The model of a side information vending machine (VM) accounts for scenarios in which the measurement of side information sequences can be controlled via the selection of cost-constrained actions. In this paper, the three-node cascade source coding problem is studied under the assumption that a side information VM is available at the intermediate and/or end node of the cascade. A single-letter characterization of the achievable tradeoff among the transmission rates, distortions in the reconstructions at the intermediate and end node, and cost for acquiring the side information is derived for a number of relevant special cases. It is shown that a joint design of the description, source, and control signals used to guide the selection of the actions at downstream nodes is generally necessary for an efficient use of the available communication links. In particular, for all the considered models, layered coding strategies prove to be optimal, whereby the base layer fulfills two network objectives: 1) determining the actions of downstream nodes and 2) simultaneously providing a coarse description of the source. Design of the optimal coding strategy is shown via examples to depend on both the network topology and action costs. Examples also illustrate the involved performance tradeoffs across the network.

The capacity of a relay channel with intersymbol interference (ISI) and additive colored Gaussian noise is examined under an input power constraint. Prior results are used to show that the capacity of this channel can be computed by examining the circular degraded relay channel in the limit of infinite block length. The current work provides single letter expressions for the achievable rates with decode-and-forward (DF) and compress-and-forward (CF) processing employed at the relay. Additionally, the cut-set bound for the relay channel is generalized for the ISI/colored Gaussian noise scenario. All results hinge on showing the optimality of the decomposition of the relay channel with ISI/colored Gaussian noise into an equivalent collection of coupled parallel, scalar, memoryless relay channels. The region of optimality of the DF and CF achievable rates is also discussed. The resulting rates are illustrated through the computation of numerical examples.

The problem of state communication over a discrete memoryless channel with discrete memoryless state is studied when the state information is available strictly causally at the encoder. It is shown that block Markov encoding, in which the encoder communicates a description of the state sequence in the previous block by incorporating side information about the state sequence at the decoder, yields the minimum state estimation error. When the same channel is used to send additional independent information at the expense of a higher channel state estimation error, the optimal tradeoff between the rate of the independent information and the state estimation error is characterized via the capacity-distortion function. It is shown that any optimal tradeoff pair can be achieved via rate-splitting. These coding theorems are then extended optimally to the case of causal channel state information at the encoder using the Shannon strategy.

Channels with action-dependent states, as defined in [1], are considered. While [1] investigated the scenario of message dependent non-adaptive action sequences, this work focuses on adaptive action sequences, where the action is a strictly causal function of the message and the state sequences. The capacity of such a channel is characterized for the case when the state information is available non-causally at the channel encoder and it is shown that the adaptive action is not useful in increasing the capacity. The capacity of the action-dependent additive Gaussian channel, which was left open in [1], is then characterized by showing the equivalence of the current setting to the problem of the cooperative multiple access channel (MAC) with asymmetric state information at the encoders [2]. The problem setting is then extended to characterize the rate-distortion region of the source coding dual of the adaptive action-dependent channel coding setup, where a source is to be communicated with some fidelity to a decoder with adaptive action-dependent side information. In this setting adaptivity offers no help in enlarging the rate-distortion region.

The analog imperfections in RF direct conversion receiver, of which I/Q imbalance is a major detriment, are examined. Existing literatures on I/Q imbalance compensation try to compensate for the imbalance by estimating the mismatches. In this work, xampling-based decoding algorithm is examined. This algorithm is shown to be very efficient in handling the impairments in the analog components. Simulation results are also presented to illustrate some of the benefits of the proposed approach.

Channels with action-dependent states are considered: given the message to be communicated, the transmitter chooses an action sequence that affects the formation of the channel states, and then creates the channel input sequence based on the observed state sequence. The capacity - distortion tradeoff of such a channel is characterized for the case when the state information is available strictly causally at the channel encoder. The problem setting extends the action dependent framework of [1] and as a special case recovers the results of few previously considered joint communication and estimation scenarios in [2], [3], [4]. The scenario when the action is also allowed to depend on the past observed states is also considered and it has been shown that such adaptive action helps in achiveing a better capacity - distortion function.

The model of a side information “vending machine” accounts for scenarios in which acquiring side information is costly and thus should be done efficiently. In this paper, the three-node cascade source coding problem is studied under the assumption that a side information vending machine is available either at the intermediate or at the end node. In both cases, a single-letter characterization of the available trade-offs among the rate, the distortions in the reconstructions at the intermediate and at the end node, and the cost in acquiring the side information are derived under given conditions.

Motivated by the presence of an implicit communication channel in the asymptotic version of Witsenhausen's counterexample, implicit discrete memoryless channels (IDMC) with discrete memoryless (DM) states are considered. Information-theoretic lower and upper bounds (based respectively on the ideas from rate-distortion theory and hybrid-coding) are derived on the optimal distortion in estimating the input of the implicit channel. The intuition gained from the DMIC with DM state model is then used to evaluate the optimal distortion for the asymptotic version of the Witsenhausen counterexample. The minimum distortion is characterized for the counterexample and it is shown that a combination of linear coding and dirty-paper coding (DPC) proposed in [1] achieves the minimum distortion.

A problem of state information transmission over a state-dependent discrete memoryless channel (DMC) with independent and identically distributed (i.i.d.) states, known causally at the transmitter is investigated. It is shown that block-Markov encoding coupled with channel state estimation conditioned on treating the decoded message and received channel output as side information at the decoder yields the minimum state estimation error. This same channel can also be used to send additional independent information at the expense of a higher channel state estimation error. It is shown that any optimal tradeoff pair can be achieved via a simple rate-splitting technique, whereby the transmitter appropriately allocates its rate between pure information transmission and state estimation.

The achievable rate of a relay channel with inter-symbol interference and additive colored Gaussian noise is examined under an input power constraint and the compress-and-forward (CF) strategy at the relay. Using classical techniques, it is shown that the circular degraded relay channels is equivalent to that of the linear one in the limit of infinite block lengths. The achievable rate for CF for a circular Gaussian relay channel is equivalent to that of coupled collection of parallel, memoryless relay channels. Additionally, this parallel channel decomposition is shown to be information lossless for the evaluation of the CF rate.

The capacity of a degraded relay channel with inter-symbol interference and additive colored Gaussian noise is examined under an input power constraint. Using the classical methodology, a related channel and signal model is developed - the circular degraded relay channel - the capacity of which is shown to be equivalent to that of the channel of interest in the limit of infinite block length. The capacity of circular relay channel is, in turn, determined by the decomposition into parallel degraded relay channels whose individual capacities are given by prior results. Two case studies based on the degraded relay channel with memory and white noise are examined: Common transmission bandwidths on each link and different effective transmission bandwidth over each link.