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During cell devision, maintaining the epigenetic information encoded in histone modification patterns is crucial for survival and identity of cells. The faithful inheritance of the histone marks from the parental to the daughter strands is a puzzle, given that each strand gets only half of the parental nucleosomes. Mapping DNA replication and reconstruction of modifications to equivalent problems in communication of information, we ask how well enzymes can recover the parental modifications, if they were ideal computing machines. Studying a parameter regime where realistic enzymes can function, our analysis predicts that enzymes may implement a critical threshold filling algorithm which fills unmodified regions of length at most k. This algorithm, motivated from communication theory, is derived from the maximum à posteriori probability (MAP) decoding which identifies the most probable modification sequence based on available observations. Simulations using our method produce modification patterns similar to what has been observed in recent experiments. We also show that our results can be naturally extended to explain inheritance of spatially distinct antagonistic modifications. Author summary: Chromatin is essentially the DNA that is folded and packaged with the help of proteins. While the nucleotide sequence in the DNA codes genetic information, the packaging of the DNA into chromatin encodes extra layer of information. This epigenetic code regulates reading of the genetic code and provides identity to cells—whether the cell is a skin cell or a brain cell, for example. In this work we examine a long standing puzzle, that is, how the epigenetic code in the form of histone modification patterns may get inherited, when a cell divides. Using theoretical arguments, we present an algorithm that enzymes could be executing so that the epigenetic code can be inherited with minimal error, soon after DNA replication. [ABSTRACT FROM AUTHOR]

It is well known that the capacity region of an average transmit power constrained Gaussian Broadcast Channel (GBC) with independent noise realizations at the receivers is enlarged by the presence of causal noiseless feedback. When the noise variances at the receivers are identical, even passive feedback via independent memoryless Gaussian links can lead to a capacity region enlargement. The last fact remains true even when the feedback noise variance is very high, and available only from one of the receivers. While such capacity enlargements are feasible for several other feedback models in the Gaussian BC setting, it is also known that feedback does not change the capacity region for physically degraded broadcast channels. In this paper, we consider a two user GBC with independent noise realizations at the receivers, where the feedback links from the receivers are corrupted by independent additive Gaussian noise processes. We investigate the set of four noise variances, two forward and two feedback, for which no capacity enlargement is possible. A sharp characterization of this region is derived, i.e., any quadruple outside the presented region will lead to a capacity enlargement, whereas quadruples inside will leave the capacity region unchanged. Our results lead to the conclusion that when the forward noise variances are different, too noisy a feedback from one of the receivers alone is not always beneficial for enlarging the capacity region, be it from the stronger user or the weaker one, in sharp contrast to the case of equal forward noise variances. [ABSTRACT FROM AUTHOR]

A hybrid communication network with a common analog source signal and independent digital data streams at the transmitters of a multiple access network is considered. The receiver has to estimate the analog signal samples with a given fidelity, and decode the digital streams with a low error probability. The main goal of this paper is to characterize the optimal tradeoff between the mean-squared error distortion in source estimation and the data rates available to each user. To this end, we consider a Gaussian multiple access channel (GMAC) setup with additive state, where the state is nothing but a scaled version of the source process itself. The state process is assumed to be non-causally available to all the transmitting nodes. The problem now becomes that of the joint state estimation and message communication in a GMAC with state. We provide a complete characterization of the optimal distortion-rate tradeoff for an $N$ —sender GMAC. Our results show that, similar to the single-user results, it is optimal to amplify the state using uncoded transmissions, whereas the digital streams are superposed using appropriate Gaussian codebooks in conjunction with dirty paper coding (DPC). Since the variance of the additive state is controlled by a scaling factor in our model, we also recover the results for communicating a common source and independent messages over a GMAC without state as a special case. [ABSTRACT FROM AUTHOR]

In wireless communications, a fading multiple-access channel (MAC) is typically used to model the uplink communication. Conventional MACs assume a centralized system, where the transmission rate and power are chosen centrally for every fading vector realization. On the other hand, there is considerable interest in the performance of distributed multiple access systems, where the lack of global channel state information (CSI) demands novel communication strategies. We consider a block-fading MAC where each transmitter is aware only of its own link CSI, which we term as the individual CSI MAC. The receiver has access to the full CSI of all links. This model was recently introduced in the information theory literature, and naturally leads to a distributed access system with several applications. An important utility of interest for this model is known as the power-controlled adaptive sum-capacity, whose evaluation is an open problem. This is the main subject of the current paper. We present the power-controlled adaptive sum-capacity of a wide class of popular fading MAC models. In particular, we characterize the sum-capacity when the statistics of the channel are identical across users. The proposed schemes also allow a low-complexity successive-cancellation decoding using rate-splitting. Furthermore, the optimal schemes are extended to situations in which each transmitter has additional finite-rate partial CSI on the link quality of others. [ABSTRACT FROM AUTHOR]

We study the problem of simulating a two-user multiple-access channel (MAC) over a multiple access network of noiseless links. Two encoders observe independent and identically distributed (i.i.d.) copies of a source random variable each, while a decoder observes i.i.d. copies of a side-information random variable. There are rate-limited noiseless communication links between each encoder and the decoder, and there is independent pairwise shared randomness between all the three possible pairs of nodes. The decoder has to output approximately i.i.d. copies of another random variable jointly distributed with the two sources and the side information. We are interested in the rate tuples which permit this simulation. This setting can be thought of as a multi-terminal generalization of the point-to-point channel simulation problem studied by Bennett et al. (2002) and Cuff (2013). When the pairwise shared randomness between the encoders is absent, the setting reduces to a special case of MAC simulation using another MAC studied by Haddadpour et al. (2013). We establish that the presence of encoder shared randomness can strictly improve the communication rate requirements. We first show that the inner bound derived from Haddadpour et al. (2013) is tight when the sources at the encoders are conditionally independent given the side-information at the decoder. This result recovers the existing results on point-to-point channel simulation and function computation over such multi-terminal networks. We then explicitly compute the communication rate regions for an example both with and without the encoder shared randomness and demonstrate that its presence strictly reduces the communication rates. Inner and outer bounds for the general case are also obtained. [ABSTRACT FROM AUTHOR]

The mesosphere–stratosphere–troposphere (MST) radar is a very high frequency (VHF) pulsed coherent Doppler radar used for ground-based remote sensing. In an MST radar, the backscattered pulses due to fluctuations in atmospheric refractive index are observed at the receiver. Echoes from higher altitudes are typically weaker, resulting in a low signal-to-noise ratio (SNR). They could also be contaminated with clutter and interference, making conventional spectral estimation techniques in the Fourier domain unreliable. In this article, we propose an algorithm to estimate the atmospheric wind profile using a dynamic programming approach employing the Viterbi data association (VDA) algorithm. Progressively for each range bin, the proposed algorithm chooses a set of probable wind speeds as nodes in a trellis. A branch metric incorporating the kinematic parameters inclusive of the differential wind shear is then constructed for state transitions within the trellis, from nodes in one range bin to the subsequent ones. A dynamic programming approach then chooses the optimal wind profile across altitudes. The proposed algorithm is experimented on simulated as well as real MST radar data sets to verify its robustness. Our experiments show that the suggested method has improved performance when compared to previously established techniques. [ABSTRACT FROM AUTHOR]

A time-slotted multiple access system with bursty data arrivals to the terminals is considered, where variable sized packets independently arrive in each slot at every transmitter. Each packet is required to be delivered to a common receiver within a certain number of slots specified by a maximum delay constraint. The terminals know only their own packet arrival process, i.e., the arrivals at the rest of the terminals are unknown to each transmitter, except for their probability distributions. For this interesting distributed multiple access model, we design novel online communication schemes which transport the arriving data without any outage, while respecting the delay constraint. In particular, the users choose their respective transmit powers in a distributed manner, ensuring at the same time that the joint power vector is sufficient to support the distributed choice of data rates employed in that slot. The proposed schemes are not only optimal in minimizing the average transmit sum power, but they also considerably outperform conventional orthogonal multiple access techniques like time-division multiple access. An optimal scheme for a multiple access channel with arrivals and time-varying fading is also presented, under a unit slot delay constraint. [ABSTRACT FROM AUTHOR]

Traditionally, the capacity region of a coherent fading multiple access channel (MAC) is analyzed in two popular contexts. In the first, a centralized system with full channel state information at the transmitters (CSITs) is assumed, and the transmit power and data-rate can be jointly chosen for every fading vector realization. On the other hand, in fast-fading links with distributed CSIT, the lack of full CSI is compensated by performing ergodic averaging over sufficiently many channel realizations. Notice that the distributed CSI may necessitate decentralized power-control for optimal data-transfer. Apart from these two models, the case of slow-fading links and distributed CSIT, though relevant to many systems, has received much less attention. In this paper, a block-fading additive white Gaussian noise MAC with full CSI at the receiver and distributed CSI at the transmitters is considered. The links undergo independent fading, but otherwise have arbitrary fading distributions. The channel statistics and respective long-term average transmit powers are known to all parties. We first consider the case where each encoder has knowledge only of its own link quality, and not of others. For this model, we compute the adaptive capacity region, i.e., the collection of average rate-tuples under blockwise coding/decoding such that the rate-tuple for every fading realization is inside the instantaneous MAC capacity region. The key step in our solution is an optimal rate allocation function for any given set of distributed power control laws at the transmitters. This also allows us to structurally characterize the optimal power control for a wide class of fading models. Further extensions are also proposed for the case where each encoder has additional partial CSI about the other links. [ABSTRACT FROM PUBLISHER]

Time Division Duplex (TDD) wireless communication systems are inherently bidirectional, which facilitates exploiting channel reciprocity for pilot based channel estimation of both uplink and downlink. However, there exists a gross asymmetry in channel estimation complexity for the uplink and downlink, particularly for Multiple Input Multiple Output (MIMO) TDD systems. Usually, Base Stations (BS) with more antennas need to estimate fewer parameters from each antenna, whereas the estimation requirement is disproportionately higher at the User Equipment (UE). Unlike the UE, the BS has powerful hardware, computational resources and energy to estimate and track channel profiles accurately. To overcome this asymmetry, we propose a solution for MIMO-TDD downlink communication, wherein the post-coder part of the channel matrix is quantized at the BS, and is communicated to the UE via a low-rate channel. Using asymptotically tight lower bounds on the downlink information-theoretic rates achievable, we quantify the performance of the proposed scheme. Simulations reveal that a moderate number of quantization bits are sufficient to achieve rates close to the link capacity. We further show that in the massive MIMO regime, where the BS has many more antennas than the UE, the channel can be effectively compensated by appropriate transmit domain precoding, without any post-coder knowledge at the UE. [ABSTRACT FROM AUTHOR]