Joint cross-layer scheduling and spectrum sensing for OFDMA cognitive radio systems
In most of the existing works on cognitive radio (CR) systems, the spectrum sensing and the cross-layer scheduling are designed separately. Specifically, the sensing module first determines whether or not a channel resource is available for the CR system based on the sensing information. The scheduling module then schedules the data transmission of different users on the available channels based on the hard-decision sensing information (HSI). In this paper, we shall propose a joint crosslayer and sensing design and study its performance advantages over the aforementioned traditional decoupled approaches. We shall consider the downlink transmission of an OFDMA-based secondary system sharing the spectrum with primary users using cognitive radio technology. We shall rely on the joint design framework to optimize a system utility, which adapts the power allocation and the subcarrier assignment across the secondary users (under a average interference constraint to the primary users) based on both the channel state information (CSI) and the raw sensing information (RSI). In addition, we shall also propose a distributed implementation for the cross-layer sensing and scheduling design using primal-dual decomposition approach. Simulation results reveals the substantial performance gain of the proposed joint design over the conventional CR systems.

title: A new scaling law on throughput and delay performance of wireless mobile relay networks over parallel fading channels
abstract: 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.

title: Combined cross-layer design and HARQ for multiuser systems with outdated channel state information at transmitter (CSIT) in slow fading channels
abstract: Cross-layer scheduling and hybrid ARQ (HARQ) are effective means to improve the spectral efficiency of wireless systems. However, most of the existing works handle HARQ and cross-layer scheduling in a decoupled manner based on heuristic approaches. In this paper, we propose an integrated design framework for cross-layer scheduling and HARQ design in multiuser systems with slow fading channel and outdated knowledge of channel state information at the base station (CSIT). We consider both the chase combining and incremental redundancy in HARQ. We define the average system goodput (which measures the average bits successfully delivered to the receiver) as the measure of system performance. Based on information theoretical approach, we derive the asymptotically optimal cross-layer policy (power allocation, rate allocation and user selection policies) to optimize the average system goodput with HARQ. In addition, we derive analytically the closed-form expression of the average system goodput, from which we can obtain useful design insights such as the role of HARQ in the overall cross-layer gain, the tradeoff between the system goodput and the HARQ delay as well as the sensitivity of the average system goodput with respect to the CSIT quality.

title: Decentralized Fair Resource Allocation for Relay-Assisted Cognitive Cellular Downlink Systems
abstract: 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.

title: Closed-loop cross-layer SDMA designs with outdated CSIT
abstract: 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.

title: Decentralized Fair Scheduling in Two-Hop Relay-Assisted Cognitive OFDMA Systems
abstract: 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.

title: Mixed Reality-Mediated Collaborative Design System: Concept, Prototype, and Experimentation
abstract: This paper introduces a Mixed Reality-mediated Collaborative design system, named MR-Collab, which combines Mixed Reality (MR), Augmented Reality (AR) and various channels of communication technologies. The concept and system of MR-Collabare developed based on the Benford's Mixed-Reality boundaries theory. This paper presents how this theory is used as a tool to analyze the system framework and guide the design of the MR-Collabsystem. The technique details of prototype and application scenario of this system are also elaborated in the paper. The system, MR-Collab, is designed in the purpose of facilitating collaboration between distributed users through the Mixed Reality environment. Experimentation that can measure the correlations between the design performance/behaviors with the increased degree of co-presence is also planned in this paper.

title: Solving P2P Traffic Identification Problems Via Optimized Support Vector Machines
abstract: Since the emergence of peer-to-peer (P2P) networking in the last 90s, P2P traffic has become one of the most significant portions of the network traffic. Accurate identification of P2P traffic makes great sense for efficient network management and reasonable utility of network resources. Application level classification of P2P traffic, especially without payload feature detection, is still a challenging problem. This paper proposes a new method for P2P traffic identification and application level classification, which merely uses transport layer information. The method uses support vector machines which have been optimized for performing large learning tasks, rendering that this method become more suitable for large network traffic. The experimental results show that this method achieved high efficiency and is suitable for real-time identification. And carefully tuning the parameters could make the method achieve high accuracy.

title: An efficient GPU-based approach for interactive global illumination
abstract: This paper presents a GPU-based method for interactive global illumination that integrates complex effects such as multi-bounce indirect lighting, glossy reflections, caustics, and arbitrary specular paths. Our method builds upon scattered data sampling and interpolation on the GPU. We start with raytraced shading points and partition them into coherent shading clusters using adaptive seeding followed by k-means. At each cluster center we apply final gather to evaluate its incident irradiance using GPU-based photon mapping. We approximate the entire photon tree as a compact illumination cut, thus reducing the final gather cost for each ray. The sampled irradiance values are then interpolated at all shading points to produce rendering. Our method exploits the spatial coherence of illumination to reduce sampling cost. We sample sparsely and the distribution of sample points conforms with the underlying illumination changes. Therefore our method is both fast and preserves high rendering quality. Although the same property has been exploited by previous caching and adaptive sampling methods, these methods typically require sequential computation of sample points, making them ill-suited for the GPU. In contrast, we select sample points adaptively in a single pass, enabling parallel computation. As a result, our algorithm runs entirely on the GPU, achieving interactive rates for scenes with complex illumination effects.

title: On the Performance of Three Kinds of Channel Code Used in Turbo-BLAST
abstract: A MIMO system named Turbo-BLAST was introduced recently. We investigate the structure of Turbo- BLAST, and study its three kinds structures using different channel codes. Some necessary deductions and new structures are proposed: the decoding algorithm of trellis coded modulation (TCM) is modified to provide the detector with extrinsic information, and a new decoder structure for Turbo code is also given. Simulation results show that the structure using Turbo code can achieve better performance and faster convergence rate for high-order modulation. And the performance improvement of the structure using TCM is also obvious. Since TCM can bring high spectral efficiency, it would be useful to apply TCM in Turbo-BLAST.

title: Precomputed Radiance Transfer Field for Rendering Interreflections in Dynamic Scenes
abstract: In this paper, we introduce a new representation – radiance transfer fields (RTF) – for rendering interreflections in dynamic scenes under low frequency illumination. The RTF describes the radiance transferred by an individual object to its surrounding space as a function of the incident radiance. An important property of RTF is its independence of the scene configuration, enabling interreflection computation in dynamic scenes. Secondly, RTFs naturally fit in with the rendering framework of precomputed shadow fields, incurring negligible cost to add interreflection effects. In addition, RTFs can be used to compute interreflections for both diffuse and glossy objects. We also show that RTF data can be highly compressed by clustered principal component analysis (CPCA), which not only reduces the memory cost but also accelerates rendering. Finally, we present some experimental results demonstrating our techniques.