input multiple-output (MIMO) passive detection problem, in which there is a surveillance array and a reference array. The reference array is known to carry a linear combination of broadband noise and a subspace signal of known dimension but unknown basis. The question is whether the surveillance channel carries a linear combination of broadband noise...
This work investigates the impact of imperfect statistical information in the uplink of massive MIMO systems. In particular, we first show why covariance information is needed and then propose two schemes for covariance matrix estimation. A lower bound on the spectral efficiency (SE) of any combining scheme is derived, under imperfect covariance knowledge, and a closed-form expression is computed...
We propose an efficient multiple-input multiple-output (MIMO) video broadcasting technique with low computational complexity that well serves different types of users residing inside the service area of a base station. We consider a video broadcasting scenario in which heterogeneous users with different display resolutions, different operating bit rates, and different numbers of receive antennas are...
There has been growing interest in millimeter wave (mmWave) multiple-input multiple-output (MIMO) systems, which would likely employ hybrid analog-digital precoding with large-scale analog arrays deployed at wide bandwidths. Primary challenges here are how to efficiently estimate the large-dimensional frequency-selective channels and customize the wideband hybrid analog-digital precoders and combiners...
This article introduces a spectral method for statistical subspace clustering. The method is built upon standard kernel spectral clustering techniques, however carefully tuned by theoretical understanding arising from random matrix findings. We show in particular that our method provides high clustering performance while standard kernel choices provably fail. An application to user grouping based...
By employing sparse sampling, MIMO radars with matrix completion (MIMO-MC) achieve the performance of MIMO radars but with significantly fewer data samples. Further, due to the way the sparse sampling modulates the interference channel between radar and communication systems, MIMO-MC radars are good candidates for spectrum sharing. In this paper, we design a scenario in which a MIMO-MC radar optimally...
We consider wireless backhauling in mobile networks, employing large-scale full-dimension MIMO antenna arrays on both sides of the link. Our focus is on design strategies for transmit and receive antenna combiners, assuming FDD transmission and limited feedback operation. We investigate the performance of two competing philosophies: 1) An algebraic approach in which antenna combiners are calculated...
This paper considers distributed massive MIMO networks where a large number of antennas, either collocated or geographically scattered over a region, communicate with mobile users. This communication is impaired by interference from similar transmissions in adjacent regions and by noise. Focusing on zero-forcing (ZF) reception, we derive simple expressions that very accurately approximate the instantaneous...
The large number of analog received signals to be processed in massive MIMO systems renders conventional high-precision analog-to-digital conversion (ADC) not feasible in terms of cost- and power-efficiency. In this paper we present a novel ADC architecture inspired by the principles of integer-forcing source coding, which jointly reconstructs the received signals in the digital domain. This scheme...
We consider wireless networks of remote radio heads (RRH) with large antenna-arrays, operated in TDD, with uplink (UL) training and channel-reciprocity based downlink (DL) transmission. To achieve large area spectral efficiencies, we advocate the use of methods that rely on rudimentary scheduling, decentralized operation at each RRH and user-centric DL transmission. A slotted system is assumed, whereby...
We present a mathematical analysis of linear precoders for downlink multiuser massive MIMO. In the scenario we consider, one-bit digital-to-analog converters are employed at the basestation antennas for mitigating power consumption and hardware complexity. Using the Bussgang theorem, a probability-of-error analysis for a general precoder is presented. The special case of zero-forcing (ZF) precoders...
We consider a downlink 1-bit quantized multiuser (MU) multiple-input-multiple-output (MIMO) system, where 1-bit digital-to-analog (DACs) and analog-to-digital converters (ADCs) are used at the transmitter and the receiver for economical and computational efficiency. We end up with a discrete memoryless channel with input and output vectors belonging to the QPSK constellation. In the context of massive...
Mixed hybrid-low resolution MIMO architectures reduce both the number of ADCs and their resolution to reduce power consumption. In such a system, the received signal suffers from two compression stages. One is due to the analog processing stage and the reduced number of RF chains, while the other is a result of signal quantization by the ADC converters. The compression steps both complicate the estimation...
Conventional centralized data detection algorithms for massive multi-user multiple-input multiple-output (MU-MIMO) systems, such as minimum mean square error (MMSE) equalization, result in excessively high raw baseband data rates and computing complexity at the centralized processing unit. Hence, practical base-station (BS) designs for massive MU-MIMO that rely on state-of-the-art hardware processors...
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