In this paper, we establish achievable rate regions for the multiple access channel (MAC) with side information partially known (estimated or sensed version) at the transmitters. Actually, we extend the lattice strategies used by Philosof-Zamir for the MAC with full side information at the transmitters to the partially known case. We show that the sensed or estimated side information reduces the rate regions, the same as that occurs for Costa Gaussian channel.Index Terms-achievabile rate region; dirty multiple accsses channel; estimated or sensed or partial side information
A generalisation of the Gaussian doubly dirty multiple access channel to a Gaussian triply dirty multiple access channel (GTD‐MAC) is considered, where there are three additive interference signals, each one non‐causally known to only associated transmitter. Same as in the Gaussian doubly dirty multiple access channel, Costa's strategy (i.e. random binning scheme) cannot achieve positive rates in the limit of strong interferences. In contrast, it is shown that positive rates independent of the interferences can be achieved by lattice strategies. In fact in some cases—which depend on the noise variance and power constraints—lattice strategies are optimal, in particular, in the high signal‐to‐noise ratio (SNR) regime. For the GTD‐MAC, two models are considered, full side information and partial side information at the transmitters. The results show that partiality in side information reduces the achievable rates as numerical illustrations confirm. Also, the results for the GTD‐MAC can be extended to the K‐user case. Copyright © 2013 John Wiley & Sons, Ltd.
In this paper we study the "Z" channel with side information non-causally available at the encoders. We use Marton encoding along with Gelf'and-Pinsker random binning scheme and Chong-Motani-Garg-El Gamal (CMGE) jointly decoding to find an achievable rate region. We will see that our achievable rate region gives the achievable rate of the multiple access channel with side information and also degraded broadcast channel with side information. We will also derive an inner bound and an outer bound on the capacity region of the state-dependent degraded discrete memoryless Z channel and also will observe that our outer bound meets the inner bound for the rates corresponding to the second transmitter. Also, by assuming the high signal to noise ratio and strong interference regime, and using the lattice strategies, we derive an achievable rate region for the Gaussian degraded Z channel with additive interference non-causally available at both of the encoders. Our method is based on lattice transmission scheme, jointly decoding at the first decoder and successive decoding at the second decoder. Using such coding scheme we remove the effect of the interference completely. I. INTRODUCTIONThe Z channel is a two-transmitter two-receiver model shown in Fig. 1 where the first sender only wishes to send information to the first receiver whereas the second transmitter sends information to both of the receivers. The Z channel was first studied by Viswanath et al [1] where they introduced the model and found the capacity region of a specialclass of Z channels and the achievable rate of a special case of the Gaussian Z channel (GZC). In [2], Liu and Ulukus obtained several capacity bounds for a class of GZC. Chong-Motani-Garg (CMGE) [3] studied three different types of degraded Z channel and characterized the capacity region in one type. They also characterized the capacity region of GZC with moderately strong crossover link.The capacity region of the general Z channel is still an open problem. The best achievable rate region for the discrete memoryless Z channel until today is due to Do et al [4].Channels with side information were first studied by Shannon [5] where he characterized the capacity of a point-to-point channel with side information causally available at the transmitters. Gelf 'and and Pinsker [6] found the capacity of a single-user channel with side information non-causally available at the encoders. State-dependent multiuser settings have been studied in [7], [8], [9], [10], and [11].In this paper we study the Z channel with channel state information non-causally available at the encoders that is depicted in Fig. 2. The reason to study this channel model is buttressed by the applications it has in some wireless communication scenarios such as the case where two communication-involved cells are interfering with each other and thus suffer from a common interference modeled by some S non-causally available to two distinct destination base stations as shown in Fig. As in Fig. 2
In this study, the authors study a two-user Gaussian doubly dirty compound multiple-access channel with partial side information (GDD-CMAC-PSI) where two independent additive interference signals are considered, each one known noncausally and partially to one of the encoders but unknown to either of the receivers. This channel, first, can model two users communicating with two base stations suffering from interference, and second, includes many previously studied channels as its special cases. For such a communication scenario, first, a general capacity outer bound is derived. Depending on the values of cross link gains, they classify the channel into three classes: weak, strong and mixed GDD-CMAC-PSI. Next, assuming that the interference signals have infinite variances, they obtain capacity outer bounds for these classes. Then, an achievable sum-rate is derived for the GDD-CMAC-PSI using Costa's strategy and thereby, they show that when both interference signals have infinite variances, this achievable sum-rate vanishes. Later, by utilising the lattice strategies and deriving achievable rate regions, independent of the interference powers, they show that in contrast with Costa's strategy, lattice-strategies can achieve positive rates. Finally, depending on signal-to-noise ratio gaps at receivers, various achievable rates are obtained.
Today, with the emergence of data mining technology and access to useful data, valuable information in different areas can be explored. Data mining uses machine learning algorithms to extract useful relationships and knowledge from a large amount of data and offers an automatic tool for various predictions and classifications. One of the most common applications of data mining in medicine and health-care is to predict different types of breast cancer which has attracted the attention of many scientists. In this paper, a hybrid model employing three algorithms of Naive Bayes Network, RBF Network, and K-means clustering is presented to predict breast cancer type. In the proposed model, the voting approach is used to combine the results obtained from the above three algorithms. Dataset used in this study is called Breast Cancer Wisconsin taken from data sources of UCI. The proposed model is implemented in MATLAB and its efficiency in predicting breast cancer type is evaluated on Breast Cancer Wisconsin dataset. Results show that the proposed hybrid model achieves an accuracy of 99% and mean absolute error of 0.019 which is superior over other models.
In this paper, a simple and novel routing algorithm is presented to improve the packet delivery in harsh conditions such as selective forwarding and blackhole attacks to the wireless sensor networks. The proposed algorithm is based on restricted multi-path broadcast based on a virtual cylinder from the source node to the sink node. In this algorithm, when a packet is broadcast by a source node, a virtual cylinder with radius w is created from the source node to a sink node. All the nodes located in this virtual cylinder are allowed to forwardthe packet to the sink. Thus, data is forwarded to sink via multiple paths, but in a restricted manner so that the nodes do not consume a high amount of energy. If there are some compromised nodes in this virtual cylinder, the packets may be forwarded to the sink via other nodes of the virtual cylinder. The proposed algorithm is simulated and evaluated in terms of packet delivery rate and energy consumption. The experiment results show that the proposed algorithm increases packet delivery rate 7 times compared to the single-path routing method and reduces energy consumption up to three times compared to flooding routing method.
Introduction:The province of Kohgiluyeh and Boyer-Ahmad in southwestern Iran is an important rice-growing area. Seed-borne fungi can cause harmful diseases, so identifying them is important to prevent these diseases. Materials and Methods: Thirty seed samples of four rice varieties were collected from different regions of the province. Seed-borne fungi were isolated by using the potato-dextrose-agar plate, blotter, and deep freezing blotter methods and after purification, their morphological characteristics were studied and they were identified. The total frequency of seeds infected with fungi and the frequency of seeds infected with each fungus were calculated. The effect of these fungi on seed germination and root growth of four cultivars Champa, Shamim, Gerdeh, and Lenjan was tested by placing them between wet sterile filter papers. Results: Twenty-eight fungi of 11 genera vs. Alternaria, Aspergillus, Bipolaris, Cladosporium, Curvularia, Epicoccum, Fusarium, Penicillium, Pyrenophora, Rhizopus, and Ulocladium were identified in these thirty samples. These fungi did not significantly affect seed germination of these varieties, but caused root rot in them. The average infestation of the Champa variety was lower than the others. Conclusion: The Champa variety is relatively resistant to these fungi, followed by Shamim, Lenjan, and Gerdeh respectively.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.