This paper characterizes the trade-offs between information and energy transmission over an additive white Gaussian noise channel in the finite block-length regime with finite channel input symbols. These trade-offs are characterized in the form of inequalities involving the information transmission rate, energy transmission rate, decoding error probability (DEP) and energy outage probability (EOP) for a given finite block-length code. The first set of results identify a set of necessary conditions that a given code must satisfy for simultaneous information and energy transmission. Following this, a novel method for constructing a family of codes that can satisfy a target information rate, energy rate, DEP and EOP is proposed. Finally, achievability results identify the set of tuples of information rate, energy rate, DEP and EOP that can be simultaneously achieved by the constructed family of codes.

This paper characterizes an achievable information-energy region of simultaneous information and energy transmission over an additive white Gaussian noise channel. This analysis is performed in the finite block-length regime with finite constellations. More specifically, a method for constructing a family of codes is proposed and the set of achievable tuples of information rate, energy rate, decoding error probability (DEP) and energy outage probability (EOP) is characterized. Using existing converse results, it is shown that the construction is information rate, energy rate, and EOP optimal. The achieved DEP is, however, sub-optimal.

This paper characterizes the trade-offs between the information and energy transmission rates, the decoding error probability, and the energy outage probability in simultaneous information and energy transmission over an additive white Gaussian noise channel. The results in this paper take into account the impact of energy harvester (EH) non-linearities on the harvested energy. The analysis is carried out in the finite block-length regime with finite constellations. Improved converse and achievability bounds that account for the EH non-linearities are presented.

In this paper, the fundamental limits on the rates at which information and energy can be simultaneously transmitted over an additive white Gaussian noise channel are studied under the following assumptions: (a) the channel is memoryless; (b) the number of channel input symbols (constellation size) and block length are finite; and (c) the decoding error probability (DEP) and the energy outage probability (EOP) are bounded away from zero. In particular, it is shown that the limits on the maximum information and energy transmission rates; and the minimum DEP and EOP, are essentially set by the type induced by the code used to perform the transmission. That is, the empirical frequency with which each channel input symbol appears in the codewords. Using this observation, guidelines for optimal constellation design for simultaneous energy and information transmission are presented.

Multicast transmission has been gaining importance as an efficient means of delivering bandwidth hungry video content and is expected to become an integral part of cellular networks worldwide. This has resulted in the need for generalized allocation algorithms that are capable of handling multiple multicast and unicast services with different Quality of Service (QoS) requirements. In this paper, we propose such a Vickrey-Clarke-Groves (VCG) auction based resource allocation and pricing algorithm. The proposed algorithm takes allocation decisions based on the QoS requirements of the end users for maximizing the system social utility. Even though the users in a multicast group are served on the same PRB, requirements of each individual user are taken into consideration while making the allocation decisions. The proposed algorithm ensures that the users report their true valuations of the system resources. VCG auctions provide a general framework for designing truthful optimal mechanisms. However, in many cases, VCG auction turns out to be NP-hard. In this paper, we propose an efficient, polynomial time implementation of the proposed VCG mechanism. Using simulations, we show that the algorithm successfully meets the unique demands of all unicast and multicast services.

With multimedia becoming the most dominant part of data traffic, many situations arise where the same content is required to be transmitted to many or all users in a cell. We propose the use of multicast transmission for dealing with such situations. With multicast transmission, we can accommodate more users in the available resources simultaneously. We propose grouping and resource allocation schemes for multicast transmissions in LTE. We also compare the performance of unicast and multicast transmission in terms of resource utilization at the evolved NodeB (eNB). We have considered two different methods for multicast group formation with fixed and variable group sizes. Allocation of resources is performed using a greedy scheme and a Linear Programming (LP) relaxation based approach. A number of scenarios become feasible by the use of multicast which are otherwise infeasible if usual unicast transmissions are used.