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Wei Yu

Publications and source records attributed to Wei Yu.

At least 235 records · Page 13Linked to original sources

Large-Scale MIMO versus Network MIMO for Multicell Interference Mitigation

This paper compares two important downlink multicell interference mitigation techniques, namely, large-scale (LS) multiple-input multiple-output (MIMO) and network MIMO. We consider a cooperative wireless cellular system operating in time-division duplex (TDD) mode, wherein each cooperating cluster includes $B$ base-stations (BSs), each equipped with multiple antennas and scheduling $K$ single-antenna users. In an LS-MIMO system, each BS employs $BM$ antennas not only to serve its scheduled users, but also to null out interference caused to the other users within the cooperating cluster using zero-forcing (ZF) beamforming. In a network MIMO system, each BS is equipped with only $M$ antennas, but interference cancellation is realized by data and channel state information exchange over the backhaul links and joint downlink transmission using ZF beamforming. Both systems are able to completely eliminate intra-cluster interference and to provide the same number of spatial degrees of freedom per user. Assuming the uplink-downlink channel reciprocity provided by TDD, both systems are subject to identical channel acquisition overhead during the uplink pilot transmission stage. Further, the available sum power at each cluster is fixed and assumed to be equally distributed across the downlink beams in both systems. Building upon the channel distribution functions and using tools from stochastic ordering, this paper shows, however, that from a performance point of view, users experience better quality of service, averaged over small-scale fading, under an LS-MIMO system than a network MIMO system. Numerical simulations for a multicell network reveal that this conclusion also holds true with regularized ZF beamforming scheme. Hence, given the likely lower cost of adding excess number of antennas at each BS, LS-MIMO could be the preferred route toward interference mitigation in cellular networks.

cs.IT↗

Learning High-level Image Representation for Image Retrieval via Multi-Task DNN using Clickthrough Data

Image retrieval refers to finding relevant images from an image database for a query, which is considered difficult for the gap between low-level representation of images and high-level representation of queries. Recently further developed Deep Neural Network sheds light on automatically learning high-level image representation from raw pixels. In this paper, we proposed a multi-task DNN learned for image retrieval, which contains two parts, i.e., query-sharing layers for image representation computation and query-specific layers for relevance estimation. The weights of multi-task DNN are learned on clickthrough data by Ring Training. Experimental results on both simulated and real dataset show the effectiveness of the proposed method.

cs.CV↗

Degrees of Freedom of MIMO Cellular Networks: Decomposition and Linear Beamforming Design

This paper investigates the symmetric degrees of freedom (DoF) of MIMO cellular networks with G cells and K users per cell, having N antennas at each base station and M antennas at each user. In particular, we investigate achievability techniques based on either decomposition with asymptotic interference alignment (IA) or linear beamforming schemes, and show that there are distinct regimes of (G,K,M,N) where one outperforms the other. We first note that both one-sided and two-sided decomposition with asymptotic IA achieve the same degrees of freedom. We then establish specific antenna configurations under which the DoF achieved using decomposition based schemes is optimal by deriving a set of outer bounds on the symmetric DoF. For linear beamforming schemes, we first focus on small networks and propose a structured approach to linear beamforming based on a notion called packing ratios. Packing ratio describes the interference footprint or shadow cast by a set of transmit beamformers and enables us to identify the underlying structures for aligning interference. Such a structured beamforming design can be shown to achieve the optimal spatially normalized DoF (sDoF) of two-cell two-user/cell network and the two-cell three-user/cell network. For larger networks, we develop an unstructured approach to linear interference alignment, where transmit beamformers are designed to satisfy conditions for IA without explicitly identifying the underlying structures for IA. The main numerical insight of this paper is that such an approach appears to be capable of achieving the optimal sDoF for MIMO cellular networks in regimes where linear beamforming dominates asymptotic decomposition, and a significant portion of sDoF elsewhere. Remarkably, polynomial identity test appears to play a key role in identifying the boundary of the achievable sDoF region in the former case.

cs.IT↗

Ion heating dynamics in solid buried layer targets irradiated by ultra-short intense laser pulses

We investigate bulk ion heating in solid buried layer targets irradiated by ultra-short laser pulses of relativistic intensities using particle-in-cell simulations. Our study focuses on a CD2-Al-CD2 sandwich target geometry. We find enhanced deuteron ion heating in a layer compressed by the expanding aluminium layer. A pressure gradient created at the Al-CD2 interface pushes this layer of deuteron ions towards the outer regions of the target. During its passage through the target, deuteron ions are constantly injected into this layer. Our simulations suggest that the directed collective outward motion of the layer is converted into thermal motion inside the layer, leading to deuteron temperatures higher than those found in the rest of the target. This enhanced heating can already be observed at laser pulse durations as low as 100 femtoseconds. Thus, detailed experimental surveys at repetition rates of several ten laser shots per minute are in reach at current high-power laser systems, which would allow for probing and optimizing the heating dynamics.

physics.plasm-ph↗

Uplink Multicell Processing with Limited Backhaul via Per-Base-Station Successive Interference Cancellation

This paper studies an uplink multicell joint processing model in which the base-stations are connected to a centralized processing server via rate-limited digital backhaul links. Unlike previous studies where the centralized processor jointly decodes all the source messages from all base-stations, this paper proposes a suboptimal achievability scheme in which the Wyner-Ziv compress-and-forward relaying technique is employed on a per-base-station basis, but successive interference cancellation (SIC) is used at the central processor to mitigate multicell interference. This results in an achievable rate region that is easily computable, in contrast to the joint processing schemes in which the rate regions can only be characterized by exponential number of rate constraints. Under the per-base-station SIC framework, this paper further studies the impact of the limited-capacity backhaul links on the achievable rates and establishes that in order to achieve to within constant number of bits to the maximal SIC rate with infinite-capacity backhaul, the backhaul capacity must scale logarithmically with the signal-to-interference-and-noise ratio (SINR) at each base-station. Finally, this paper studies the optimal backhaul rate allocation problem for an uplink multicell joint processing model with a total backhaul capacity constraint. The analysis reveals that the optimal strategy that maximizes the overall sum rate should also scale with the log of the SINR at each base-station.

cs.IT↗

The state-of-the-art in web-scale semantic information processing for cloud computing

Based on integrated infrastructure of resource sharing and computing in distributed environment, cloud computing involves the provision of dynamically scalable and provides virtualized resources as services over the Internet. These applications also bring a large scale heterogeneous and distributed information which pose a great challenge in terms of the semantic ambiguity. It is critical for application services in cloud computing environment to provide users intelligent service and precise information. Semantic information processing can help users deal with semantic ambiguity and information overload efficiently through appropriate semantic models and semantic information processing technology. The semantic information processing have been successfully employed in many fields such as the knowledge representation, natural language understanding, intelligent web search, etc. The purpose of this report is to give an overview of existing technologies for semantic information processing in cloud computing environment, to propose a research direction for addressing distributed semantic reasoning and parallel semantic computing by exploiting semantic information newly available in cloud computing environment.

cs.DC↗

Incremental Relaying for the Gaussian Interference Channel with a Degraded Broadcasting Relay

This paper studies incremental relay strategies for a two-user Gaussian relay-interference channel with an in-band-reception and out-of-band-transmission relay, where the link between the relay and the two receivers is modelled as a degraded broadcast channel. It is shown that generalized hash-and-forward (GHF) can achieve the capacity region of this channel to within a constant number of bits in a certain weak relay regime, where the transmitter-to-relay link gains are not unboundedly stronger than the interference links between the transmitters and the receivers. The GHF relaying strategy is ideally suited for the broadcasting relay because it can be implemented in an incremental fashion, i.e., the relay message to one receiver is a degraded version of the message to the other receiver. A generalized-degree-of-freedom (GDoF) analysis in the high signal-to-noise ratio (SNR) regime reveals that in the symmetric channel setting, each common relay bit can improve the sum rate roughly by either one bit or two bits asymptotically depending on the operating regime, and the rate gain can be interpreted as coming solely from the improvement of the common message rates, or alternatively in the very weak interference regime as solely coming from the rate improvement of the private messages. Further, this paper studies an asymmetric case in which the relay has only a single single link to one of the destinations. It is shown that with only one relay-destination link, the approximate capacity region can be established for a larger regime of channel parameters. Further, from a GDoF point of view, the sum-capacity gain due to the relay can now be thought as coming from either signal relaying only, or interference forwarding only.

cs.IT↗

Two Birds and One Stone: Gaussian Interference Channel with a Shared Out-of-Band Relay of Limited Rate

The two-user Gaussian interference channel with a shared out-of-band relay is considered. The relay observes a linear combination of the source signals and broadcasts a common message to the two destinations, through a perfect link of fixed limited rate $R_0$ bits per channel use. The out-of-band nature of the relay is reflected by the fact that the common relay message does not interfere with the received signal at the two destinations. A general achievable rate is established, along with upper bounds on the capacity region for the Gaussian case. For $R_0$ values below a certain threshold, which depends on channel parameters, the capacity region of this channel is determined in this paper to within a constant gap of $Δ=1.95$ bits. We identify interference regimes where a two-for-one gain in achievable rates is possible for every bit relayed, up to a constant approximation error. Instrumental to these results is a carefully-designed quantize-and-forward type of relay strategy along with a joint decoding scheme employed at destination ends. Further, we also study successive decoding strategies with optimal decoding order (corresponding to the order at which common, private, and relay messages are decoded), and show that successive decoding also achieves two-for-one gains asymptotically in regimes where a two-for-one gain is achievable by joint decoding; yet, successive decoding produces unbounded loss asymptotically when compared to joint decoding, in general.

cs.IT↗

On the Capacity of the $K$-User Cyclic Gaussian Interference Channel

This paper studies the capacity region of a $K$-user cyclic Gaussian interference channel, where the $k$th user interferes with only the $(k-1)$th user (mod $K$) in the network. Inspired by the work of Etkin, Tse and Wang, who derived a capacity region outer bound for the two-user Gaussian interference channel and proved that a simple Han-Kobayashi power splitting scheme can achieve to within one bit of the capacity region for all values of channel parameters, this paper shows that a similar strategy also achieves the capacity region of the $K$-user cyclic interference channel to within a constant gap in the weak interference regime. Specifically, for the $K$-user cyclic Gaussian interference channel, a compact representation of the Han-Kobayashi achievable rate region using Fourier-Motzkin elimination is first derived, a capacity region outer bound is then established. It is shown that the Etkin-Tse-Wang power splitting strategy gives a constant gap of at most 2 bits in the weak interference regime. For the special 3-user case, this gap can be sharpened to 1 1/2 bits by time-sharing of several different strategies. The capacity result of the $K$-user cyclic Gaussian interference channel in the strong interference regime is also given. Further, based on the capacity results, this paper studies the generalized degrees of freedom (GDoF) of the symmetric cyclic interference channel. It is shown that the GDoF of the symmetric capacity is the same as that of the classic two-user interference channel, no matter how many users are in the network.

cs.IT↗

On the Capacity of the K-User Cyclic Gaussian Interference Channel

This paper studies the capacity region of a $K$-user cyclic Gaussian interference channel, where the $k$th user interferes with only the $(k-1)$th user (mod $K$) in the network. Inspired by the work of Etkin, Tse and Wang, which derived a capacity region outer bound for the two-user Gaussian interference channel and proved that a simple Han-Kobayashi power splitting scheme can achieve to within one bit of the capacity region for all values of channel parameters, this paper shows that a similar strategy also achieves the capacity region for the $K$-user cyclic interference channel to within a constant gap in the weak interference regime. Specifically, a compact representation of the Han-Kobayashi achievable rate region using Fourier-Motzkin elimination is first derived, a capacity region outer bound is then established. It is shown that the Etkin-Tse-Wang power splitting strategy gives a constant gap of at most two bits (or one bit per dimension) in the weak interference regime. Finally, the capacity result of the $K$-user cyclic Gaussian interference channel in the strong interference regime is also given.

cs.IT↗

Data Structure Lower Bounds on Random Access to Grammar-Compressed Strings

In this paper we investigate the problem of building a static data structure that represents a string s using space close to its compressed size, and allows fast access to individual characters of s. This type of structures was investigated by the recent paper of Bille et al. Let n be the size of a context-free grammar that derives a unique string s of length L. (Note that L might be exponential in n.) Bille et al. showed a data structure that uses space O(n) and allows to query for the i-th character of s using running time O(log L). Their data structure works on a word RAM with a word size of logL bits. Here we prove that for such data structures, if the space is poly(n), then the query time must be at least (log L)^{1-ε}/log S where S is the space used, for any constant eps>0. As a function of n, our lower bound is Ω(n^{1/2-ε}). Our proof holds in the cell-probe model with a word size of log L bits, so in particular it holds in the word RAM model. We show that no lower bound significantly better than n^{1/2-ε} can be achieved in the cell-probe model, since there is a data structure in the cell-probe model that uses O(n) space and achieves O(\sqrt{n log n}) query time. The "bad" setting of parameters occurs roughly when L=2^{\sqrt{n}}. We also prove a lower bound for the case of not-as-compressible strings, where, say, L=n^{1+ε}. For this case, we prove that if the space is n polylog(n), then the query time must be at least Ω(log n/loglog n). The proof works by reduction to communication complexity, namely to the LSD problem, recently employed by Patrascu and others. We prove lower bounds also for the case of LZ-compression and Burrows-Wheeler (BWT) compression. All of our lower bounds hold even when the strings are over an alphabet of size 2 and hold even for randomized data structures with 2-sided error.

cs.CC↗

Gaussian Z-Interference Channel with a Relay Link: Achievability Region and Asymptotic Sum Capacity

This paper studies a Gaussian Z-interference channel with a rate-limited digital relay link from one receiver to another. Achievable rate regions are derived based on a combination of Han-Kobayashi common-private information splitting technique and several different relay strategies including compress-and-forward and a partial decode-and-forward strategy, in which the interference is partially decoded then binned and forwarded through the digital link for subtraction at the other end. For the Gaussian Z-interference channel with a digital link from the interference-free receiver to the interfered receiver, the capacity region is established in the strong interference regime; an achievable rate region is established in the weak interference regime. In the weak interference regime, the partial decode-and-forward strategy is shown to be asymptotically sum-capacity achieving in the high signal-to-noise ratio and high interference-to-noise ratio limit. In this case, each relay bit asymptotically improves the sum capacity by one bit. For the Gaussian Z-interference channel with a digital link from the interfered receiver to the interference-free receiver, the capacity region is established in the strong interference regime; achievable rate regions are established in the moderately strong and weak interference regimes. In addition, the asymptotically sum capacity is established in the limit of large relay link rate. In this case, the sum capacity improvement due to the digital link is bounded by half a bit when the interference link is weaker than certain threshold, but the sum capacity improvement becomes unbounded as the interference link becomes stronger.

cs.IT↗

Electrostatic field acceleration of laser-driven ion bunch by using double layer thin foils

Monoenergetic ion bunch generation and acceleration from double layer thin foil target irradiated by intense linearly polarized (LP) laser pulse is investigated using two-dimensional (2D) particle-in-cell (PIC) simulations. The low-Z ions in the front layer of the target are accelerated by the laser-driven hot electrons and penetrate through the high-Z ion layer to generate a quasi-monoenergetic ion bunch, and this bunch will continue to be accelerated by the quasi-stable electrostatic sheath field which is formed by the immobile high-Z ions and the hot electrons. This mechanism offers possibility to generate monoenergetic ion bunch without ultrahigh-contrast and ultrahigh gradient laser pulses in beam generation experiments, which is confirmed by our simulations.

physics.plasm-ph↗

Bit Allocation Laws for Multi-Antenna Channel Feedback Quantization: Multi-User Case

This paper addresses the optimal design of limited-feedback downlink multi-user spatial multiplexing systems. A multiple-antenna base-station is assumed to serve multiple single-antenna users, who quantize and feed back their channel state information (CSI) through a shared rate-limited feedback channel. The optimization problem is cast in the form of minimizing the average transmission power at the base-station subject to users' target signal-to-interference-plus-noise ratios (SINR) and outage probability constraints. The goal is to derive the feedback bit allocations among the users and the corresponding channel magnitude and direction quantization codebooks in a high-resolution quantization regime. Toward this end, this paper develops an optimization framework using approximate analytical closed-form solutions, the accuracy of which is then verified by numerical results. The results show that, for channels in the real space, the number of channel direction quantization bits should be $(M-1)$ times the number of channel magnitude quantization bits, where $M$ is the number of base-station antennas. Moreover, users with higher requested quality-of-service (QoS), i.e. lower target outage probabilities, and higher requested downlink rates, i.e. higher target SINR's, should use larger shares of the feedback rate. It is also shown that, for the target QoS parameters to be feasible, the total feedback bandwidth should scale logarithmically with the geometric mean of the target SINR values and the geometric mean of the inverse target outage probabilities. In particular, the minimum required feedback rate is shown to increase if the users' target parameters deviate from the corresponding geometric means. Finally, the paper shows that, as the total number of feedback bits $B$ increases, the performance of the limited-feedback system approaches the perfect-CSI system as ${2^{-{B}/{M^2}}}$.

cs.IT↗

On Noisy Network Coding for a Gaussian Relay Chain Network with Correlated Noises

Noisy network coding, which elegantly combines the conventional compress-and-forward relaying strategy and ideas from network coding, has recently drawn much attention for its simplicity and optimality in achieving to within constant gap of the capacity of the multisource multicast Gaussian network. The constant-gap result, however, applies only to Gaussian relay networks with independent noises. This paper investigates the application of noisy network coding to networks with correlated noises. By focusing on a four-node Gaussian relay chain network with a particular noise correlation structure, it is shown that noisy network coding can no longer achieve to within constant gap to capacity with the choice of Gaussian inputs and Gaussian quantization. The cut-set bound of the relay chain network in this particular case, however, can be achieved to within half a bit by a simple concatenation of a correlation-aware noisy network coding strategy and a decode-and-forward scheme.

cs.IT↗

Capacity of the Gaussian Relay Channel with Correlated Noises to Within a Constant Gap

This paper studies the relaying strategies and the approximate capacity of the classic three-node Gaussian relay channel, but where the noises at the relay and at the destination are correlated. It is shown that the capacity of such a relay channel can be achieved to within a constant gap of $\hf \log_2 3 =0.7925$ bits using a modified version of the noisy network coding strategy, where the quantization level at the relay is set in a correlation dependent way. As a corollary, this result establishes that the conventional compress-and-forward scheme also achieves to within a constant gap to the capacity. In contrast, the decode-and-forward and the single-tap amplify-and-forward relaying strategies can have an infinite gap to capacity in the regime where the noises at the relay and at the destination are highly correlated, and the gain of the relay-to-destination link goes to infinity.

cs.IT↗

Bit Allocation Law for Multi-Antenna Channel Feedback Quantization: Single-User Case

This paper studies the design and optimization of a limited feedback single-user system with multiple-antenna transmitter and single-antenna receiver. The design problem is cast in form of the minimizing the average transmission power at the base station subject to the user's outage probability constraint. The optimization is over the user's channel quantization codebook and the transmission power control function at the base station. Our approach is based on fixing the outage scenarios in advance and transforming the design problem into a robust system design problem. We start by showing that uniformly quantizing the channel magnitude in dB scale is asymptotically optimal, regardless of the magnitude distribution function. We derive the optimal uniform (in dB) channel magnitude codebook and combine it with a spatially uniform channel direction codebook to arrive at a product channel quantization codebook. We then optimize such a product structure in the asymptotic regime of $B\rightarrow \infty$, where $B$ is the total number of quantization feedback bits. The paper shows that for channels in the real space, the asymptotically optimal number of direction quantization bits should be ${(M{-}1)}/{2}$ times the number of magnitude quantization bits, where $M$ is the number of base station antennas. We also show that the performance of the designed system approaches the performance of the perfect channel state information system as $2^{-\frac{2B}{M+1}}$. For complex channels, the number of magnitude and direction quantization bits are related by a factor of $(M{-}1)$ and the system performance scales as $2^{-\frac{B}{M}}$ as $B\rightarrow\infty$.

cs.IT↗

Enhanced surface acceleration of fast electrons by using sub-wavelength grating targets

Surface acceleration of fast electrons in intense laser-plasma interaction is improved by using sub-wavelength grating targets. The fast electron beam emitted along the target surface was enhanced by more than three times relative to that by using planar target. The total number of the fast electrons ejected from the front side of target was also increased by about one time. The method to enhance the surface acceleration of fast electron is effective for various targets with sub-wavelength structured surface, and can be applied widely in the cone-guided fast ignition, energetic ion acceleration, plasma device, and other high energy density physics experiments.

physics.plasm-ph↗