We consider a multiuser multiple-input multiple- output (MIMO) Gaussian broadcast channel (BC), where the transmitter and receivers have multiple antennas. Since the MIMO BC is in general a nondegraded BC, its capacity region remains an unsolved problem. We establish a duality between what is termed the "dirty paper" achievable region (the Caire-Shamai (see Proc. IEEE Int. Symp. Information Theory, Washington, DC, June 2001, p.322) achievable region) for the MIMO BC and the capacity region of the MIMO multiple-access channel (MAC), which is easy to compute. Using this duality, we greatly reduce the computational complexity required for obtaining the dirty paper achievable region for the MIMO BC. We also show that the dirty paper achievable region achieves the sum-rate capacity of the MIMO BC by establishing that the maximum sum rate of this region equals an upper bound on the sum rate of the MIMO BC.
Cognitive radio promises a low-cost, highly flexible alternative to the classic single-frequency band, single-protocol wireless device. By sensing and adapting to its environment, such a device is able to fill voids in the wireless spectrum and can dramatically increase spectral efficiency. In this paper, the cognitive radio channel is defined as a two-sender, two-receiver interference channel in which sender 2 obtains the encoded message sender 1 plans to transmit. We consider two cases: in the genie-aided cognitive radio channel, sender 2 is noncausally presented the data to be transmitted by sender 1 while in the causal cognitive radio channel, the data is obtained causally. The cognitive radio at sender 2 may then choose to transmit simultaneously over the same channel, as opposed to waiting for an idle channel as is traditional for a cognitive radio. Our main result is the development of an achievable region which combines Gel'fand-Pinkser coding with an achievable region construction for the interference channel. In the additive Gaussian noise case, this resembles dirty-paper coding, a technique used in the computation of the capacity of the Gaussian multiple-input multiple-output (MIMO) broadcast channel. Numerical evaluation of the region in the Gaussian noise case is performed, and compared to an inner bound, the interference channel, and an outer bound, a modified Gaussian MIMO broadcast channel. Results are also extended to the case in which the message is causally obtained.
A Gaussian broadcast channel (GBC) with r single-antenna receivers and t antennas at the transmitter is considered. Both transmitter and receivers have perfect knowledge of the channel. Despite its apparent simplicity, this model is, in general, a nondegraded broadcast channel (BC), for which the capacity region is not fully known. For the two-user case, we find a special case of Marton's (1979) region that achieves optimal sum-rate (throughput). In brief, the transmitter decomposes the channel into two interference channels, where interference is caused by the other user signal. Users are successively encoded, such that encoding of the second user is based on the noncausal knowledge of the interference caused by the first user. The crosstalk parameters are optimized such that the overall throughput is maximum and, surprisingly, this is shown to be optimal over all possible strategies (not only with respect to Marton's achievable region). For the case of r>2 users, we find a somewhat simpler choice of Marton's region based on ordering and successively encoding the users. For each user i in the given ordering, the interference caused by users j>i is eliminated by zero forcing at the transmitter, while interference caused by users j<i is taken into account by coding for noncausally known interference. Under certain mild conditions, this scheme is found to be throughput-wise asymptotically optimal for both high and low signal-to-noise ratio (SNR). We conclude by providing some numerical results for the ergodic throughput of the simplified zero-forcing scheme in independent Rayleigh fading.
A new achievable rate region for the general interference channel which extends previous results is presented and evaluated. The technique used is a generalization of superposition coding to the multivariable case. A detailed computation for the Gaussian channel case clarifies to what extent the new region improves previous ones. The capacity of a class of Gaussian interference channels is also established.
We propose novel cooperative transmission protocols for delay-limited coherent fading channels consisting of N (half-duplex and single-antenna) partners and one cell site. In our work, we differentiate between the relay, cooperative broadcast (down-link), and cooperative multiple-access (CMA) (up-link) channels. The proposed protocols are evaluated using Zheng-Tse diversity-multiplexing tradeoff. For the relay channel, we investigate two classes of cooperation schemes; namely, amplify and forward (AF) protocols and decode and forward (DF) protocols. For the first class, we establish an upper bound on the achievable diversity-multiplexing tradeoff with a single relay. We then construct a new AF protocol that achieves this upper bound. The proposed algorithm is then extended to the general case with (N-1) relays where it is shown to outperform the space-time coded protocol of Laneman and Wornell without requiring decoding/encoding at the relays. For the class of DF protocols, we develop a dynamic decode and forward (DDF) protocol that achieves the optimal tradeoff for multiplexing gains 0lesrles1/N. Furthermore, with a single relay, the DDF protocol is shown to dominate the class of AF protocols for all multiplexing gains. The superiority of the DDF protocol is shown to be more significant in the cooperative broadcast channel. The situation is reversed in the CMA channel where we propose a new AF protocol that achieves the optimal tradeoff for all multiplexing gains. A distinguishing feature of the proposed protocols in the three scenarios is that they do not rely on orthogonal subspaces, allowing for a more efficient use of resources. In fact, using our results one can argue that the suboptimality of previously proposed protocols stems from their use of orthogonal subspaces rather than the half-duplex constraint.
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In this work we investigate the effect of the convolutional network depth on its accuracy in the large-scale image recognition setting. Our main contribution is a thorough evaluation of networks of increasing depth using an architecture with very small (3x3) convolution filters, which shows that a significant improvement on the prior-art configurations can be achieved by pushing the depth to 16-19 weight layers. These findings were the basis of our ImageNet Challenge 2014 submission, where our team secured the first and the second places in the localisation and classification tracks respectively. We also show that our representations generalise well to other datasets, where they achieve state-of-the-art results. We have made our two best-performing ConvNet models publicly available to facilitate further research on the use of deep visual representations in computer vision.
<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> A method is proposed, called channel polarization, to construct code sequences that achieve the symmetric capacity <emphasis emphasistype="italic"><formula formulatype="inline"><tex Notation="TeX">$I(W)$</tex></formula></emphasis> of any given binary-input discrete memoryless channel (B-DMC) <emphasis emphasistype="italic"><formula formulatype="inline"><tex Notation="TeX">$W$</tex></formula></emphasis>. The symmetric capacity is the highest rate achievable subject to using the input letters of the channel with equal probability. Channel polarization refers to the fact that it is possible to synthesize, out of <emphasis emphasistype="italic"><formula formulatype="inline"><tex Notation="TeX">$N$</tex></formula></emphasis> independent copies of a given B-DMC <emphasis emphasistype="italic"><formula formulatype="inline"> <tex Notation="TeX">$W$</tex></formula></emphasis>, a second set of <emphasis emphasistype="italic"><formula formulatype="inline"><tex Notation="TeX">$N$</tex> </formula></emphasis> binary-input channels <emphasis emphasistype="italic"><formula formulatype="inline"><tex Notation="TeX">$\{W_N^{(i)}:1\le i\le N\}$</tex> </formula></emphasis> such that, as <emphasis emphasistype="italic"><formula formulatype="inline"><tex Notation="TeX">$N$</tex></formula></emphasis> becomes large, the fraction of indices <emphasis emphasistype="italic"><formula formulatype="inline"> <tex Notation="TeX">$i$</tex></formula></emphasis> for which <emphasis emphasistype="italic"><formula formulatype="inline"><tex Notation="TeX">$I(W_N^{(i)})$</tex></formula></emphasis> is near <emphasis emphasistype="italic"><formula formulatype="inline"><tex Notation="TeX">$1$</tex> </formula></emphasis> approaches <emphasis emphasistype="italic"><formula formulatype="inline"><tex Notation="TeX">$I(W)$</tex></formula></emphasis> and the fraction for which <emphasis emphasistype="italic"><formula formulatype="inline"> <tex Notation="TeX">$I(W_N^{(i)})$</tex></formula></emphasis> is near <emphasis emphasistype="italic"><formula formulatype="inline"><tex Notation="TeX">$0$</tex> </formula></emphasis> approaches <emphasis emphasistype="italic"><formula formulatype="inline"><tex Notation="TeX">$1-I(W)$</tex></formula></emphasis>. The polarized channels <emphasis emphasistype="italic"><formula formulatype="inline"> <tex Notation="TeX">$\{W_N^{(i)}\}$</tex></formula></emphasis> are well-conditioned for channel coding: one need only send data at rate <emphasis emphasistype="italic"><formula formulatype="inline"><tex Notation="TeX">$1$</tex></formula></emphasis> through those with capacity near <emphasis emphasistype="italic"><formula formulatype="inline"> <tex Notation="TeX">$1$</tex></formula></emphasis> and at rate <emphasis emphasistype="italic"><formula formulatype="inline"><tex Notation="TeX">$0$</tex></formula></emphasis> through the remaining. Codes constructed on the basis of this idea are called polar codes. The paper proves that, given any B-DMC <emphasis emphasistype="italic"><formula formulatype="inline"><tex Notation="TeX">$W$</tex></formula></emphasis> with <emphasis emphasistype="italic"><formula formulatype="inline"><tex Notation="TeX">$I(W)> 0$</tex></formula></emphasis> and any target rate <emphasis emphasistype="italic"><formula formulatype="inline"><tex Notation="TeX">$R ≪ I(W)$</tex></formula></emphasis>, there exists a sequence of polar codes <emphasis emphasistype="italic"><formula formulatype="inline"><tex Notation="TeX">$\{{\Fraktur {C}}_n;n\ge 1\}$</tex> </formula></emphasis> such that <emphasis emphasistype="italic"><formula formulatype="inline"> <tex Notation="TeX">${\Fraktur {C}}_n$</tex></formula></emphasis> has block-length <emphasis emphasistype="italic"><formula formulatype="inline"><tex Notation="TeX">$N=2^n$</tex> </formula></emphasis>, rate <emphasis emphasistype="italic"><formula formulatype="inline"> <tex Notation="TeX">$\ge R$</tex></formula></emphasis>, and probability of block error under successive cancellation decoding bounded as <emphasis emphasistype="italic"><formula formulatype="inline"><tex Notation="TeX">$P_{e}(N,R) \le O(N^{-{1\over 4}})$</tex> </formula></emphasis> independently of the code rate. This performance is achievable by encoders and decoders with complexity <emphasis emphasistype="italic"><formula formulatype="inline"><tex Notation="TeX">$O(N\log N)$</tex></formula></emphasis> for each. </para>
We trained a large, deep convolutional neural network to classify the 1.2 million high-resolution images in the ImageNet LSVRC-2010 contest into the 1000 different classes. On the test data, we achieved top-1 and top-5 error rates of 37.5% and 17.0%, respectively, which is considerably better than the previous state-of-the-art. The neural network, which has 60 million parameters and 650,000 neurons, consists of five convolutional layers, some of which are followed by max-pooling layers, and three fully connected layers with a final 1000-way softmax. To make training faster, we used non-saturating neurons and a very efficient GPU implementation of the convolution operation. To reduce overfitting in the fully connected layers we employed a recently developed regularization method called "dropout" that proved to be very effective. We also entered a variant of this model in the ILSVRC-2012 competition and achieved a winning top-5 test error rate of 15.3%, compared to 26.2% achieved by the second-best entry.
The increasing global industrialization and over-exploitation of fossil fuels has induced the release of greenhouse gases, leading to an increase in global temperature and causing environmental issues. There is therefore an urgent necessity to reach net-zero carbon emissions. Only 4.5% of countries have achieved carbon neutrality, and most countries are still planning to do so by 2050-2070. Moreover, synergies between different countries have hampered synergies between adaptation and mitigation policies, as well as their co-benefits. Here, we present a strategy to reach a carbon neutral economy by examining the outcome goals of the 26th summit of the United Nations Climate Change Conference of the Parties (COP 26). Methods have been designed for mapping carbon emissions, such as input-output models, spatial systems, geographic information system maps, light detection and ranging techniques, and logarithmic mean divisia. We present decarbonization technologies and initiatives, and negative emissions technologies, and we discuss carbon trading and carbon tax. We propose plans for carbon neutrality such as shifting away from fossil fuels toward renewable energy, and the development of low-carbon technologies, low-carbon agriculture, changing dietary habits and increasing the value of food and agricultural waste. Developing resilient buildings and cities, introducing decentralized energy systems, and the electrification of the transportation sector is also necessary. We also review the life cycle analysis of carbon neutral systems.
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For most patients, asthma is not controlled as defined by guidelines; whether this is achievable has not been prospectively studied. A 1-year, randomized, stratified, double-blind, parallel-group study of 3,421 patients with uncontrolled asthma compared fluticasone propionate and salmeterol/fluticasone in achieving two rigorous, composite, guideline-based measures of control: totally and well-controlled asthma. Treatment was stepped-up until total control was achieved (or maximum 500 microg corticosteroid twice a day). Significantly more patients in each stratum (previously corticosteroid-free, low- and moderate-dose corticosteroid users) achieved control with salmeterol/fluticasone than fluticasone. Total control was achieved across all strata: 520 (31%) versus 326 (19%) patients after dose escalation (p < 0.001) and 690 (41%) versus 468 (28%) at 1 year for salmeterol/fluticasone and fluticasone, respectively. Asthma became well controlled in 1,071 (63%) versus 846 (50%) after dose escalation (p < 0.001) and 1,204 (71%) versus 988 (59%) at 1 year. Control was achieved more rapidly and at a lower corticosteroid dose with salmeterol/fluticasone versus fluticasone. Across all strata, 68% and 76% of the patients receiving salmeterol/fluticasone and fluticasone, respectively, were on the highest dose at the end of treatment. Exacerbation rates (0.07-0.27 per patient per year) and improvement in health status were significantly better with salmeterol/fluticasone. This study confirms that the goal of guideline-derived asthma control was achieved in a majority of the patients.
As a fascinating conjugated polymer, graphitic carbon nitride (g-C3N4) has become a new research hotspot and drawn broad interdisciplinary attention as a metal-free and visible-light-responsive photocatalyst in the arena of solar energy conversion and environmental remediation. This is due to its appealing electronic band structure, high physicochemical stability, and "earth-abundant" nature. This critical review summarizes a panorama of the latest progress related to the design and construction of pristine g-C3N4 and g-C3N4-based nanocomposites, including (1) nanoarchitecture design of bare g-C3N4, such as hard and soft templating approaches, supramolecular preorganization assembly, exfoliation, and template-free synthesis routes, (2) functionalization of g-C3N4 at an atomic level (elemental doping) and molecular level (copolymerization), and (3) modification of g-C3N4 with well-matched energy levels of another semiconductor or a metal as a cocatalyst to form heterojunction nanostructures. The construction and characteristics of each classification of the heterojunction system will be critically reviewed, namely metal-g-C3N4, semiconductor-g-C3N4, isotype g-C3N4/g-C3N4, graphitic carbon-g-C3N4, conducting polymer-g-C3N4, sensitizer-g-C3N4, and multicomponent heterojunctions. The band structures, electronic properties, optical absorption, and interfacial charge transfer of g-C3N4-based heterostructured nanohybrids will also be theoretically discussed based on the first-principles density functional theory (DFT) calculations to provide insightful outlooks on the charge carrier dynamics. Apart from that, the advancement of the versatile photoredox applications toward artificial photosynthesis (water splitting and photofixation of CO2), environmental decontamination, and bacteria disinfection will be presented in detail. Last but not least, this comprehensive review will conclude with a summary and some invigorating perspectives on the challenges and future directions at the forefront of this research platform. It is anticipated that this review can stimulate a new research doorway to facilitate the next generation of g-C3N4-based photocatalysts with ameliorated performances by harnessing the outstanding structural, electronic, and optical properties for the development of a sustainable future without environmental detriment.
Mixed methods research offers powerful tools for investigating complex processes and systems in health and health care. This article describes integration principles and practices at three levels in mixed methods research and provides illustrative examples. Integration at the study design level occurs through three basic mixed method designs-exploratory sequential, explanatory sequential, and convergent-and through four advanced frameworks-multistage, intervention, case study, and participatory. Integration at the methods level occurs through four approaches. In connecting, one database links to the other through sampling. With building, one database informs the data collection approach of the other. When merging, the two databases are brought together for analysis. With embedding, data collection and analysis link at multiple points. Integration at the interpretation and reporting level occurs through narrative, data transformation, and joint display. The fit of integration describes the extent the qualitative and quantitative findings cohere. Understanding these principles and practices of integration can help health services researchers leverage the strengths of mixed methods.
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For over a decade prophets have voiced the contention that the organization of a single computer has reached its limits and that truly significant advances can be made only by interconnection of a multiplicity of computers in such a manner as to permit cooperative solution. Variously the proper direction has been pointed out as general purpose computers with a generalized interconnection of memories, or as specialized computers with geometrically related memory interconnections and controlled by one or more instruction streams.
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The emergence of artificial intelligence (AI) and its progressively wider impact on many sectors requires an assessment of its effect on the achievement of the Sustainable Development Goals. Using a consensus-based expert elicitation process, we find that AI can enable the accomplishment of 134 targets across all the goals, but it may also inhibit 59 targets. However, current research foci overlook important aspects. The fast development of AI needs to be supported by the necessary regulatory insight and oversight for AI-based technologies to enable sustainable development. Failure to do so could result in gaps in transparency, safety, and ethical standards.
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