Topic
Codebook
About: Codebook is a research topic. Over the lifetime, 8492 publications have been published within this topic receiving 115995 citations.
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TL;DR: This paper proposes an approach to extract robust and discriminative facial features and use soft encoding, which achieves an absolute(relative) improvement of 3.6%(6.5%) over the best reported results [Shan, 2010].
46 citations
01 Jan 2004
TL;DR: This paper derives capacity expressions for perfectly-secure steganographic systems by exploiting the fact that the warden may be passive, or active using a memoryless attack channel, oractive using an arbitrarily varying channel.
Abstract: This paper extends recent results on steganographic capacity. We derive capacity expressions for perfectly-secure steganographic systems. The warden may be passive, or active using a memoryless attack channel, or active using an arbitrarily varying channel. Neither encoder nor decoder know which channel was selected by the warden. In some cases, the steganographic constraint does not result in any capacity loss. To achieve steganographic capacity, encoder and decoder generally need to share a secret codebook.
46 citations
TL;DR: This paper designs precoders for two users with two transmit antennas and one receiver with two receive antennas using quantized feedback and proposes to construct codebook using Grassmannian line packing, and analytically proves that the system can achieve full diversity for each user.
Abstract: When two users transmit signals to a common receiver, one can design precoders to cancel the interference for each user, if each user knows all the channel information perfectly. Also the diversity for each user is full. However, in practice, perfect channel information is not available. In this paper, we design precoders for two users with two transmit antennas and one receiver with two receive antennas using quantized feedback. We propose to construct codebook using Grassmannian line packing. By choosing precoders from the codebook properly, our proposed scheme can cancel the interference for each user. Also we analytically prove that our system can achieve full diversity for each user. Then we extend our scheme to any number of transmit and receive antennas. Simulation results confirm our analytical proof and show that our scheme can serve as a bridge between a system with no feedback and a system with perfect feedback.
46 citations
22 May 2016
TL;DR: A novel swap-matching algorithm is proposed in which the users and the subcarriers are considered as two sets of players, and every two users can cooperate to swap their matches so as to improve each other's profits.
Abstract: In this paper, we study the codebook-based resource allocation problem for an uplink sparse code multiple access (SCMA) network. The base station (BS) assigns to each user a set of subcarriers corresponding to a specific codebook, and each user performs power control over multiple subcarriers. We aim to optimize the subcarrier assignment and power allocation to maximize the total sum-rate. To solve the above problem, we formulate it as a many-to-many two-sided matching problem with externalities. A novel swap-matching algorithm is then proposed in which the users and the subcarriers are considered as two sets of players, and every two users can cooperate to swap their matches so as to improve each other's profits. The algorithm converges to a pair-wise stable matching after a limited number of iterations. Simulation results show that the proposed algorithm greatly outperforms the orthogonal multiple access scheme and a random allocation scheme.
46 citations
TL;DR: This paper develops decoding and encoding mechanisms by engaging the theory of possibility and fuzzy relational calculus and shows that the decoded information granule is either a granular interval or interval-valued fuzzy set.
Abstract: Information granules are generic building blocks supporting the processing realized in granular computing and facilitating communication with the environment. In this paper, we are concerned with a fundamental problem of encoding–decoding of information granules. The essence of the problem is outlined as follows: given a finite collection of granular data X 1, X 2,…, XN (sets, fuzzy sets, etc.), construct an optimal codebook composed of information granules A 1 , A2 , …, Ac , where typically c N, so that any Xk represented in terms of A i 's and then decoded (reconstructed) with the help of this codebook leads to the lowest decoding error. A fundamental result is established, which states that in the proposed encoders and decoders, when encoding–decoding error is present, the information granule coming as a result of decoding is of a higher type than the original information granules (say, if Xk is information granule of type-1, then its decoded version becomes information granule of type-2). It would be beneficial to note that as the encoding–decoding process is not lossless (in general, with an exception of a few special cases), the lossy nature of the method is emphasized by the emergence of information granules of higher type (in comparison with the original data being processed). For instance, when realizing encoding–decoding of numeric data (viz., information granules of type-0), the losses occur and they are quantified in terms of intervals, fuzzy sets, probabilities, rough sets, etc., where, in fact, the result becomes an information granule of type-1. In light of the nature of the constructed result when Xk is an interval or a fuzzy set, an optimized performance index engages a distance between the bounds of the interval-valued membership function. We develop decoding and encoding mechanisms by engaging the theory of possibility and fuzzy relational calculus and show that the decoded information granule is either a granular interval or interval-valued fuzzy set. The optimization mechanism is realized with the aid of the particle swarm optimization (PSO). A series of experiments are reported with intent to illustrate the details of the encoding–decoding mechanisms and show that the PSO algorithm can efficiently optimize the granular codebook.
46 citations