The paper presents a carrier frequency offset(CFO) estimation algorithm with synchronization for digital communication receivers. The algorithm utilizes fractional time periods to arrive at a coarse CFO estimate. The reliability of the coarse CFO estimate is improved using information from the phase difference across the preamble period. The proposed algorithm is not specific to any standard and can estimate CFO of large magnitudes. This aspect is particularly useful in scenario wherein the preamble period falls short in capturing the phase information corresponding to CFO range specified by the standard. Simulation studies have been carried out to demonstrate the performance of the proposed algorithm.

In this work, capacity based optimal best beam set selection methods in MIMO channel condition are presented. Proposed methods are suitable for existing Verizon 5G specifications \cite{VzW} and also scalable to upcoming 3GPP NR\cite{NR} mmWave communications systems. Proposed methods are aimed at improving the performance, robustness and computational efficiency of the user equipment (UE) system where beam measurements are intended. Two methods namely, a two stage capacity maximization (CM) based method and a hybrid power and capacity maximization based method are proposed herein. Capacity based solutions are preferred over received signal strength (RSS) based methods in view of its superior performance in presence of unknown interference and noise. Hybrid method exploits the sparse channels inherent in beamformed mmWave systems. Also, it is preferable as it complies with the evolving 5G communication requirements which need estimation of additional alternative MIMO transmit and receive beam pairs apart from the serving beams to achieve higher throughput by overcoming random beam blockage and misalignment. Efficacy and performance of the proposed beam-selection methods is compared with existing RSS based method. Also computational complexity of the proposed methods are analyzed and numerical results comparing them are presented. Advantages of the capacity based methods proposed are demonstrated through analysis and simulation results.

This paper presents a low complexity algorithm for compensating the sampling-clock frequency offset encountered in short-range WPAN receivers. The proposed algorithm leverages on the pulse shaping information in the transmitted signal to identify erroneous samples resulting from the sampling-clock frequency offset and then compensates for the same. Simulation results demonstrate that the proposed algorithm almost completely compensates for offsets of magnitudes specified by WPAN standards.

This paper explores a novel approach for beamforming (BF) training in millimeter wave (mmWave) multiantenna communication systems. The contribution of this paper is in the following aspects: i) This paper proposes a fast BF training procedure building on the novel concept of beamcoding for the estimation of the optimal direction of arrival (DoA) and direction of departure (DoD). Briefly, the beamcoding scheme facilitates the identification of DoA/DoD at the receiver/transmitter based on a set of orthogonal codes. ii) Building on the properties of a special class of orthogonal codes called constant amplitude zero autocorrelation(CAZAC) sequences, this paper proposes a low-complexity implementation of beamcoding procedure to facilitate BF training. We emphasize that the proposed beamcoding schemes can be implemented at the transmitter/receiver with the help of only a single radio frequency (RF) chain with a set of analog phase shifters. Notably, the proposed method is not restricted to just mmWave communication systems, and can be applied to any generic system involving multiantenna transceivers. Simulation results are presented to demonstrate the efficacy of our proposed idea.

In this paper, we explore a method for simultaneous tranmission to coherent and non-coherent receivers, based on ternary sequences. In many communication scenarios, the transmitters are required to support both coherent and non-coherent forms of reception thereby requiring the transmission protocols to be designed such that the transmitted data is decoded reliably at both coherent and non-coherent receivers. Further, in such scenarios, for practical purposes, the transmitter is assumed to be agnostic to the type of the intended receiver, making the design more challenging. Thus motivated, we propose a transmission mechanism for simultaneous reception by coherent and noncoherent receivers. This transmission is enabled by ternary codes, i.e., codes over the ternary alphabet: {−1, 0, +1}. The design of these ternary codes, which exhibit good correlation properties for both coherent and non-coherent reception is a major contribution of this paper. Simulation results show that the proposed codes provide almost similar performance as the optimal codes meant for the respective receiver types.

This paper considers opportunistic cooperative networking (OCN) in wireless ad hoc networks, with a focus on characterizing the desired tradeoff between the probing cost for establishing cooperative relaying and hence higher throughput via opportunistic cooperative networking. Specifically, opportunistic cooperative networking is treated as an optimal stopping problem with two-levels of incomplete information. Cases with or without dedicated relays are considered, and the existence of the optimal strategies for both cases are established. Then, it is shown that for the case with dedicated relays, the optimal strategy exhibits a threshold structure, in which it is optimal to probe the dedicated relay when the signal-to-noise ratio (SNR) of the source-relay link exceeds some threshold. For the case without dedicated relays, under more restrictive conditions, the optimal strategy is also threshold-based, in the sense that it is optimal to probe potential relays when the SNR of the source-destination link lies between two thresholds. Furthermore, these strategies can be implemented in a distributed manner.

This paper considers distributed opportunistic scheduling (DOS) with cooperative relaying in wireless ad hoc networks, with a focus on characterizing the desired tradeoff between the probing cost for establishing cooperative relaying and the higher throughput via opportunistic cooperative networking. Specifically, distributed scheduling and probing for cooperative relaying is treated as an optimal stopping problem with two levels of incomplete information. Cases with or without dedicated relays are considered, and the existence of the optimal strategies for both cases are established. Then, it is shown that for the case with dedicated relays, the optimal strategy exhibits a threshold structure, in which it is optimal to probe the dedicated relay when the signal-to-noise ratio (SNR) of the source-relay link exceeds some threshold. For the case without dedicated relays, under more restrictive conditions, the optimal strategy is also threshold-based, in the sense that it is optimal to probe potential relays when the SNR of the source-destination link lies between two thresholds. Furthermore, these strategies can be implemented in a distributed manner.

This paper studies multicasting compressively sampled signals from a source to many receivers, over lossy wireless channels. Our focus is on the network outage from the perspective of signal distortion across all receivers, for both cases where the transmitter may or may not be capable of reconstructing the compressively sampled signals. Capitalizing on extreme value theory, we characterize the network outage in terms of key system parameters, including the erasure probability, the number of receivers and the sparse structure of the signal. We show that when the transmitter can reconstruct the compressively sensed signal, the strategy of using network coding to multicast the reconstructed signal coefficients can reduce the network outage significantly. We observe, however, that the traditional network coding could result in suboptimal performance with power-law decay signals. Thus motivated, we devise a new method, namely subblock network coding, which involves fragmenting the data into subblocks, and allocating time slots to different subblocks, based on its priority. We formulate the corresponding optimal allocation as an integer programming problem. Since integer programming is often intractable, we develop a heuristic algorithm that prioritizes the time slot allocation by exploiting the inherent priority structure of power-law decay signals. Numerical results show that the proposed schemes outperform the traditional methods with significant margins.

A two-user interference channel is considered where each transmitter has access to a part of the information intended to the other destination. A primary objective is to maximize the information rates, by exploring the cooperation between the transmitters for interference mitigation, based on the partial side information. It is clear that full cooperation between the transmitters is not possible since each transmitter has only a part of the side information. With this insight, several “layered coding” schemes, consisting of binning and superposition at different stages, are developed. These schemes are are carefully built on coding strategies for the classical interference channel and node cooperation mechanisms. In particular, two layered coding schemes, which are based on a combination of MIMO broadcast coding and the Han-Kobayashi (HK) coding, are thoroughly studied : The first one, namely layered coding with binning, makes heavy use of the Gelfand-Pinsker binning and the HK coding and the second one, namely layered superposition coding, involves superposition coding over different tiers. Rate regions corresponding to the proposed schemes are derived. Then the application of these coding schemes are illustrated for the Gaussian case and numerical results corroborate that the proposed layered coding schemes yield substantial gains at high SNR.

We consider a two-user Gaussian interference channel with a relay. Specifically, two source-destination pairs and the relay share a single common channel, and the relay receives messages from both sources, and assists them in communicating the messages to their respective destinations. We propose two relaying schemes using "amplify-and-forward" (AF). For each of two modes considered, we characterize the achievable sum rate and present upper bounds as functions of relay locations.

Distributed opportunistic scheduling (DOS) is studied for wireless ad hoc networks in which many links contend for a channel using random access before data transmission. Simply put, DOS involves a process of joint channel probing and distributed scheduling for ad hoc (peer-to-peer) communications. Since, in practice, link conditions are estimated with noisy observations, the transmission rate must be backed off from the estimated rate in order to avoid transmission outages. Then, a natural question to ask is whether or not it is worthwhile for the link with successful contention to perform further channel probing to mitigate estimation errors, at the cost of additional probing. Thus motivated, this work investigates DOS with two-level channel probing by optimizing the tradeoff between the throughput gain from more accurate rate estimation and the resulting additional delay. By capitalizing on optimal stopping theory with incomplete information, it is shown that the optimal scheduling policy is threshold-based and is characterized by either one or two thresholds, depending on network settings. Necessary and sufficient conditions for both cases are rigorously established. In particular, this analysis reveals that performing second-level channel probing is optimal when the first-level estimated channel condition falls in between the two thresholds. Numerical results are provided to illustrate the effectiveness of the proposed DOS with two-level channel probing. This study is also extended to the case with limited feedback, in which the feedback from the receiver to its transmitter takes the form of$(0,1,e)$.

Distributed opportunistic scheduling (DOS) is studied for wireless ad-hoc networks in which many links contend for the channel using random access before data transmissions. Simply put, DOS involves a process of joint channel probing and distributed scheduling for ad-hoc (peer-to-peer) communications. Since, in practice, link conditions are estimated with noisy observations, the transmission rate has to be backed off from the estimated rate to avoid transmission outages. Then, a natural question to ask is whether it is worthwhile for the link with successful contention to perform further channel probing to mitigate estimation errors, at the cost of additional probing. Thus motivated, this work investigates DOS with two-level channel probing by optimizing the tradeoff between the throughput gain from more accurate rate estimation and the resulting additional delay. Capitalizing on optimal stopping theory with incomplete information, we show that the optimal scheduling policy is threshold-based and is characterized by either one or two thresholds, depending on network settings. Necessary and sufficient conditions for both cases are rigorously established. In particular, our analysis reveals that performing second-level channel probing is optimal when the first-level estimated channel condition falls in between the two thresholds. Finally, numerical results are provided to illustrate the effectiveness of the proposed DOS with two-level channel probing.