Sastry Kompella

An optimal algorithm for relay node assignment in cooperative ad hoc networks

Recently, cooperative communications, in the form of having each node equipped with a single antenna and exploit spatial diversity via some relay nodes antenna, is shown to be a promising approach to increase data rates in wireless networks. Under this communication paradigm, the choice of a relay node (among a set of available relay nodes) is critical in the overall network performance. In this paper, we study the relay node assignment problem in a cooperative ad hoc network environment, where multiple source-destination pairs compete for the same pool of relay nodes in the network. Our objective is to assign the available relay nodes to different source-destination pairs so as to maximize the minimum data rate among all pairs. The main contribution of this paper is the development of an optimal polynomial time algorithm, called ORA, that achieves this objective. A novel idea in this algorithm is a “linear marking” mechanism, which maintains linear complexity of each iteration. We give a formal proof of optimality for ORA and use numerical results to demonstrate its capability.

Cooperative Communications in Multi-hop Wireless Networks: Joint Flow Routing and Relay Node Assignment

It has been shown that cooperative communications (CC) have the potential to significantly increase the capacity of wireless networks. However, most of the existing results are limited to single-hop wireless networks. To illustrate the benefits of CC in multi-hop wireless networks, we solve a joint optimization problem of relay node assignment and flow routing for concurrent sessions. We study this problem via mathematical modeling and solve it using a solution procedure based on the branch-and-cut framework. We design several novel components to speed-up the computation time of branch-and-cut. Via numerical results, we show the significant rate gains that can be achieved by incorporating CC in multi-hop networks.

Maximizing Capacity in Multihop Cognitive Radio Networks under the SINR Model

Cognitive radio networks (CRNs) have the potential to utilize spectrum efficiently and are positioned to be the core technology for the next-generation multihop wireless networks. An important problem for such networks is its capacity. We study this problem for CRNs in the SINR (signal-to-interference-and-noise-ratio) model, which is considered to be a better characterization of interference (but also more difficult to analyze) than disk graph model. The main difficulties of this problem are two-fold. First, SINR is a nonconvex function of transmission powers; an optimization problem in the SINR model is usually a nonconvex program and NP-hard in general. Second, in the SINR model, scheduling feasibility and the maximum allowed flow rate on each link are determined by SINR at the physical layer. To maximize capacity, it is essential to follow a cross-layer approach, but joint optimization at physical (power control), link (scheduling), and network (flow routing) layers with the SINR function is inherently difficult. In this paper, we give a mathematical characterization of the joint relationship among these layers. We devise a solution procedure that provides a (1- \varepsilon ) optimal solution to this complex problem, where \varepsilon is the required accuracy. Our theoretical result offers a performance benchmark for any other algorithms developed for practical implementation. Using numerical results, we demonstrate the efficacy of the solution procedure and offer quantitative understanding on the interaction of power control, scheduling, and flow routing in a CRN.

Stable throughput tradeoffs in cognitive shared channels with cooperative relaying

This paper addresses fundamental issues in a shared channel where the users have different priority levels. In particular, we characterize the stable-throughput region in a two user cognitive shared channel where the primary (higher priority) user transmits whenever it has packets to transmit while the secondary (cognitive) node transmits its packets with probability p. Therefore, in this system, the secondary link is allowed to share the channel along with the primary link, in contrast to the traditional notion of cognitive radio, in which the secondary user is required to relinquish the channel as soon as the primary is detected. The analysis also takes into account the compound effects of multi-packet reception as well as of the relaying capability on the stability region of the network. We start by analyzing the non-cooperation case where nodes transmit their own packets to their respective destinations. We then extend the analysis to a system where the secondary node cooperatively relays some of the primarys packets. Specifically, in the cooperation case, the secondary node relays those packets that it receives successfully from the primary, but are not decoded properly by the primary destination. In such cognitive shared channels, a tradeoff arises in terms of activating the secondary along with the primary so that both transmissions may be successful, but with a lower probability, compared to the case of the secondary node staying idle when the primary user transmits. Results show the benefits of relaying for both the primary as well as the secondary nodes in terms of the stable-throughput region.

On path selection and rate allocation for video in wireless mesh networks

Multi-path transport is an important mechanism for supporting video communications in multihop wireless networks. In this paper, we investigate the joint problem of optimal path selection and rate allocation for multiple video sessions in a wireless mesh network. We present a mathematical formulation to optimize the application level performance (i.e., video distortion) in the context of path selection and rate allocation. For this complex optimization problem, we propose a branch-and-bound based solution procedure, embedded with the reformulation-linearization technique (RLT) that can produce (1-epsiv)-optimal solutions for any small epsiv . This result is significant as it not only provides theoretical understanding of this problem, but also offers a performance benchmark for any future proposed distributed algorithm and protocol for this problem. Simulation results are also provided to demonstrate the efficacy of the solution procedure.

Cross-layer optimized multipath routing for video communications in wireless networks

Traditionally, routing is considered solely as a network layer problem and has been decoupled from application layer objectives. Although such an approach offers simplicity in the design of the protocol stack, it does not offer good performance for certain applications such as video. In this paper, we explore the problem of how to perform routing with the objective of optimizing application layer performance. Specifically, we consider how to perform multipath routing for multiple description (MD) video in a multi-hop wireless network. We formulate this problem into an optimization problem with application performance metric as the objective function and routing and link layer considerations as constraints. We develop a formal branch-and-bound framework and exploit the so-called reformulation-linearization technique (RLT) in the solution procedure. We show that this solution procedure is able to produce a set of routes whose objective value is within (1 - e) of the optimum. We use simulation results to substantiate the efficacy of the solution procedure and compare the performance with that under non-cross-layer approach.

On optimal SINR-based scheduling in multihop wireless networks

In this paper, we revisit the problem of determining the minimum-length schedule that satisfies certain traffic demands in a wireless network. Traditional approaches for the determination of minimum-length schedules are based on a collision channel model, in which neighboring transmissions cause destructive interference if and only if they are within the “interference region” of the receiving nodes. By contrast, we adopt here a more realistic model for the physical layer by requiring that a threshold be exceeded by the signal-to-interference-plus-noise ratio (SINR) for a transmission to be successful. We present a novel formulation of the problem that incorporates various power and rate adaptation schemes while seamlessly integrating the generation of “matchings” (i.e., sets of links that can be activated simultaneously) by taking into consideration the SINR constraints at the receivers. For the formulated problem, we propose a column-generation-based solution method and show that it theoretically converges to a globally optimal solution, with a potential advantage of not having to enumerate all the feasible matchings a priori. We also discuss the influence of power control, spatial reuse, and variable transmission rates on network performance. Furthermore, we include aspects of the routing problem and provide computational results for our proposed column-generation-based solution procedure.

Age of information under random updates

We consider the system where a source randomly generates status update messages and transmits them via a network cloud to the intended destination. These update message can take different times to traverse the network, which we model as exponential service times, and may result in packets reaching the destination out of order, rendering some of the earlier transmissions obsolete. We analyze the status update age for such a system, and show that it tracks well with simulation results.

Squeezing the most out of interference: An optimization framework for joint interference exploitation and avoidance

There is a growing interest in exploiting interference (rather than avoiding it) to increase network throughput. In particular, the so-called successive interference cancellation (SIC) scheme appears very promising, due to its ability to enable concurrent receptions from multiple transmitters as well as interference rejection. Although SIC has been extensively studied as a physical layer technology, its research and advances in the context of multi-hop wireless network remain limited. In this paper, we try to answer the following fundamental questions. What are the limitations of SIC? How to overcome such limitations? How to optimize the interaction between SIC and interference avoidance? How to incorporate multiple layers (physical, link, and network) in an optimization framework? We find that SIC alone is not adequate to handle interference in a multi-hop wireless network, and advocate the use of joint SIC and interference avoidance. To optimize a joint scheme, we propose a cross-layer optimization framework that incorporates variables at physical, link, and network layers. This is the first work that combines successive interference cancellation and interference avoidance in multi-hop wireless network. We use numerical results to affirm the validity of our optimization framework and give insights on how SIC and interference avoidance can complement each other in an optimal manner.

Is Network Coding Always Good for Cooperative Communications

Network coding (NC) is a promising approach to reduce time-slot overhead for cooperative communications (CC) in a multi-session environment. Most of the existing works take advantage of the benefits of NC in CC but do not fully recognize its potential adverse effect. In this paper, we show that employing NC may not always benefit CC. We substantiate this important finding in the context of analog network coding (ANC) and amplify-and-forward (AF) CC. This paper, for the first time, introduces an important concept of network coding noise (NC noise). Specifically, we analyze the signal aggregation at a relay node and signal extraction at a destination node. We then use the analysis to derive a closed-form expression for NC noise at each destination node in a multi-session environment. We show that NC noise can diminish the advantage of NC in CC. Our results formalizes an important concept on using NC in CC.