Coherence Optimization and Best Complex Antipodal Spherical Codes

Vector sets with optimal coherence according to the Welch bound cannot exist for all pairs of dimension and cardinality. If such an optimal vector set exists, it is an equiangular tight frame and represents the solution to a Grassmannian line packing problem. Best Complex Antipodal Spherical Codes (BCASCs) are the best vector sets with respect to the coherence. By extending methods used to find best spherical codes in the real-valued Euclidean space, the proposed approach aims to find BCASCs, and thereby, a complex-valued vector set with minimal coherence. There are many applications demanding vector sets with low coherence. Examples are not limited to several techniques in wireless communication or to the field of compressed sensing. Within this contribution, existing analytical and numerical approaches for coherence optimization of complex-valued vector spaces are summarized and compared to the proposed approach. The numerically obtained coherence values improve previously reported results. The drawback of increased computational effort is addressed and a faster approximation is proposed which may be an alternative for time critical cases

Gleichstellungs-News : Nr. 14

Many embedded systems with real-time requirements demand minimal jitter and low communication end-to-end latency for its communication networks. The time-triggered paradigm, adopted by many real-time protocols, was designed to cope with these demands. A cost-efficient way to implement this paradigm is to synthesize a static schedule that indicates the transmission times of all the time-triggered frames such that all requirements are met. Synthesizing this schedule can be seen as a bin-packing problem, known to be NPcomplete, with complexity driven by the number of frames. In the last years, requirements on the amount of data being transmitted and the scalability of the network have increased. A solution was proposed, adapting real-time switched Ethernet to benefit from its high bandwidth. However, it added more complexity in computing the schedule, since every frame is distributed over multiple links. Tools like Satisfiability Modulo Theory solvers were able to cope with the added complexity and synthesize schedules of industrial size networks. Despite the success of such tools, applications are appearing requiring embedded systems with even more complex networks. In the future, real-time embedded systems, such as large factory automation or smart cities, will need extremely large hybrid networks, combining wired and wireless communication, with schedules that cannot be synthesized with current tools in a reasonable amount of time. With this in mind, the first thesis goal is to identify the performance limits of Satisfiability Modulo Theory solvers in schedule synthesis. Given these limitations, the next step is to define and develop a divide and conquer approach for decomposing the entire scheduling problem in smaller and easy solvable subproblems. However, there are constraints that relate frames from different subproblems. These constraints need to be treated differently and taken into account at the start of every subproblem. The third thesis goal is to develop an approach that is able to synthesize schedules when different frame constraints related to different subproblems are inter-dependent. Last, is to define the requirements that the integration of wireless communication in hybrid networks will bring to the schedule synthesis and how to cope with the increased complexity. We demonstrate the viability of our approaches by means of evaluations, showing that our method is capable to synthesize schedules of hundred of thousands of frames in less than 5 hours.RetNe

VIRTUALIZED BASEBAND UNITS CONSOLIDATION IN ADVANCED LTE NETWORKS USING MOBILITY- AND POWER-AWARE ALGORITHMS

Virtualization of baseband units in Advanced Long-Term Evolution networks and a rapid performance growth of general purpose processors naturally raise the interest in resource multiplexing. The concept of resource sharing and management between virtualized instances is not new and extensively used in data centers. We adopt some of the resource management techniques to organize virtualized baseband units on a pool of hosts and investigate the behavior of the system in order to identify features which are particularly relevant to mobile environment. Subsequently, we introduce our own resource management algorithm specifically targeted to address some of the peculiarities identified by experimental results

Self-concatenated coding and multi-functional MIMO aided H.264 video telephony

Abstract— Robust video transmission using iteratively detected Self-Concatenated Coding (SCC), multi-dimensional Sphere Packing (SP) modulation and Layered Steered Space-Time Coding (LSSTC) is proposed for H.264 coded video transmission over correlated Rayleigh fading channels. The self-concatenated convolutional coding (SECCC) scheme is composed of a Recursive Systematic Convolutional (RSC) code and an interleaver, which is used to randomise the extrinsic information exchanged between the self-concatenated constituent RSC codes. Additionally, a puncturer is employed for improving the achievable bandwidth efficiency. The convergence behaviour of the MIMO transceiver advocated is investigated with the aid of Extrinsic Information Transfer (EXIT) charts. The proposed system exhibits an Eb /N0 gain of about 9 dB at the PSNR degradation point of 1 dB in comparison to the identical-rate benchmarker scheme

High-Efficient Parallel CAVLC Encoders on Heterogeneous Multicore Architectures

This article presents two high-efficient parallel realizations of the context-based adaptive variable length coding (CAVLC) based on heterogeneous multicore processors. By optimizing the architecture of the CAVLC encoder, three kinds of dependences are eliminated or weaken, including the context-based data dependence, the memory accessing dependence and the control dependence. The CAVLC pipeline is divided into three stages: two scans, coding, and lag packing, and be implemented on two typical heterogeneous multicore architectures. One is a block-based SIMD parallel CAVLC encoder on multicore stream processor STORM. The other is a component-oriented SIMT parallel encoder on massively parallel architecture GPU. Both of them exploited rich data-level parallelism. Experiments results show that compared with the CPU version, more than 70 times of speedup can be obtained for STORM and over 50 times for GPU. The implementation of encoder on STORM can make a real-time processing for 1080p @30fps and GPU-based version can satisfy the requirements for 720p real-time encoding. The throughput of the presented CAVLC encoders is more than 10 times higher than that of published software encoders on DSP and multicore platforms

Grassmannian Frames with Applications to Coding and Communication

For a given class ${\cal F}$ of uniform frames of fixed redundancy we define a Grassmannian frame as one that minimizes the maximal correlation $|< f_k,f_l >|$ among all frames $\{f_k\}_{k \in {\cal I}} \in {\cal F}$. We first analyze finite-dimensional Grassmannian frames. Using links to packings in Grassmannian spaces and antipodal spherical codes we derive bounds on the minimal achievable correlation for Grassmannian frames. These bounds yield a simple condition under which Grassmannian frames coincide with uniform tight frames. We exploit connections to graph theory, equiangular line sets, and coding theory in order to derive explicit constructions of Grassmannian frames. Our findings extend recent results on uniform tight frames. We then introduce infinite-dimensional Grassmannian frames and analyze their connection to uniform tight frames for frames which are generated by group-like unitary systems. We derive an example of a Grassmannian Gabor frame by using connections to sphere packing theory. Finally we discuss the application of Grassmannian frames to wireless communication and to multiple description coding.Comment: Submitted in June 2002 to Appl. Comp. Harm. Ana

Optimal Distributed Scheduling in Wireless Networks under the SINR interference model

Radio resource sharing mechanisms are key to ensuring good performance in wireless networks. In their seminal paper \cite{tassiulas1}, Tassiulas and Ephremides introduced the Maximum Weighted Scheduling algorithm, and proved its throughput-optimality. Since then, there have been extensive research efforts to devise distributed implementations of this algorithm. Recently, distributed adaptive CSMA scheduling schemes \cite{jiang08} have been proposed and shown to be optimal, without the need of message passing among transmitters. However their analysis relies on the assumption that interference can be accurately modelled by a simple interference graph. In this paper, we consider the more realistic and challenging SINR interference model. We present {\it the first distributed scheduling algorithms that (i) are optimal under the SINR interference model, and (ii) that do not require any message passing}. They are based on a combination of a simple and efficient power allocation strategy referred to as {\it Power Packing} and randomization techniques. We first devise algorithms that are rate-optimal in the sense that they perform as well as the best centralized scheduling schemes in scenarios where each transmitter is aware of the rate at which it should send packets to the corresponding receiver. We then extend these algorithms so that they reach throughput-optimality