arXiv subjects

David J. Love

Publications and source records attributed to David J. Love.

At least 109 records · Page 6Linked to original sources

arXiv2018

Adaptive Beam Tracking with the Unscented Kalman Filter for Millimeter Wave Communication

Millimeter wave (mmWave) communication links for 5G cellular technology require high beamforming gain to overcome channel impairments and achieve high throughput. While much work has focused on estimating mmWave channels and designing beamforming schemes, the time dynamic nature of mmWave channels quickly renders estimates stale and increases sounding overhead. We model the underlying time dynamic state space of mmWave channels and design sounding beamformers suitable for tracking in a Kalman filtering framework. Given an initial channel estimate, filtering efficiently leads to refined estimates and allows forward prediction for higher sustained beamforming gain during data transmission. From tracked prior channel estimates, adaptively chosen optimal and constrained suboptimal beams reduce sounding overhead while minimizing estimation error.

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arXiv2018

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.

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arXiv2018

Channel Reconstruction-Based Hybrid Precoding for Millimeter Wave Multi-User MIMO Systems

The focus of this paper is on multi-user MIMO transmissions for millimeter wave systems with a hybrid precoding architecture at the base-station. To enable multi-user transmissions, the base-station uses a cell-specific codebook of beamforming vectors over an initial beam alignment phase. Each user uses a user-specific codebook of beamforming vectors to learn the top-P (where P >= 1) beam pairs in terms of the observed SNR in a single-user setting. The top-P beam indices along with their SNRs are fed back from each user and the base-station leverages this information to generate beam weights for simultaneous transmissions. A typical method to generate the beam weights is to use only the best beam for each user and either steer energy along this beam, or to utilize this information to reduce multi-user interference. The other beams are used as fall back options to address blockage or mobility. Such an approach completely discards information learned about the channel condition(s) even though each user feeds back this information. With this background, this work develops an advanced directional precoding structure for simultaneous transmissions at the cost of an additional marginal feedback overhead. This construction relies on three main innovations: 1) Additional feedback to allow the base-station to reconstruct a rank-P approximation of the channel matrix between it and each user, 2) A zeroforcing structure that leverages this information to combat multi-user interference by remaining agnostic of the receiver beam knowledge in the precoder design, and 3) A hybrid precoding architecture that allows both amplitude and phase control at low-complexity and cost to allow the implementation of the zeroforcing structure. Numerical studies show that the proposed scheme results in a significant sum rate performance improvement over naive schemes even with a coarse initial beam alignment codebook.

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arXiv2017

Noisy Beam Alignment Techniques for Reciprocal MIMO Channels

Future multi-input multi-output (MIMO) wireless communications systems will use beamforming as a first-step towards realizing the capacity requirements necessitated by the exponential increase in data demands. The focus of this work is on beam alignment for time-division duplexing (TDD) systems, for which we propose a number of novel algorithms. These algorithms seek to obtain good estimates of the optimal beamformer/combiner pair (which are the dominant singular vectors of the channel matrix). They are motivated by the power method, an iterative algorithm to determine eigenvalues and eigenvectors through repeated matrix multiplication. In contrast to the basic power method which considers only the most recent iteration and assumes noiseless links, the proposed techniques consider information from all the previous iterations of the algorithm and combine them in different ways. The first technique (Sequential Least-Squares method) sequentially constructs a least-squares estimate of the channel matrix, which is then used to calculate the beamformer/combiner pair estimate. The second technique (Summed Power method) aims to mitigate the effect of noise by using a linear combination of the previously tried beams to calculate the next beam, providing improved performance in the low-SNR regime (typical for mmWave systems) with minimal complexity/feedback overhead. A third technique (Least-Squares Initialized Summed Power method) combines the good performance of the first technique at the high-SNR regime with the low-complexity advantage of the second technique by priming the summed power method with initial estimates from the sequential method.

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arXiv2017

Non-Orthogonal Multiple Access in Multi-Cell Networks: Theory, Performance, and Practical Challenges

Non-orthogonal multiple access (NOMA) is a potential enabler for the development of 5G and beyond wireless networks. By allowing multiple users to share the same time and frequency, NOMA can scale up the number of served users, increase the spectral efficiency, and improve user-fairness compared to existing orthogonal multiple access (OMA) techniques. While single-cell NOMA has drawn significant attention recently, much less attention has been given to multi-cell NOMA. This article discusses the opportunities and challenges of NOMA in a multi-cell environment. As the density of base stations and devices increases, inter-cell interference becomes a major obstacle in multi-cell networks. As such, identifying techniques that combine interference management approaches with NOMA is of great significance. After discussing the theory behind NOMA, this paper provides an overview of the current literature and discusses key implementation and research challenges, with an emphasis on multi-cell NOMA.

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arXiv2017

Common Codebook Millimeter Wave Beam Design: Designing Beams for Both Sounding and Communication with Uniform Planar Arrays

Fifth generation (5G) wireless networks are expected to utilize wide bandwidths available at millimeter wave (mmWave) frequencies for enhancing system throughput. However, the unfavorable channel conditions of mmWave links, e.g., higher path loss and attenuation due to atmospheric gases or water vapor, hinder reliable communications. To compensate for these severe losses, it is essential to have a multitude of antennas to generate sharp and strong beams for directional transmission. In this paper, we consider mmWave systems using uniform planar array (UPA) antennas, which effectively place more antennas on a two-dimensional grid. A hybrid beamforming setup is also considered to generate beams by combining a multitude of antennas using only a few radio frequency chains. We focus on designing a set of transmit beamformers generating beams adapted to the directional characteristics of mmWave links assuming a UPA and hybrid beamforming. We first define ideal beam patterns for UPA structures. Each beamformer is constructed to minimize the mean squared error from the corresponding ideal beam pattern. Simulation results verify that the proposed codebooks enhance beamforming reliability and data rate in mmWave systems.

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arXiv2016

On the Spatial Degrees of Freedom of Multicell and Multiuser MIMO Channels

We study the converse and achievability for the degrees of freedom of the multicellular multiple-input multiple-output (MIMO) multiple access channel (MAC) with constant channel coefficients. We assume L>1 homogeneous cells with K>0 users per cell where the users have M antennas and the base stations are equipped with N antennas. The degrees of freedom outer bound for this L-cell and K-user MIMO MAC is formulated. The characterized outer bound uses insight from a limit on the total degrees of freedom for the L-cell heterogeneous MIMO network. We also show through an example that a scheme selecting a transmitter and performing partial message sharing outperforms a multiple distributed transmission strategy in terms of the total degrees of freedom. Simple linear schemes attaining the outer bound (i.e., those achieving the optimal degrees of freedom) are explores for a few cases. The conditions for the required spatial dimensions attaining the optimal degrees of freedom are characterized in terms of K, L, and the number of transmit streams. The optimal degrees of freedom for the two-cell MIMO MAC are examined by using transmit zero forcing and null space interference alignment and subsequently, simple receive zero forcing is shown to provide the optimal degrees of freedom for L>1. By the uplink and downlink duality, the degrees of freedom results in this paper are also applicable to the downlink. In the downlink scenario, we study the degrees of freedom of L-cell MIMO interference channel exploring multiuser diversity. Strong convergence modes of the instantaneous degrees of freedom as the number of users increases are characterized.

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arXiv2015

Antenna Grouping based Feedback Compression for FDD-based Massive MIMO Systems

Recent works on massive multiple-input multiple-output (MIMO) have shown that a potential breakthrough in capacity gains can be achieved by deploying a very large number of antennas at the basestation. In order to achieve the performance that massive MIMO systems promise, accurate transmit-side channel state information (CSI) should be available at the basestation. While transmit-side CSI can be obtained by employing channel reciprocity in time division duplexing (TDD) systems, explicit feedback of CSI from the user terminal to the basestation is needed for frequency division duplexing (FDD) systems. In this paper, we propose an antenna grouping based feedback reduction technique for FDD-based massive MIMO systems. The proposed algorithm, dubbed antenna group beamforming (AGB), maps multiple correlated antenna elements to a single representative value using pre-designed patterns. The proposed method modifies the feedback packet by introducing the concept of a header to select a suitable group pattern and a payload to quantize the reduced dimension channel vector. Simulation results show that the proposed method achieves significant feedback overhead reduction over conventional approach performing the vector quantization of whole channel vector under the same target sum rate requirement.

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arXiv2015

Training Sequence Design for Feedback Assisted Hybrid Beamforming in Massive MIMO Systems

The use of large-scale antenna systems in future commercial wireless communications is an emerging technology that uses an excess of transmit antennas to realize high spectral efficiency. Achieving potential gains with large-scale antenna arrays in practice hinges on sufficient channel estimation accuracy. Much prior work focuses on TDD based networks, relying on reciprocity between the uplink and downlink channels. However, most currently deployed commercial wireless systems are FDD based, making it difficult to exploit channel reciprocity. In massive MIMO FDD systems, the problem of channel estimation becomes even more challenging due to the attendant substantial training resources and feedback requirements which scale with the number of antennas. In this paper, we consider the problem of training sequence design that employs a set of training signals and its mapping to the training periods. We focus on reduced-dimension training sequence designs, along with transmit precoder designs, aimed at reducing both hardware complexity and power consumption. The resulting designs are extended to hybrid analog-digital beamforming systems, which employ a limited number of active RF chains for transmit precoding, by applying the Toeplitz distribution theorem to large-scale linear antenna systems. A practical guideline for training sequence parameter selection is presented along with performance analysis.

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arXiv2015

Adaptive Millimeter Wave Beam Alignment for Dual-Polarized MIMO Systems

Fifth generation wireless systems are expected to employ multiple antenna communication at millimeter wave (mmWave) frequencies using small cells within heterogeneous cellular networks. The high path loss of mmWave as well as physical obstructions make communication challenging. To compensate for the severe path loss, mmWave systems may employ a beam alignment algorithm that facilitates highly directional transmission by aligning the beam direction of multiple antenna arrays. This paper discusses a mmWave system employing dual-polarized antennas. First, we propose a practical soft-decision beam alignment (soft-alignment) algorithm that exploits orthogonal polarizations. By sounding the orthogonal polarizations in parallel, the equality criterion of the Welch bound for training sequences is relaxed. Second, the analog beamforming system is adapted to the directional characteristics of the mmWave link assuming a high Ricean K-factor and poor scattering environment. The soft-algorithm enables the mmWave system to align innumerable narrow beams to channel subspace in an attempt to effectively scan the mmWave channel. Thirds, we propose a method to efficiently adapt the number of channel sounding observations to the specific channel environment based on an approximate probability of beam misalignment. Simulation results show the proposed soft-alignment algorithm with adaptive sounding time effectively scans the channel subspace of a mobile user by exploiting polarization diversity.

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arXiv2015

Exploiting the Preferred Domain of FDD Massive MIMO Systems with Uniform Planar Arrays

Massive multiple-input multiple-output (MIMO) systems hold the potential to be an enabling technology for 5G cellular. Uniform planar array (UPA) antenna structures are a focus of much commercial discussion because of their ability to enable a large number of antennas in a relatively small area. With UPA antenna structures, the base station can control the beam direction in both the horizontal and vertical domains simultaneously. However, channel conditions may dictate that one dimension requires higher channel state information (CSI) accuracy than the other. We propose the use of an additional one bit of feedback information sent from the user to the base station to indicate the preferred domain on top of the feedback overhead of CSI quantization in frequency division duplexing (FDD) massive MIMO systems. Combined with variable-rate CSI quantization schemes, the numerical studies show that the additional one bit of feedback can increase the quality of CSI significantly for UPA antenna structures.

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arXiv2014

Secondary Spectrum Auctions for Markets with Communication Constraints

Auctions have been proposed as a way to provide economic incentives for primary users to dynamically allocate unused spectrum to other users in need of it. Previously proposed schemes do not take into account the fact that the power constraints of users might prevent them from transmitting their bid prices to the auctioneer with high precision and that transmitted bid prices must travel through a noisy channel. These schemes also have very high overheads which cannot be accommodated in wireless standards. We propose auction schemes where a central clearing authority auctions spectrum to users who bid for it, while taking into account quantization of prices, overheads in bid revelation, and noise in the channel explicitly. Our schemes are closely related to channel output feedback problems and, specifically, to the technique of posterior matching. We consider several scenarios where the objective of the clearing authority is to award spectrum to the bidders who value spectrum the most. We prove theoretically that this objective is asymptotically attained by our scheme when the bidders are non-strategic with constant bids. We propose separate schemes to make strategic users reveal their private values truthfully, to auction multiple sub-channels among strategic users, and to track slowly time-varying bid prices. Our simulations illustrate the optimality of our schemes for constant bid prices, and also demonstrate the effectiveness of our tracking algorithm for slowly time-varying bids.

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arXiv2014

Channel Estimation Techniques for Quantized Distributed Reception in MIMO Systems

The Internet of Things (IoT) could enable the development of cloud multiple-input multiple-output (MIMO) systems where internet-enabled devices can work as distributed transmission/reception entities. We expect that spatial multiplexing with distributed reception using cloud MIMO would be a key factor of future wireless communication systems. In this paper, we first review practical receivers for distributed reception of spatially multiplexed transmit data where the fusion center relies on quantized received signals conveyed from geographically separated receive nodes. Using the structures of these receivers, we propose practical channel estimation techniques for the block-fading scenario. The proposed channel estimation techniques rely on very simple operations at the received nodes while achieving near-optimal channel estimation performance as the training length becomes large.

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arXiv2014

Trellis-Extended Codebooks and Successive Phase Adjustment: A Path from LTE-Advanced to FDD Massive MIMO Systems

It is of great interest to develop efficient ways to acquire accurate channel state information (CSI) for frequency division duplexing (FDD) massive multiple-input multiple-output (MIMO) systems for backward compatibility. It is theoretically well known that the codebook size for CSI quantization should be increased as the number of transmit antennas becomes larger, and 3GPP long term evolution (LTE) and LTE-Advanced codebooks also follow this trend. Thus, in massive MIMO, it is hard to apply the conventional approach of using pre-defined vector-quantized codebooks for CSI quantization mainly because of codeword search complexity. In this paper, we propose a trellis-extended codebook (TEC) that can be easily harmonized with current wireless standards such as LTE or LTE-Advanced by extending standardized codebooks designed for 2, 4, or 8 antennas with trellis structures. TEC exploits a Viterbi decoder and convolutional encoder in channel coding as the CSI quantizer and the CSI reconstructer, respectively. By quantizing multiple channel entries simultaneously using standardized codebooks in a state transition of trellis search, TEC can achieve fractional bits per channel entry quantization to have a practical feedback overhead. Thus, TEC can solve both the complexity and the feedback overhead issues of CSI quantization in massive MIMO systems. We also develop trellis-extended successive phase adjustment (TE-SPA) which works as a differential codebook of TEC. This is similar to the dual codebook concept of LTE-Advanced. TE-SPA can reduce CSI quantization error even with lower feedback overhead in temporally correlated channels. Numerical results verify the effectiveness of the proposed schemes in FDD massive MIMO systems.

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arXiv2014

Distributed Reception with Spatial Multiplexing: MIMO Systems for the Internet of Things

The Internet of things (IoT) holds much commercial potential and could facilitate distributed multiple-input multiple-output (MIMO) communication in future systems. We study a distributed reception scenario in which a transmitter equipped with multiple antennas sends multiple streams via spatial multiplexing to a large number of geographically separated single antenna receive nodes. The receive nodes then quantize their received signals and forward the quantized received signals to a receive fusion center. With global channel knowledge and forwarded quantized information from the receive nodes, the fusion center attempts to decode the transmitted symbols. We assume the transmit vector consists of phase shift keying (PSK) constellation points, and each receive node quantizes its received signal with one bit for each of the real and imaginary parts of the signal to minimize the transmission overhead between the receive nodes and the fusion center. Fusing this data is a non-trivial problem because the receive nodes cannot decode the transmitted symbols before quantization. Instead, each receive node processes a single quantity, i.e., the received signal, regardless of the number of transmitted symbols. We develop an optimal maximum likelihood (ML) receiver and a low-complexity zero-forcing (ZF)-type receiver at the fusion center. Despite its suboptimality, the ZF-type receiver is simple to implement and shows comparable performance with the ML receiver in the low signal-to-noise ratio (SNR) regime but experiences an error rate floor at high SNR. It is shown that this error floor can be overcome by increasing the number of receive nodes. Hence, the ZF-type receiver would be a practical solution for distributed reception with spatial multiplexing in the era of the IoT where we can easily have a large number of receive nodes.

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arXiv2014

Bounds on Eigenvalues of a Spatial Correlation Matrix

It is critical to understand the properties of spatial correlation matrices in massive multiple-input multiple-output (MIMO) systems. We derive new bounds on the extreme eigenvalues of a spatial correlation matrix that is characterized by the exponential model in this paper. The new upper bound on the maximum eigenvalue is tighter than the previous known bound. Moreover, numerical studies show that our new lower bound on the maximum eigenvalue is close to the true maximum eigenvalue in most cases. We also derive an upper bound on the minimum eigenvalue that is also tight. These bounds can be exploited to analyze many wireless communication scenarios including uniform planar arrays, which are expected to be widely used for massive MIMO systems.

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arXiv2014

Closed-Loop Beam Alignment for Massive MIMO Channel Estimation

Training sequences are designed to probe wireless channels in order to obtain channel state information for block-fading channels. Optimal training sounds the channel using orthogonal beamforming vectors to find an estimate that optimizes some cost function, such as mean square error. As the number of transmit antennas increases, however, the training overhead becomes significant. This creates a need for alternative channel estimation schemes for increasingly large transmit arrays. In this work, we relax the orthogonal restriction on sounding vectors. The use of a feedback channel after each forward channel use during training enables closed-loop sounding vector design. A misalignment cost function is introduced, which provides a metric to sequentially design sounding vectors. In turn, the structure of the sounding vectors aligns the transmit beamformer with the true channel direction, thereby increasing beamforming gain. This beam alignment scheme for massive MIMO is shown to improve beamforming gain over conventional orthogonal training for a MISO channel.

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arXiv2014

Coded Distributed Diversity: A Novel Distributed Reception Technique for Wireless Communication Systems

In this paper, we consider a distributed reception scenario where a transmitter broadcasts a signal to multiple geographically separated receive nodes over fading channels, and each node forwards a few bits representing a processed version of the received signal to a fusion center. The fusion center then tries to decode the transmitted signal based on the forwarded information from the receive nodes and possible channel state information. We show that there is a strong connection between the problem of minimizing a symbol error probability at the fusion center in distributed reception and channel coding in coding theory. This connection allows us to design a unified framework for coded distributed diversity reception. We focus linear block codes such as simplex codes or first-order Reed-Muller codes that achieve the Griesmer bound with equality to maximize the diversity gain. Due to its simple structure, no complex offline optimization process is needed to design the coding structure at the receive nodes for the proposed coded diversity technique. The proposed technique can support a wide array of distributed reception scenarios, i.e., arbitrary $M$-ary symbol transmission at the transmitter and received signal processing with multiple bits at the receive nodes. Numerical studies show that the proposed coded diversity technique can achieve practical symbol error rates even with moderate signal-to-noise ratio and numbers of the receive nodes.

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