7644449
A new scaling law on throughput and delay performance of wireless mobile relay networks over parallel fading channels
In this paper, utilizing the relay buffers, we propose an opportunistic decode-wait-and-forward relay scheme for a point-to-point communication system with a half-duplexing mobile relay network. The proposed scheme achieves the maximum throughput of Θ(log K) at a cost of O(1) total transmission power and O(K=q) average end-to-end packet delay, where 0 ≪ q ≤ ½ measures the speed of relays' mobility. It can be proved that this system throughput is unattainable for the existing designs with low relay mobility. Therefore, the proposed relay scheme can exploit the time diversity and relays' mobility more efficiently.
32959076
Combined Cross Layer Design and HARQ for TDD Multiuser Systems with Outdated CSIT
Cross-layer scheduling and hybrid ARQ (HARQ) are effective means to improve the spectral efficiency of wireless systems and have been widely adopted in next generation wireless systems. However, most of the existing works handle HARQ and cross-layer scheduling in a decoupled manner based on heuristic approach. In this paper, we propose an integrated design framework for cross-layer scheduling and HARQ design in TDD multiuser systems with outdated knowledge of channel state information at the base station (CSIT). We focus on incremental redundancy in HARQ and derive the asymptotically optimal cross-layer policy (power allocation, rate allocation and user selection policies) to optimize the system goodput. In addition, we derive analytically closed-form expressions for the average system goodput where we can obtain useful design insights. For instance, the average system goodput scales in the order of O(In L) where L is the maximum transmission number of a packet, illustrating how the HARQ can enhance the cross-layer system goodput gain.
3513124
Distributive subband allocation, power and rate control for relay-assisted OFDMA cellular system with imperfect system state knowledge
In this paper, we consider distributive subband, power and rate allocation for a two-hop downlink transmission in an orthogonal frequency-division multiple-access (OFDMA) cellular system with fixed relays which operate in decode-and-forward strategy. We take into account of the penalty of packet errors due to imperfect CSIT and system fairness by considering weighted sum goodput as our optimization objective. Based on the cluster-based architecture, we obtain a fast-converging distributive solution with only local imperfect CSIT by using decomposition of the optimization problem. To further reduce the signaling overhead and computational complexity, we propose a reduced feedback distributive solution, which can achieve asymptotically optimal performance for large number of users with arbitrarily small feedback overhead per user.We also derive asymptotic average system throughput so as to obtain useful design insights.
18276513
Decentralized Fair Resource Allocation for Relay-Assisted Cognitive Cellular Downlink Systems
In this paper, we consider a relay-assisted cognitive cellular downlink system dynamically accessing a spectrum licensed to a primary network, thereby improving the efficiency of spectrum usage. A cluster-based relay-assisted architecture is proposed, where relay stations are employed for minimizing the interference to users in the primary network and achieving fairness for cell-edge users. Based on this architecture, an optimal solution is derived for jointly controlling data rate, transmission power, and subband allocation to optimize the weighted sum goodput where proportional fair scheduling (PFS) is included as a special case. As shown by simulations, the proposed solution achieves significant throughput gains and better user fairness compared with existing designs.
9665993
Closed-loop cross-layer SDMA designs with outdated CSIT
In this paper, we propose a novel closed-loop approach for robust downlink multi-antenna cross-layer design with outdated channel state information at the transmitter (CSIT). Based on the ACK/NAK feedbacks from the mobiles, the proposed cross-layer design does not require the knowledge of CSIT error statistics. We formulate the cross-layer design as a mixed combinatorial search and Markov decision process (MDP). While it is well-known that general solutions for MDP are very complex, one important contribution of this paper is that we obtain simple closed-form power, rate and user allocation policies which are asymptotically optimal for small target frame error rate (FER). Simulation results illustrate that the performance of the proposed closed-loop cross-layer design is very robust with respect to the outdated CSIT, CSIT error model mismatch as well as channel variations due to Doppler.
3505472
Decentralized Fair Scheduling in Two-Hop Relay-Assisted Cognitive OFDMA Systems
In this paper, we consider a two-hop relay-assisted cognitive downlink Orthogonal frequency-division multiple access (OFDMA) system (named as secondary system) dynamically accessing a spectrum licensed to a primary network, thereby improving the efficiency of spectrum usage. A cluster-based relay-assisted architecture is proposed for the secondary system, where relay stations are employed for minimizing the interference to the users in the primary network and achieving fairness for cell-edge users in the secondary system. Based on this architecture, an asymptotically optimal solution is derived for jointly controlling data rates, transmission power, and subchannel allocation to optimize the average weighted sum goodput where the proportional fair scheduling (PFS) is included as a special case. This solution supports decentralized implementation, requires small communication overhead, and is robust against imperfect channel state information at the transmitter (CSIT) and imperfect sensing measurement. The proposed solution achieves significant throughput gain and better user-fairness compared with the existing designs. Finally, we derive a simple and asymptotically optimal scheduling solution as well as the associated closed-form performance under the proportional fair scheduling for a large number of users. The system throughput is shown to be O(N(1-qp)(1-qpN)lnlnKc), where Kc is the number of users in one cluster, N is the number of subchannels, and qp is the active probability of primary users.
5692674
Synthesizing trees by plantons
In this paper, we present a two-level statistical model for characterizing the stochastic and specific nature of trees. At the low level, we define plantons, which are a group of similar organs, to depict tree organ details statistically. At the high level, a set of transitions between plantons is provided to describe the stochastic distribution of organs.Based on such a tree model, we propose a novel tree modeling approach, synthesizing trees by plantons, which are extracted from tree samples. All tree samples are captured from the real world. We have designed a maximum likelihood estimation algorithm to acquire the two-level statistical tree model from single samples or multi- samples. Experimental results show that our new model is capable of synthesizing new trees with similar, yet visually different shapes.
42750715
NP-Completeness Results for All-Shortest-Path Interval Routing
k-Interval Routing Scheme (k-IRS) is a compact routing method that allows up to k interval labels to be assigned to an arc. A fundamental problem is to characterize the networks that admit k-IRS. Many of the problems related to single-shortest-path k-IRS have already been shown to be NP-complete. For all-shortest-path k-IRS, the characterization problem remains open for k≥ 1. We investigate the time complexity of devising minimal-space all-shortest-path k-IRS and prove that it is NP-complete to decide whether a graph admits an all-shortest-path k-IRS, for every integer k≥ 3, as well as whether a graph admits an all-shortest-path k-strict IRS, for every integer k≥ 4. These are the first NP-completeness results for all-shortest-path k-IRS where k is a constant and the graph is unweighted. Moreover, the NP-completeness holds also for the linear case.
2756749
Privacy-preserving genomic computation through program specialization
In this paper, we present a new approach to performing important classes of genomic computations (e.g., search for homologous genes) that makes a significant step towards privacy protection in this domain. Our approach leverages a key property of the human genome, namely that the vast majority of it is shared across humans (and hence public), and consequently relatively little of it is sensitive. Based on this observation, we propose a privacy-protection framework that partitions a genomic computation, distributing the part on sensitive data to the data provider and the part on the pubic data to the user of the data. Such a partition is achieved through program specialization that enables a biocomputing program to perform a concrete execution on public data and a symbolic execution on sensitive data. As a result, the program is simplified into an efficient query program that takes only sensitive genetic data as inputs. We prove the effectiveness of our techniques on a set of dynamic programming algorithms common in genomic computing. We develop a program transformation tool that automatically instruments a legacy program for specialization operations. We also demonstrate that our techniques can greatly facilitate secure multi-party computations on large biocomputing problems.
144647
Recognizing Textual Relatedness with Predicate-Argument Structures
In this paper, we first compare several strategies to handle the newly proposed three-way Recognizing Textual Entailment (RTE) task. Then we define a new measurement for a pair of texts, called Textual Relatedness, which is a weaker concept than semantic similarity or paraphrase. We show that an alignment model based on the predicate-argument structures using this measurement can help an RTE system to recognize the Unknown cases at the first stage, and contribute to the improvement of the overall performance in the RTE task. In addition, several heterogeneous lexical resources are tested, and different contributions from them are observed.
1460434
Log-based recovery for middleware servers
We have developed new methods for log-based recovery for middleware servers which involve thread pooling, private in-memory states for clients, shared in-memory state and message interactions among middleware servers. Due to the observed rareness of crashes, relatively small size of shared state and infrequency of shared state read/write accesses, we are able to reduce the overhead of message logging and shared state logging while maintaining recovery independence. Checkpointing has a very small impact on ongoing activities while still reducing recovery time. Our recovery mechanism enables client private states to be recovered in parallel after a crash. On a commercial middleware server platform, we have implemented a recovery infrastructure prototype, which demonstrates the manageability of system complexity and shows promising performance results.