Using Grouped Linear Prediction and Accelerated Reinforcement Learning for Online Content Caching

Proactive caching is an effective way to alleviate peak-hour traffic congestion by prefetching popular contents at the wireless network edge. To maximize the caching efficiency requires the knowledge of content popularity profile, which however is often unavailable in advance. In this paper, we first propose a new linear prediction model, named grouped linear model (GLM) to estimate the future content requests based on historical data. Unlike many existing works that assumed the static content popularity profile, our model can adapt to the temporal variation of the content popularity in practical systems due to the arrival of new contents and dynamics of user preference. Based on the predicted content requests, we then propose a reinforcement learning approach with model-free acceleration (RLMA) for online cache replacement by taking into account both the cache hits and replacement cost. This approach accelerates the learning process in non-stationary environment by generating imaginary samples for Q-value updates. Numerical results based on real-world traces show that the proposed prediction and learning based online caching policy outperform all considered existing schemes.Comment: 6 pages, 4 figures, ICC 2018 worksho

A New SLNR-based Linear Precoding for Downlink Multi-User Multi-Stream MIMO Systems

Signal-to-leakage-and-noise ratio (SLNR) is a promising criterion for linear precoder design in multi-user (MU) multiple-input multiple-output (MIMO) systems. It decouples the precoder design problem and makes closed-form solution available. In this letter, we present a new linear precoding scheme by slightly relaxing the SLNR maximization for MU-MIMO systems with multiple data streams per user. The precoding matrices are obtained by a general form of simultaneous diagonalization of two Hermitian matrices. The new scheme reduces the gap between the per-stream effective channel gains, an inherent limitation in the original SLNR precoding scheme. Simulation results demonstrate that the proposed precoding achieves considerable gains in error performance over the original one for multi-stream transmission while maintaining almost the same achievable sum-rate.Comment: 8 pages, 1 figur

Resource Allocation for Delay Differentiated Traffic in Multiuser OFDM Systems

Most existing work on adaptive allocation of subcarriers and power in multiuser orthogonal frequency division multiplexing (OFDM) systems has focused on homogeneous traffic consisting solely of either delay-constrained data (guaranteed service) or non-delay-constrained data (best-effort service). In this paper, we investigate the resource allocation problem in a heterogeneous multiuser OFDM system with both delay-constrained (DC) and non-delay-constrained (NDC) traffic. The objective is to maximize the sum-rate of all the users with NDC traffic while maintaining guaranteed rates for the users with DC traffic under a total transmit power constraint. Through our analysis we show that the optimal power allocation over subcarriers follows a multi-level water-filling principle; moreover, the valid candidates competing for each subcarrier include only one NDC user but all DC users. By converting this combinatorial problem with exponential complexity into a convex problem or showing that it can be solved in the dual domain, efficient iterative algorithms are proposed to find the optimal solutions. To further reduce the computational cost, a low-complexity suboptimal algorithm is also developed. Numerical studies are conducted to evaluate the performance the proposed algorithms in terms of service outage probability, achievable transmission rate pairs for DC and NDC traffic, and multiuser diversity.Comment: 29 pages, 8 figures, submitted to IEEE Transactions on Wireless Communication

Stimulatory effect of gonadal hormones on fetal rat hippocampal neural proliferation requires neurotrophin receptor activation in vitro

AbstractTo determine the effects of gonadal hormones on proliferation of the hippocampal neural cells, which are of importance in learning and memory function. 17β-Estradiol or testosterone was added to the culture at various concentrations. Their proliferation and protective effects on the neural cell were determined with BrdU, flow cytometry and MTT assay. Effects of the gonadal hormones on brain-derived neurotrophic factor (BDNF) expression were determined using ELISA and RT-PCR respectively. 17β-Estradiol and testosterone at 20nM or higher concentrations significantly increased the neural cell proliferation and viability, and induced increasing in the S phase arrest which is essential for cell proliferation. Both estradiol and testosterone significantly increased the neural cell expression of cellular mature BDNF and BDNF mRNA. Effect of testosterone on hippocampal neural proliferation was blocked by Trk neurotrophin receptor inhibitor. 17β-Estradiol and testosterone promoted hippocampal neural proliferation and improved cell viability in vitro. The effect of testosterone on hippocampal neural cell proliferation required neurotrophin receptor activation

All Nash Equilibria of the Multi-Unit Vickrey Auction

This paper completely characterizes the set of Nash equilibria of the Vickrey auction for multiple identical units when buyers have non-increasing marginal valuations and there at least three potential buyers. There are two types of equilibria: In the first class of equilibria there are positive bids below the maximum valuation. In this class, above a threshold value all bidders bid truthfully on all units. One of the bidders bids at the threshold for any unit for which his valuation is below the threshold; the other bidders bid zero in this range. In the second class of equilibria there are as many bids at or above the maximum valuation as there are units. The allocation of these bids is arbitrary across bidders. All the remaining bids equal zero. With any positive reserve price equilibrium becomes unique: Bidders bid truthfully on all units for which their valuation exceeds the reserve price