Outage analysis of superposition modulation aided network coded cooperation in the presence of network coding noise

We consider a network, where multiple sourcedestination pairs communicate with the aid of a half-duplex relay node (RN), which adopts decode-forward (DF) relaying and superposition-modulation (SPM) for combining the signals transmitted by the source nodes (SNs) and then forwards the composite signal to all the destination nodes (DNs). Each DN extracts the signals transmitted by its own SN from the composite signal by subtracting the signals overheard from the unwanted SNs. We derive tight lower-bounds for the outage probability for transmission over Rayleigh fading channels and invoke diversity combining at the DNs, which is validated by simulation for both the symmetric and the asymmetric network configurations. For the high signal-to-noise ratio regime, we derive both an upperbound as well as a lower-bound for the outage performance and analyse the achievable diversity gain. It is revealed that a diversity order of 2 is achieved, regardless of the number of SN-DN pairs in the network. We also highlight the fact that the outage performance is dominated by the quality of the worst overheated link, because it contributes most substantially to the network coding noise. Finally, we use the lower bound for designing a relay selection scheme for the proposed SPM based network coded cooperative communication (SPM-NC-CC) system.<br/

Ultra-Reliable Cloud Mobile Computing with Service Composition and Superposition Coding

An emerging requirement for 5G systems is the ability to provide wireless ultra-reliable communication (URC) services with close-to-full availability for cloud-based applications. Among such applications, a prominent role is expected to be played by mobile cloud computing (MCC), that is, by the offloading of computationally intensive tasks from mobile devices to the cloud. MCC allows battery-limited devices to run sophisticated applications, such as for gaming or for the "tactile" internet. This paper proposes to apply the framework of reliable service composition to the problem of optimal task offloading in MCC over fading channels, with the aim of providing layered, or composable, services at differentiated reliability levels. Inter-layer optimization problems, encompassing offloading decisions and communication resources, are formulated and addressed by means of successive convex approximation methods. The numerical results demonstrate the energy savings that can be obtained by a joint allocation of computing and communication resources, as well as the advantages of layered coding at the physical layer and the impact of channel conditions on the offloading decisions.Comment: 8 pages, 5 figures, To be presented at CISS 201

Resource-efficient wireless relaying protocols

Relay-aided communication is considered one of the key techniques to achieve high throughput at low cost in future wireless systems. However, when transmitting signals via a relay, additional time slots, antennas, or frequency slots are required, which may erode the potential gain of relay-aided systems. In this article various approaches to creating relay-aided systems are reviewed. The advantages and disadvantages of various relaying schemes are compared in terms of their slot efficiency, error rate performance, and feasibility. Our detailed comparisons and the numerical results indicate that the specific family of network coding aided relaying protocols constitutes one of the most promising solutions. We conclude this article by listing a number of open problems

The Multi-way Relay Channel

The multiuser communication channel, in which multiple users exchange information with the help of a relay terminal, termed the multi-way relay channel (mRC), is introduced. In this model, multiple interfering clusters of users communicate simultaneously, where the users within the same cluster wish to exchange messages among themselves. It is assumed that the users cannot receive each other's signals directly, and hence the relay terminal in this model is the enabler of communication. In particular, restricted encoders, which ignore the received channel output and use only the corresponding messages for generating the channel input, are considered. Achievable rate regions and an outer bound are characterized for the Gaussian mRC, and their comparison is presented in terms of exchange rates in a symmetric Gaussian network scenario. It is shown that the compress-and-forward (CF) protocol achieves exchange rates within a constant bit offset of the exchange capacity independent of the power constraints of the terminals in the network. A finite bit gap between the exchange rates achieved by the CF and the amplify-and-forward (AF) protocols is also shown. The two special cases of the mRC, the full data exchange model, in which every user wants to receive messages of all other users, and the pairwise data exchange model which consists of multiple two-way relay channels, are investigated in detail. In particular for the pairwise data exchange model, in addition to the proposed random coding based achievable schemes, a nested lattice coding based scheme is also presented and is shown to achieve exchange rates within a constant bit gap of the exchange capacity.Comment: Revised version of our submission to the Transactions on Information Theor

Minimum-cost multicast over coded packet networks

We consider the problem of establishing minimum-cost multicast connections over coded packet networks, i.e., packet networks where the contents of outgoing packets are arbitrary, causal functions of the contents of received packets. We consider both wireline and wireless packet networks as well as both static multicast (where membership of the multicast group remains constant for the duration of the connection) and dynamic multicast (where membership of the multicast group changes in time, with nodes joining and leaving the group). For static multicast, we reduce the problem to a polynomial-time solvable optimization problem, and we present decentralized algorithms for solving it. These algorithms, when coupled with existing decentralized schemes for constructing network codes, yield a fully decentralized approach for achieving minimum-cost multicast. By contrast, establishing minimum-cost static multicast connections over routed packet networks is a very difficult problem even using centralized computation, except in the special cases of unicast and broadcast connections. For dynamic multicast, we reduce the problem to a dynamic programming problem and apply the theory of dynamic programming to suggest how it may be solved

Networked Slepian-Wolf: theory, algorithms, and scaling laws

Consider a set of correlated sources located at the nodes of a network, and a set of sinks that are the destinations for some of the sources. The minimization of cost functions which are the product of a function of the rate and a function of the path weight is considered, for both the data-gathering scenario, which is relevant in sensor networks, and general traffic matrices, relevant for general networks. The minimization is achieved by jointly optimizing a) the transmission structure, which is shown to consist in general of a superposition of trees, and b) the rate allocation across the source nodes, which is done by Slepian-Wolf coding. The overall minimization can be achieved in two concatenated steps. First, the optimal transmission structure is found, which in general amounts to finding a Steiner tree, and second, the optimal rate allocation is obtained by solving an optimization problem with cost weights determined by the given optimal transmission structure, and with linear constraints given by the Slepian-Wolf rate region. For the case of data gathering, the optimal transmission structure is fully characterized and a closed-form solution for the optimal rate allocation is provided. For the general case of an arbitrary traffic matrix, the problem of finding the optimal transmission structure is NP-complete. For large networks, in some simplified scenarios, the total costs associated with Slepian-Wolf coding and explicit communication (conditional encoding based on explicitly communicated side information) are compared. Finally, the design of decentralized algorithms for the optimal rate allocation is analyzed