arXiv subjects

Dongning Guo

Publications and source records attributed to Dongning Guo.

At least 55 records · Page 3Linked to original sources

arXiv2016

Mobile Millimeter Wave Channel Acquisition, Tracking, and Abrupt Change Detection

Millimeter wave provides a promising approach for meeting the ever-growing traffic demand in next generation wireless networks. It is crucial to obtain relatively accurate channel state information so that beamforming/combining can be performed to compensate for severe path loss in this band. In contrast to lower frequencies, a typical mobile millimeter wave channel consists of a few dominant paths. It is generally sufficient to estimate the path gains, angles of departure (AoD), and angles of arrival (AoA) of those paths. In this paper, multiple transmit and receive antennas and beamforming with a single baseband processing chain are assumed. We propose a framework for estimating millimeter wave channels with intermittent abrupt changes (e.g., blockage or emergence of dominant paths) and slow variations of AoDs and AoAs. The solution consists of three components: tracking of the slow channel variations, detection of abrupt changes, followed by (re-)acquisition of channel (and back to the tracking stage). For acquisition, we formulate a least squares problem and find its solution based on the Levenberg-Marquardt algorithm. To track slow variations of AoDs and AoAs, we propose a new approach using Kalman filtering. Finally, an algorithm based on a likelihood test is devised for detecting abrupt changes. Simulation results show that, with moderate signal-to-noise ratios, the proposed scheme can achieve more than 8 dB higher estimation accuracy than several other methods using the same number of pilots.

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arXiv2016

Sparse Channel Estimation for Massive MIMO with 1-bit Feedback per Dimension

In massive multiple-input multiple-output (MIMO) systems, acquisition of the channel state information at the transmitter side (CSIT) is crucial. In this paper, a practical CSIT estimation scheme is proposed for frequency division duplexing (FDD) massive MIMO systems. Specifically, each received pilot symbol is first quantized to one bit per dimension at the receiver side and then the quantized bits are fed back to the transmitter. A joint one-bit compressed sensing algorithm is implemented at the transmitter to recover the channel matrices. The algorithm leverages the hidden joint sparsity structure in the user channel matrices to minimize the training and feedback overhead, which is considered to be a major challenge for FDD systems. Moreover, the one-bit compressed sensing algorithm accurately recovers the channel directions for beamforming. The one-bit feedback mechanism can be implemented in practical systems using the uplink control channel. Simulation results show that the proposed scheme nearly achieves the maximum output signal-to-noise-ratio for beamforming based on the estimated CSIT.

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arXiv2016

Licensed and Unlicensed Spectrum Allocation in Heterogeneous Networks

In future networks, an operator may employ a wide range of access points using diverse radio access technologies (RATs) over multiple licensed and unlicensed frequency bands. This paper studies centralized user association and spectrum allocation across many access points in such a heterogeneous network (HetNet). Such centralized control is on a relatively slow timescale to allow information exchange and joint optimization over multiple cells. This is in contrast and complementary to fast timescale distributed scheduling. A queueing model is introduced to capture the lower spectral efficiency, reliability, and additional delays of data transmission over the unlicensed bands due to contention and/or listen-before-talk requirements. Two optimization-based spectrum allocation schemes are proposed along with efficient algorithms for computing the allocations. The proposed solutions are fully aware of traffic loads, network topology, as well as external interference levels in the unlicensed bands. Packet-level simulation results show that the proposed schemes significantly outperform orthogonal and full-frequency-reuse allocations under all traffic conditions.

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arXiv2016

A Generalized LDPC Framework for Robust and Sublinear Compressive Sensing

Compressive sensing aims to recover a high-dimensional sparse signal from a relatively small number of measurements. In this paper, a novel design of the measurement matrix is proposed. The design is inspired by the construction of generalized low-density parity-check codes, where the capacity-achieving point-to-point codes serve as subcodes to robustly estimate the signal support. In the case that each entry of the $n$-dimensional $k$-sparse signal lies in a known discrete alphabet, the proposed scheme requires only $O(k \log n)$ measurements and arithmetic operations. In the case of arbitrary, possibly continuous alphabet, an error propagation graph is proposed to characterize the residual estimation error. With $O(k \log^2 n)$ measurements and computational complexity, the reconstruction error can be made arbitrarily small with high probability.

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arXiv2016

Energy-Efficient Cell Activation, User Association, and Spectrum Allocation in Heterogeneous Networks

Next generation (5G) cellular networks are expected to be supported by an extensive infrastructure with many-fold increase in the number of cells per unit area compared to today. The total energy consumption of base transceiver stations (BTSs) is an important issue for both economic and environmental reasons. In this paper, an optimization-based framework is proposed for energy-efficient global radio resource management in heterogeneous wireless networks. Specifically, with stochastic arrivals of known rates intended for users, the smallest set of BTSs is activated with jointly optimized user association and spectrum allocation to stabilize the network first and then minimize the delay. The scheme can be carried out periodically on a relatively slow timescale to adapt to aggregate traffic variations and average channel conditions. Numerical results show that the proposed scheme significantly reduces the energy consumption and increases the quality of service compared to existing schemes in the literature.

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arXiv2015

Tracking Angles of Departure and Arrival in a Mobile Millimeter Wave Channel

Millimeter wave provides a very promising approach for meeting the ever-growing traffic demand in next generation wireless networks. To utilize this band, it is crucial to obtain the channel state information in order to perform beamforming and combining to compensate for severe path loss. In contrast to lower frequencies, a typical millimeter wave channel consists of a few dominant paths. Thus it is generally sufficient to estimate the path gains, angles of departure (AoDs), and angles of arrival (AoAs) of those paths. Proposed in this paper is a dual timescale model to characterize abrupt channel changes (e.g., blockage) and slow variations of AoDs and AoAs. This work focuses on tracking the slow variations and detecting abrupt changes. A Kalman filter based tracking algorithm and an abrupt change detection method are proposed. The tracking algorithm is compared with the adaptive algorithm due to Alkhateeb, Ayach, Leus and Heath (2014) in the case with single radio frequency chain. Simulation results show that to achieve the same tracking performance, the proposed algorithm requires much lower signal-to-noise-ratio (SNR) and much fewer pilots than the other algorithm. Moreover, the change detection method can always detect abrupt changes with moderate number of pilots and SNR.

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arXiv2015

Traffic-Driven Spectrum Allocation in Heterogeneous Networks

Next generation cellular networks will be heterogeneous with dense deployment of small cells in order to deliver high data rate per unit area. Traffic variations are more pronounced in a small cell, which in turn lead to more dynamic interference to other cells. It is crucial to adapt radio resource management to traffic conditions in such a heterogeneous network (HetNet). This paper studies the optimization of spectrum allocation in HetNets on a relatively slow timescale based on average traffic and channel conditions (typically over seconds or minutes). Specifically, in a cluster with $n$ base transceiver stations (BTSs), the optimal partition of the spectrum into $2^n$ segments is determined, corresponding to all possible spectrum reuse patterns in the downlink. Each BTS's traffic is modeled using a queue with Poisson arrivals, the service rate of which is a linear function of the combined bandwidth of all assigned spectrum segments. With the system average packet sojourn time as the objective, a convex optimization problem is first formulated, where it is shown that the optimal allocation divides the spectrum into at most $n$ segments. A second, refined model is then proposed to address queue interactions due to interference, where the corresponding optimal allocation problem admits an efficient suboptimal solution. Both allocation schemes attain the entire throughput region of a given network. Simulation results show the two schemes perform similarly in the heavy-traffic regime, in which case they significantly outperform both the orthogonal allocation and the full-frequency-reuse allocation. The refined allocation shows the best performance under all traffic conditions.

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arXiv2014

Traffic Driven Resource Allocation in Heterogenous Wireless Networks

Most work on wireless network resource allocation use physical layer performance such as sum rate and outage probability as the figure of merit. These metrics may not reflect the true user QoS in future heterogenous networks (HetNets) with many small cells, due to large traffic variations in overlapping cells with complicated interference conditions. This paper studies the spectrum allocation problem in HetNets using the average packet sojourn time as the performance metric. To be specific, in a HetNet with $K$ base terminal stations (BTS's), we determine the optimal partition of the spectrum into $2^K$ possible spectrum sharing combinations. We use an interactive queueing model to characterize the flow level performance, where the service rates are decided by the spectrum partition. The spectrum allocation problem is formulated using a conservative approximation, which makes the optimization problem convex. We prove that in the optimal solution the spectrum is divided into at most $K$ pieces. A numerical algorithm is provided to solve the spectrum allocation problem on a slow timescale with aggregate traffic and service information. Simulation results show that the proposed solution achieves significant gains compared to both orthogonal and full spectrum reuse allocations with moderate to heavy traffic.

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arXiv2014

Joint Bi-Directional Training of Nonlinear Precoders and Receivers in Cellular Networks

Joint optimization of nonlinear precoders and receive filters is studied for both the uplink and downlink in a cellular system. For the uplink, the base transceiver station (BTS) receiver implements successive interference cancellation, and for the downlink, the BTS station pre-compensates for the interference with Tomlinson-Harashima precoding (THP). Convergence of alternating optimization of receivers and transmitters in a single cell is established when filters are updated according to a minimum mean squared error (MMSE) criterion, subject to appropriate power constraints. Adaptive algorithms are then introduced for updating the precoders and receivers in the absence of channel state information, assuming time-division duplex transmissions with channel reciprocity. Instead of estimating the channels, the filters are directly estimated according to a least squares criterion via bi-directional training: Uplink pilots are used to update the feedforward and feedback filters, which are then used as interference pre-compensation filters for downlink training of the mobile receivers. Numerical results show that nonlinear filters can provide substantial gains relative to linear filters with limited forward-backward iterations.

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arXiv2014

Maximizing Mobile Coverage via Optimal Deployment of Base Station and Relays

Deploying relays and/or mobile base stations is a major means of extending the coverage of a wireless network. This paper presents models, analytical results, and algorithms to answer two related questions: The first is where to deploy relays in order to extend the reach from a base station to the maximum; the second is where to deploy a mobile base station and how many relays are needed to reach any point in a given area. Simple time-division and frequency-division scheduling schemes as well as an end-to-end data rate requirement are assumed. An important use case of the results is in the Public Safety Broadband Network, in which deploying relays and mobile base stations is often crucial to provide coverage to an incident scene.

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arXiv2014

In-Band Full-Duplex Wireless: Challenges and Opportunities

In-band full-duplex (IBFD) operation has emerged as an attractive solution for increasing the throughput of wireless communication systems and networks. With IBFD, a wireless terminal is allowed to transmit and receive simultaneously in the same frequency band. This tutorial paper reviews the main concepts of IBFD wireless. Because one the biggest practical impediments to IBFD operation is the presence of self-interference, i.e., the interference caused by an IBFD node's own transmissions to its desired receptions, this tutorial surveys a wide range of IBFD self-interference mitigation techniques. Also discussed are numerous other research challenges and opportunities in the design and analysis of IBFD wireless systems.

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arXiv2014

Many-Access Channels: The Gaussian Case with Random User Activities

Classical multiuser information theory studies the fundamental limits of models with a fixed (often small) number of users as the coding blocklength goes to infinity. This work proposes a new paradigm, referred to as many-user information theory, where the number of users is allowed to grow with the blocklength. This paradigm is motivated by emerging systems with a massive number of users in an area, such as machine-to-machine communication systems and sensor networks. The focus of the current paper is the many-access channel model, which consists of a single receiver and many transmitters, whose number increases unboundedly with the blocklength. Moreover, an unknown subset of transmitters may transmit in a given block and need to be identified. A new notion of capacity is introduced and characterized for the Gaussian many-access channel with random user activities. The capacity can be achieved by first detecting the set of active users and then decoding their messages.

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arXiv2014

Many-Broadcast Channels: Definition and Capacity in the Degraded Case

Classical multiuser information theory studies the fundamental limits of models with a fixed (often small) number of users as the coding blocklength goes to infinity. Motivated by emerging systems with a massive number of users, this paper studies the new {\em many-user paradigm}, where the number of users is allowed to grow with the blocklength. The focus of this paper is the degraded many-broadcast channel model, whose number of users may grow as fast as linearly with the blocklength. A notion of capacity in terms of message length is defined and an example of Gaussian degraded many-broadcast channel is studied. In addition, a numerical example for the Gaussian degraded many-broadcast channel with fixed transmit power constraint is solved, where every user achieves strictly positive message length asymptotically.

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arXiv2014

A Message-Passing Approach to Combating Hidden Terminals in Wireless Networks

Collisions with hidden terminals is a major cause of performance degradation in 802.11 and likewise wireless networks. Carrier sense multiple access with collision avoidance (CSMA/CA) is utilized to avoid collisions at the cost of spatial reuse. This report studies receiver design to mitigate interference from hidden terminals. A wireless channel model with correlated fading in time is assumed. A message-passing approach is proposed, in which a receiver can successfully receive and decode partially overlapping transmissions from two sources rather than treating undesired one as thermal noise. Numerical results of both coded and uncoded systems show the advantage of the receiver over conventional receivers.

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arXiv2013

Distributed Ranging and Localization for Wireless Networks via Compressed Sensing

Location-based services in a wireless network require nodes to know their locations accurately. Conventional solutions rely on contention-based medium access, where only one node can successfully transmit at any time in any neighborhood. In this paper, a novel, complete, distributed ranging and localization solution is proposed, which let all nodes in the network broadcast their location estimates and measure distances to all neighbors simultaneously. An on-off signaling is designed to overcome the physical half-duplex constraint. In each iteration, all nodes transmit simultaneously, each broadcasting codewords describing the current location estimate. From the superposed signals from all neighbors, each node decodes their neighbors' locations and also estimates their distances using the signal strengths. The node then broadcasts its improved location estimates in the subsequent iteration. Simulations demonstrate accurate localization throughout a large network over a few thousand symbol intervals, suggesting much higher efficiency than conventional schemes based on ALOHA or CSMA.

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arXiv2013

Virtual Full Duplex Wireless Broadcasting via Compressed Sensing

A novel solution is proposed to undertake a frequent task in wireless networks, which is to let all nodes broadcast information to and receive information from their respective one-hop neighboring nodes. The contribution is two-fold. First, as each neighbor selects one message-bearing codeword from its unique codebook for transmission, it is shown that decoding their messages based on a superposition of those codewords through the multiaccess channel is fundamentally a problem of compressed sensing. In the case where each message consists of a small number of bits, an iterative algorithm based on belief propagation is developed for efficient decoding. Second, to satisfy the half-duplex constraint, each codeword consists of randomly distributed on-slots and off-slots. A node transmits during its on-slots, and listens to its neighbors only through its own off-slots. Over one frame interval, each node broadcasts a message to neighbors and simultaneously decodes neighbors' messages based on the superposed signals received through its own off-slots. Thus the solution fully exploits the multiaccess nature of the wireless medium and addresses the half-duplex constraint at the fundamental level. In a network consisting of Poisson distributed nodes, numerical results demonstrate that the proposed scheme often achieves several times the rate of slotted ALOHA and CSMA with the same packet error rate.

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arXiv2013

The Public Safety Broadband Network: A Novel Architecture with Mobile Base Stations

A nationwide interoperable public safety broadband network is being planned by the United States government. The network will be based on long term evolution (LTE) standards and use recently designated spectrum in the 700 MHz band. The public safety network has different objectives and traffic patterns than commercial wireless networks. In particular, the public safety network puts more emphasis on coverage, reliability and latency in the worst case scenario. Moreover, the routine public safety traffic is relatively light, whereas when a major incident occurs, the traffic demand at the incident scene can be significantly heavier than that in a commercial network. Hence it is prohibitively costly to build the public safety network using conventional cellular network architecture consisting of an infrastructure of stationary base transceiver stations. A novel architecture is proposed in this paper for the public safety broadband network. The architecture deploys stationary base stations sparsely to serve light routine traffic and dispatches mobile base stations to incident scenes along with public safety personnel to support heavy traffic. The analysis shows that the proposed architecture can potentially offer more than 75% reduction in terms of the total number of base stations needed.

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arXiv2013

Wireless MIMO Switching: Weighted Sum Mean Square Error and Sum Rate Optimization

This paper addresses joint transceiver and relay design for a wireless multiple-input-multiple-output (MIMO) switching scheme that enables data exchange among multiple users. Here, a multi-antenna relay linearly precodes the received (uplink) signals from multiple users before forwarding the signal in the downlink, where the purpose of precoding is to let each user receive its desired signal with interference from other users suppressed. The problem of optimizing the precoder based on various design criteria is typically non-convex and difficult to solve. The main contribution of this paper is a unified approach to solve the weighted sum mean square error (MSE) minimization and weighted sum rate maximization problems in MIMO switching. Specifically, an iterative algorithm is proposed for jointly optimizing the relay's precoder and the users' receive filters to minimize the weighted sum MSE. It is also shown that the weighted sum rate maximization problem can be reformulated as an iterated weighted sum MSE minimization problem and can therefore be solved similarly to the case of weighted sum MSE minimization. With properly chosen initial values, the proposed iterative algorithms are asymptotically optimal in both high and low signal-to-noise ratio (SNR) regimes for MIMO switching, either with or without self-interference cancellation (a.k.a., physical-layer network coding). Numerical results show that the optimized MIMO switching scheme based on the proposed algorithms significantly outperforms existing approaches in the literature.

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