9480518
Feedback capacity of the first-order moving average Gaussian channel
Despite numerous bounds and partial results, the feedback capacity of the stationary nonwhite Gaussian additive noise channel has been open, even for the simplest cases such as the first-order autoregressive Gaussian channel studied by Butman, Tiernan and Schalkwijk, Wolfowitz, Ozarow, and more recently, Yang, Kavccaronicacute, and Tatikonda. Here we consider another simple special case of the stationary first-order moving average additive Gaussian noise channel and find the feedback capacity in closed form. Specifically, the channel is given by Yi=Xi+Zi, i=1,2,..., where the input {X i} satisfies a power constraint and the noise {Zi} is a first-order moving average Gaussian process defined by Zi=alphaUi-1+Ui, |alpha|les 1, with white Gaussian innovations Ui, i=0,1,.... We show that the feedback capacity of this channel is CFB=-log x0  where x0 is the unique positive root of the equation rhox2=(1-x2)(1-|alpha|x)2 and rho is the ratio of the average input power per transmission to the variance of the noise innovation Ui. The optimal coding scheme parallels the simple linear signaling scheme by Schalkwijk and Kailath for the additive white Gaussian noise channel-the transmitter sends a real-valued information-bearing signal at the beginning of communication and subsequently refines the receiver's knowledge by processing the feedback noise signal through a linear stationary first-order autoregressive filter. The resulting error probability of the maximum likelihood decoding decays doubly exponentially in the duration of the communication. Refreshingly, this feedback capacity of the first-order moving average Gaussian channel is very similar in form to the best known achievable rate for the first-order autoregressive Gaussian noise channel given by Butman
8966837
Channel capacity and state estimation for state-dependent Gaussian channels
We formulate a problem of state information transmission over a state-dependent channel with states known at the transmitter. In particular, we solve a problem of minimizing the mean-squared channel state estimation error E/spl par/S/sup n/ - S/spl circ//sup n//spl par/ for a state-dependent additive Gaussian channel Y/sup n/ = X/sup n/ + S/sup n/ + Z/sup n/ with an independent and identically distributed (i.i.d.) Gaussian state sequence S/sup n/ = (S/sub 1/, ..., S/sub n/) known at the transmitter and an unknown i.i.d. additive Gaussian noise Z/sup n/. We show that a simple technique of direct state amplification (i.e., X/sup n/ = /spl alpha/S/sup n/), where the transmitter uses its entire power budget to amplify the channel state, yields the minimum mean-squared state estimation error. This same channel can also be used to send additional independent information at the expense of a higher channel state estimation error. We characterize the optimal tradeoff between the rate R of the independent information that can be reliably transmitted and the mean-squared state estimation error D. We show that any optimal (R, D) tradeoff pair can be achieved via a simple power-sharing technique, whereby the transmitter power is appropriately allocated between pure information transmission and state amplification.
8818412
A Counterexample to Cover's$2P$Conjecture on Gaussian Feedback Capacity
We provide a counterexample to Cover's conjecture that the feedback capacity CFB of an additive Gaussian noise channel under power constraint P be no greater than the nonfeedback capacity C of the same channel under power constraint 2P, i.e., CFB(P) les C(2P)
2304269
Lightweight logging and recovery for distributed shared memory over virtual interface architecture
As software Distributed Shared Memory(DSM) systems become attractive on larger clusters, the focus of attention moves toward improving the reliability of systems. In this paper, we propose a lightweight logging scheme, called remote logging, and a recovery protocol for home-based DSM. Remote logging stores coherence-related data to the volatile memory of a remote node. The logging overhead can be moderated with high-speed system area network and user-level DMA operations supported by modern communication protocols. Remote logging tolerates multiple failures if the backup nodes of failed nodes are alive. It makes the reliability of DSM grow much higher. Experimental results show that our fault-tolerant DSM has low overhead compared to conventional stable logging and it can be effectively recovered from some concurrent failures.
43170896
MCCA: A high-throughput MAC strategy for next-generation WLANs
Wireless LAN technology has been shown to he a revolutionary development during the last decade. Recently popularized IEEE 802.11a/g-based products can support up to 54 Mb/s physical layer rate and provide wireless access to the Internet. However, in order to deal robustly with the unreliable wireless nature, the 802.11 medium access control protocol has a relatively large overhead and hence, the throughput performance is much worse than the underlying physical layer rate. Moreover, along with many emerging applications and services over WLANs, such as voice over WLAN and audio/video streaming, the demand lor faster and higher- capacity WLANs has been growing recently. In this article, we propose a new medium access control protocol for the next-generation high-speed WLANs. The proposed medium access control, called multi-user polling controlled channel access, is composed of two components: multi-layer frame aggregation, which performs aggregation at both the medium access control and the physical layers; and multi-user polling, used to reduce the contention overhead and in turn, achieve higher network utilization. Multi-user polling controlled channel access is compared with the 802.11e-enhanced distributed channel access medium access control. Highly enhanced medium access control efficiency can be achieved by applying multi-user polling controlled channel access. We show the improved medium access control performance in terms of the aggregate throughput of non-QoS Hows with relevant QoS requirements.
36639292
Lock-Gain Based Graph Partitioning
We propose a new heuristic for the graph partitioning problem. Based on the traditional iterative improvement framework, the heuristic uses a new type of gain in selecting vertices to move between partitions. The new type of gain provides a good explanation for the performance difference of tie-breaking strategies in KL-based iterative improvement graph partitioning algorithms. The new heuristic performed excellently. Theoretical arguments supporting its efficacy are also provided. As the proposed heuristic is considered a good candidate for local optimization engines in metaheuristics, we combined it with a genetic algorithm as a sample case and obtained a surprising result that even the average results over 1,000 runs equalled the best known for most graphs.
2299968
Multi-campaign Assignment Problem and Optimizing Lagrange Multipliers
Customer relationship management is crucial in acquiring and maintaining royal customers. To maximize revenue and customer satisfaction, companies try to provide personalized services for customers. A representative effort is one-to-one marketing. The fast development of Internet and mobile communication boosts up the market of one-to-one marketing. A personalized campaign targets the most attractive customers with respect to the subject of the campaign. So it is important to expect customer preferences for campaigns. Collaborative Filtering (CF) and various data mining techniques are used to expect customer preferences for campaigns. Especially, since CF is fast and simple, it is widely used for personalization in e-commerce. There have been a number of customer-preference estimation methods based on CF. As personalized campaigns are frequently performed, several campaigns often happen to run simultaneously. It is often the case that an attractive customer for a specific campaign tends to be attractive for other campaigns. If we perform separate campaigns without considering this problem, some customers may be bombarded by a considerable number of campaigns. We call this overlapped recommendation problem. The larger the number of recommendations for a customer, the lower the customer interest for campaigns. In the long run, the customer response for campaigns drops. It lowers the marketing efficiency as well as customer satisfaction. Unfortunately, traditional methods only focused on the effectiveness of a single campaign and did not consider the problem with respect to the overlapped recommendations. In this paper, we define the multi-campaign assignment problem (MCAP) considering the overlapped recommendation problem and propose a number of methods for the issue including a genetic approach. We also verify the effectiveness of the proposed methods with field data.
14130132
Signal space detection for recording channels with jitter noise
A delay-constrained sequence detector is considered for recording channels whose major impediments include intersymbol interference (ISI) and magnetic transition jitter noise. The jitter noise is data-dependent, and a given noise sample is correlated with neighboring noise samples. A sequence detector with a finite decision delay can be formulated in a finite dimensional vector space. For a correlated noise channel, the decision boundary is generally quadratic. We present a technique for obtaining a minimal set of hyperplanes approximating a quadratic decision boundary with a negligible performance loss. In this process, a distance measure, which is consistent with the notion of the effective SNR, is defined and used as a design parameter to trade the complexity and performance. As an achievable performance bound, we derive the effective SNR for the maximum-likelihood sequence detector (MLSD) for these channels. The performance of the partial response maximum likelihood (PRML) detector commonly adopted for current data storage channels as well as the Viterbi algorithm (VA) based on the traditional Euclidean metric, which serves as the MLSD for additive white Gaussian noise, are also analyzed and compared with that of the proposed signal space detector.