The dining cryptographers protocol implements a multiple access channel in whichsenders and recipients are anonymous. A problem is that a malicious participant can disrupt commu-nication by deliberately creating collisions. We propose a computationally secure dining cryptogra-phers protocol with collision resolution that achieves a maximum stable throughput of 0.924 messagesper round and which allows to easily detect disruptors.
Superposed receiving @cite_9 @cite_8 is a collision resolution technique for the dining cryptographers protocol that achieves throughput of 100 an additive group. When a collision occurs, the average of the messages values is computed and only messages whose value is less than this average are retransmitted. Like in SICTA, inference cancellation is used, which leads to the $100 the use of an additive finite group and it cannot be implemented using the algebraic ciphertexts that we need for efficient ciphertexts generation and for zero-knowledge proofs.
@cite_9 @cite_8
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This paper introduces a novel technique for access by a cognitive Secondary User (SU) to a spectrum with an incumbent Primary User (PU), which uses Type-I Hybrid ARQ. The technique allows the SU to perform selective retransmissions of previously corrupted SU data packets. The temporal redundancy introduced by the primary ARQ protocol and by the selective SU retransmission process can be exploited by the SU receiver to perform Interference Cancellation (IC) over the entire interference pattern, thus creating a "clean" channel for the decoding of the concurrent message. The chain decoding technique, initiated by a successful decoding operation of a SU or PU message, consists in the iterative application of IC, as previously corrupted messages become decodable. Based on this scheme, we design an optimal policy that maximizes the SU throughput under a constraint on the average long-term PU throughput degradation. We show that the optimal policy can be found by first optimizing the SU access policy using a Markov Decision Process formulation, and then applying a chain decoding protocol defined by five basic rules. Such an approach enables a compact state representation of the protocol, and its efficient numerical optimization. Finally, we show by numerical results the throughput benefit of the proposed technique. Motivated by a problem of transmitting supplemental data over broadcast channels (Birk and Kol, INFOCOM 1998), we study the following coding problem: a sender communicates with n receivers R1,..., Rn. He holds an input x ∈ 0,01l n and wishes to broadcast a single message so that each receiver Ri can recover the bit xi. Each Ri has prior side information about x, induced by a directed graph Grain nodes; Ri knows the bits of a; in the positions j | (i,j) is an edge of G .G is known to the sender and to the receivers. We call encoding schemes that achieve this goal INDEXcodes for 0,1 n with side information graph G. In this paper we identify a measure on graphs, the minrank, which exactly characterizes the minimum length of linear and certain types of nonlinear INDEX codes. We show that for natural classes of side information graphs, including directed acyclic graphs, perfect graphs, odd holes, and odd anti-holes, minrank is the optimal length of arbitrary INDEX codes. For arbitrary INDEX codes and arbitrary graphs, we obtain a lower bound in terms of the size of the maximum acyclic induced subgraph. This bound holds even for randomized codes, but has been shown not to be tight. Motivated by cognitive radio applications, we consider mitigating the effect of interference by exploiting known properties about its signal structure. Specifically, we analyze communication between a source and destination with an interferer that induces random variations in the source-destination channel. The interferer transmits a sequence chosen uniformly from a randomly generated codebook, which has an i.i.d. structure, or a superposition structure. It is assumed that both the encoder and decoder know the interferer's codebook. We first provide a definition of capacity for these settings. When the encoder knows the interferer's message noncausally, it can use Gel'fand-Pinsker (GP) encoding to precode against interference. Alternatively, it can encode by taking into account that the interference is a codeword, to enable the decoder to decode both messages. It is demonstrated by an example that the latter can outperform GP encoding. Two upper bounds to the performance of this channel are then presented. Next, a more realistic scenario is considered in which the interference is learned at the cognitive encoder causally through a noisy channel. It is shown that for the case of i.i.d. generated interference, this information has no value. In contrast, when the interference is a codeword from an i.i.d. generated codebook, this fact can be exploited to obtain higher rates between the cognitive pair. Techniques to process a number of “received” symbol streams in a Multiple-Input Multiple-Output (MIMO) system with multipath channels such that improved performance may be achieved when using successive interference cancellation (SIC) processing. In an aspect, metrics indicative of the quality or “goodness” of a “detected” symbol stream are provided. These metrics consider the frequency selective response of the multipath channels used to transmit the symbol stream. For example, the metrics may relate to (1) an overall channel capacity for all transmission channels used for the symbol stream, or (2) an equivalent signal-to-interference noise ratio (SNR) of an Additive White Gaussian Noise (AWGN) channel modeling these transmission channels. In another aspect, techniques are provided to process the received symbol streams, using SIC processing, to recover a number of transmitted symbol streams. The particular order in which the symbol streams are recovered is determined based on the metrics determined for symbol streams detected at each SIC processing stage.