Federated Learning is a promising option for data privacy and security in ITS, because it allows edge devices, Road Side Units (RSUs), and Central Server (CS) to jointly train the machine learning model. Since RSU collects data from the vehicles passing through its range, the local data of each RSU will have a non-IID distribution, which adversely affects the convergence speed and accuracy of FL training. Generating synthetic data locally at individual nodes, followed by data shuffling among the nodes, is a promising approach to address the Non-IID data problem. In this work, we propose pliable index coding (PIC) solutions for efficient data shuffling among the nodes in an FL system. In PIC($S$) problems, a client is satisfied if it can retrieve any $S$ new messages not originally present in its side-information. We particularly consider decentralized pliable index coding problems (DPIC) where the clients communicate among themselves without a central server to model the data shuffling in FL. A class of DPIC, known as Consecutive Decentralized Pliable Index Coding (CDPIC($S$,$K$)), where each client has $K$ consecutive messages as side-information, is considered. For CDPIC($S$,$K$) problems, pliable index code designs are provided for any value of $K$ and $S$, and optimality proofs for some of the cases are established. Further, these CDPIC solutions are applied for data shuffling in FL, to transform the local data distribution towards IID progressively with each transmission, thereby enhancing the performance of FL. The improvement in the accuracy and convergence of the most popular FL technique, FedAvg, and a promising federated submodel technique, CELL (Communication Efficient Lottery Learning), are analysed by providing different degrees of data shuffling using the proposed CDPIC schemes.

Multi-carrier Non Orthogonal Multiple Access system is considered a promising technique for future wireless communication systems. MC-NOMA system divides transmission bandwidth into sub-bands and multiple users in each sub-band are served based on power-domain NOMA. This work attempts to find the best clustering scheme that can provide the maximum sum rate for NOMA with unequal bandwidth allocation. We try to improve the system performance by tuning the bandwidth allocated to different clusters to find the best clustering scheme. The analytical results compared and validated using the golden search method reveal that pairing up the best channel gain user with the next best channel gain user with optimal bandwidth allocation gives a better sum rate compared to competitive schemes available in the literature.

Vehicular ad hoc network (VANET), is a developing platform with massive data demands for infotainment services in recent years. Index Coded NOMA (IC-NOMA) is a spectral efficient transmission method that can be used in VANETs. IC-NOMA applies the concepts of non-orthogonal multiple access (NOMA) over the index coded data to increase spectrum and power efficiency. In NOMA, far user does not get access to the near user data, while near user can successfully decode far user data. Therefore, the IC-NOMA demands a novel design of index code for improved bandwidth efficiency. This work considers the design of index code for NOMA when the user demands in VANET follows the data distribution of one-sided symmetric neighboring consecutive side information single unicast index coding problem (SNC-SUICP). For this setup, we develop an optimal closed form index coding (IC) solution which can bring in additional bandwidth savings through NOMA. The improved performance of the proposed IC-NOMA transmission scheme when compared with one-sided SNC-SUICP in terms of bandwidth efficiency is demonstrated.

An Index Coding Problem (ICP) has a central server that possesses files and is connected to multiple users through a shared link. Each user demands a subset of files and possesses another subset of files as side-information. The files which are neither demanded nor possessed as side-information by a user are called its interference files. In a symmetric ICP, the relative positions of side-information and interference files are the same for all the users. In this paper, a general representation for symmetric ICPs is proposed, and using this representation, we give bounds on the optimal transmission rate for a general symmetric ICP. We identify two broad categories of symmetric ICPs: Neighboring Interference ICP (NI-ICP) and Neighboring Side-information ICP (NS-ICP). For a particular class of NI-ICP, we find the optimal transmission rate, and for another class, an order-optimal transmission rate is derived. An upper bound on the optimal transmission rate is established for NS-ICP. Furthermore, for a particular class of NS-ICP, a lower bound for the optimal transmission rate is also derived.

Vehicle to vehicle (V2V) communication has gained its importance in recent years. In this work we consider the index coding problem (ICP) over noisy channel in V2V communication phase of message dissemination. The ICP in V2V communication is considered as device to device ICP with transmitting nodes as receiving nodes also. The index code is used in noisy scenario over AWGN channel and the broadcast vectors are mapped to suitable M-PSK signal constellations to save bandwidth, thus increasing the bandwidth efficiency. An algorithm is proposed to derive suitable mapping of the broadcast vectors to M-PSK signal constellation for improving the error performance. Performance improvement in terms of PSK index coding gain is discussed. While one vehicle transmits, the proposed algorithm provides performance improvement for at least one of the remaining vehicles, in most of the scenarios, while not penalizing the other vehicles.

The decentralized coded caching was Introduced In [M. A. Maddah-Ali and U. Niesen, "Decentralized coded caching attains order-optimal memory-rate tradeoff," IEEE/ACM Trans. Networking, Aug. 2015] in which no coordination is required for the content placement. This scheme is extended to all the demand cases and the optimality is shown in the literature under the uncoded prefetching regime using information theoretic lower bound. In this paper, an alternate proof for optimality is given using index coding techniques. Moreover, for the case when the shared broadcast link is error prone, an optimal error correcting delivery scheme is proposed for coded caching problems with the decentralized placement. Next, the Least Recently Sent (LRS) online coded caching scheme is considered. The optimality of this scheme is also proved using index coding techniques. An optimal error correcting delivery scheme is proposed for coded caching problems with the LRS online prefetching.

For the problem of embedded index coding, a matrix representation, called a side-information matrix and a metric called min-rank are defined to characterize the length of an optimal embedded index code. An optimal embedded index code for a given embedded index coding problem is shown to be obtainable from the columns of its side information matrix. Further, for a class of embedded index coding problems, called one-sided neighboring side information problems, the min-rank is derived and a transmission scheme which has length equal to this min-rank is presented.

Classical coded caching setting avails each user to have one dedicated cache. This is generalized to a more general shared cache scheme and the exact expression for the worst case rate was derived in [E. Parrinello, A. Unsal, P. Elia, " Fundamental Limits of Caching in Heterogeneous Networks with Uncoded Prefetching," available on arXiv:1811.06247 [cs.IT], Nov. 2018]. For this case, an optimal linear error correcting delivery scheme is proposed and an expression for the peak rate is established for the same. Furthermore, a new delivery scheme is proposed, which gives an improved rate for the case when the demands are not distinct.

The index coding with side-information problem introduced by Birk and Kol has been generalized to the case, where the transmissions are subjected to errors by Dau et al.. Lower and upper bounds on the optimal number of transmissions required to correct a specified number δ of errors were established. In another generalization of index coding problem, namely, generalized index coding (GIC) problem introduced by Dai et al., linear combination of the messages can be demanded and held as side information by the receivers. Error correction for GIC problems was studied and the bounds for optimal number of transmissions required for δ-error correcting generalized index codes were established by Byrne and Calderini. In this paper, for a particular class of GIC problems construction of optimal scalar linear index codes are discussed. For this class of GIC problems, the optimal linear δ-error correcting index codes are also constructed. As special cases, optimal linear error correcting codes are obtained for two classes of original index coding problems, namely, single-prior index coding problems and single unicast index coding problems with symmetric neighboring consecutive side information.

In coded caching, a single server is connected to a set of users through a shared bottleneck link, which is assumed to be error free. During non-peak hours, all the users fill their local cache with portions of the files available. During the delivery phase, each user requests a file and the server delivers coded transmissions to meet the demands. In this paper, the links between the server and the users are assumed to be error prone. Prefetching errors are also considered. A new delivery scheme is required to meet the demands of each user even after receiving a finite number of transmissions in error in the presence of erroneous portions of files in the cache. The minimum average rate and minimum peak rate for this problem are characterized. Closed form expressions for average and peak rates for a particular caching scheme, namely, symmetric batch prefetching are established when there are no prefetching errors. An optimal linear error correcting delivery scheme is proposed for coded caching problems with symmetric batch prefetching in the absence of prefetching errors. In addition to this, lower bounds are established for the optimal rate required when there are prefetching errors in symmetric batch prefetching.

Optimal delivery scheme for coded caching problems with small buffer sizes and the number of users no less than the amount of files in the server was proposed by Chen, Fan and Letaief [“Fundamental limits of caching: improved bounds for users with small buffers,” IET Communications, 2016]. This scheme is referred to as the CFL scheme. In this paper, an extension to the coded caching scheme where the link between the server and the users is error prone, is considered. The delivery phase is error prone and the placement phase is considered to be error free. The closed form expressions for average rate and peak rate of error correcting delivery scheme are found for CFL prefetching scheme using techniques from index coding. For a given demand, the delivery phase of a coded caching problem becomes an index coding problem. Using results from error correcting index coding, an optimal linear error correcting delivery scheme for caching problems employing CFL prefetching is proposed.

Coded caching is used to reduce network congestion during peak hours. A single server is connected to a set of users through a shared bottleneck link, which generally is assumed to be error-free. During non-peak hours, all the users have full access to the files and they fill their local cache with portions of the files available. During delivery phase, each user requests a file and the server delivers coded transmissions to meet the demands taking into consideration their cache contents. In this paper we assume that the link between the server and the users is error prone. A new delivery scheme is required to meet the demands of each user even after receiving finite number of transmissions in error. We characterize the average rate and peak rate for this problem. We find closed form expressions of these rates for a particular caching scheme namelysymmetric batch prefetching. We also propose an optimal linear error correcting delivery scheme for coded caching problems with symmetric batch prefetching.

The index coding problem with side information (ICSI) was introduced by Birk and Kol, 1998. In this problem, a sender seeks to meet the demands, in minimum number of transmissions, of several receivers, each of which has some prior information on the messages (called side information). In a generalization of this problem called Generalized Index Coding problem (GICP) (Dai et al 2014), linear combination of the messages can be demanded and held as side information by the receivers. The paper by Byrne and Calderini 2017, characterizes the optimal length of linear index codes for GICP based on generalized minrank. Computation of min-rank is known to be NP-hard in general. Another generalization to ICSI problem, where transmissions are subject to noise, was addressed in Dau et al 2013 and lower and upper bounds on optimal linear ¿-error correcting index codes were established. The paper by Byrne and Calderini 2017, studied error correction for GICP and obtains lower and upper bounds on optimal linear ¿-error correcting index codes. In this paper, we find the optimal length of scalar linear index codes (min-rank) for a specific class of GICP and discuss the construction of optimal scalar linear index codes. We also find optimal error correcting index codes for some special cases of the above mentioned class and discuss the construction of optimal linear ¿-error correcting index codes.

The symmetric capacity for index coding problems with K messages and K receivers, each demanding a unique message (Single Unicast Index Coding Problem) and having symmetric (with respect to receiver index), neighboring and consecutive side information (SUICP-SNC) have been reported by Maleki, Cadambe and Jafar. For these index coding problems, assuming that the transmissions are error prone, we present optimal length error-correcting index codes for all one-sided SUICP-SNC problems and for some cases of two-sided SUICP-SNC problems. We also discuss construction for these optimal Error Correcting Index Codes.