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Wu S.X.,Chinese University of Hong Kong | Ma W.-K.,Chinese University of Hong Kong | So A.M.-C.,CUHK
IEEE Transactions on Signal Processing | Year: 2013

Consider transceiver designs in a multiuser multi-input single-output (MISO) downlink channel, where the users are to receive the same data stream simultaneously. This problem, known as physical-layer multicasting, has drawn much interest. Presently, a popularized approach is transmit beamforming, in which the beamforming optimization is handled by a rank-one approximation method called semidefinite relaxation (SDR). SDR-based beamforming has been shown to be promising for a small or moderate number of users. This paper describes two new transceiver strategies for physical-layer multicasting. The first strategy, called stochastic beamforming (SBF), randomizes the beamformer in a per-symbol time-varying manner, so that the rank-one approximation in SDR can be bypassed. We propose several efficiently realizable SBF schemes, and prove that their multicast achievable rate gaps with respect to the MISO multicast capacity must be no worse than 0.8314 bits/s/Hz, irrespective of any other factors such as the number of users. The use of channel coding and the assumption of sufficiently long code lengths play a crucial role in achieving the above result. The second strategy combines transmit beamforming and the Alamouti space-time code. The result is a rank-two generalization of SDR-based beamforming. We show by analysis that this SDR-based beamformed Alamouti scheme has a better worst-case effective signal-to-noise ratio (SNR) scaling, and hence a better multicast rate scaling, than SDR-based beamforming. We further the work by combining SBF and the beamformed Alamouti scheme, wherein an improved constant rate gap of 0.39 bits/s/Hz is proven. Simulation results show that under a channel-coded, many-user setting, the proposed multicast transceiver schemes yield significant SNR gains over SDR-based beamforming at the same bit error rate level. © 1991-2012 IEEE.


Sheng C.,CUHK | Tao Y.,KAIST
Proceedings of the ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems | Year: 2012

In the top-K range reporting problem, the dataset contains N points in the real domain ℝ, each of which is associated with a real-valued score. Given an interval [x 1,x 2] in ℝ and an integer K ≤ N, a query returns the K points in [x 1,x 2] having the smallest scores. We want to store the dataset in a structure so that queries can be answered efficiently. In the external memory model, the state of the art is a static structure that consumes O(N/B) space, answers a query in O(log B N + K/B) time, and can be constructed in O(N + (N log N / B) log M/B (N/B)) time, where B is the size of a disk block, and M the size of memory. We present a fully-dynamic structure that retains the same space and query bounds, and can be updated in O(log B 2 N) amortized time per insertion and deletion. Our structure can be constructed in O((N/B) log M/B (N/B)) time. © 2012 ACM.


Tao Y.,CUHK
Proceedings of the ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems | Year: 2014

We present a structure in external memory for top-k range reporting, which uses linear space, answers a query in O(lgB n + κ/B) I/Os, and supports an update in O(lgB n) amortized I/Os, where n is the input size, and B is the block size. This improves the state of the art which incurs O(lgB 2 n) amortized I/Os per update. Copyright 2014 ACM.


Sheng C.,CUHK | Tao Y.,CUHK
Proceedings of the ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems | Year: 2011

We consider the skyline problem (a.k.a. the maxima problem), which has been extensively studied in the database community. The input is a set P of d-dimensional points. A point dominates another if the former has a lower coordinate than the latter on every dimension. The goal is to find the skyline, which is the set of points p ∈ P such that p is not dominated by any other data point. In the external-memory model, the 2-d version of the problem is known to be solvable in O((N/B) log M/B(N/B)) I/Os, where N is the cardinality of P, B the size of a disk block, and M the capacity of main memory. For fixed d ≥ 3, we present an algorithm with I/O-complexity O((N/B) log d-2 M/B(N/B)). Previously, the best solution was adapted from an in-memory algorithm, and requires O((N/B) log d-2 2 (N/M)) I/Os. Copyright © 2011 ACM.


Sheng C.,CUHK | Tao Y.,CUHK
Proceedings of the ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems | Year: 2011

We consider the orthogonal range aggregation problem. The dataset S consists of N axis-parallel rectangles in R2, each of which is associated with an integer weight. Given an axisparallel rectangle Q and an aggregate function F, a query reports the aggregated result of the weights of the rectangles in S intersecting Q. The goal is to preprocess S into a structure such that all queries can be answered efficiently. We present indexing schemes to solve the problem in external memory when F = max (hence, min) and F = sum (hence, count and average), respectively. Our schemes have linear or near-linear space, and answer a query in O(logB N) or O(log2 B N) I/Os, where B is the disk block size. Copyright © 2011 ACM.

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