Canming Jiang

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.

An optimal link layer model for multi-hop MIMO networks

The rapid advances of MIMO to date have mainly stayed at the physical layer. Such fruits have not been fully benefited at the network layer mainly due to the computational complexity associated with the matrix-based model that MIMO involves. Recently, there are some efforts to simplify link layer model for MIMO so as to ease research for the upper layers. These models only require numeric computations on MIMOs degrees-of-freedom (DoFs) for spatial multiplexing (SM) and interference cancellation (IC) to obtain a feasible rate region. Thus, these models are much simpler than the original matrix-based model from the communications world. However, none of these DoF-based models is shown to achieve the same rate region as that by the matrix-based model. In this paper, we re-visit this important problem of MIMO modeling. Based on accurate accounting of how DoFs are consumed, we develop a simple link layer model for multi-hop MIMO networks. We show that this model is optimal in the sense of achieving the same rate region as that by the matrix-based model under SM and IC for any network topology. This work offers an important building block for theoretical research on multi-hop MIMO networks.

On the Asymptotic Capacity of Multi-Hop MIMO Ad Hoc Networks

Multi-input multi-output (MIMO) is a key technology to increase the capacity of wireless networks. Although there has been extensive work on MIMO at the physical and link layers, there is limited work on MIMO at the network layer (i.e., multi-hop MIMO network), particularly results on capacity scaling laws. In this paper, we investigate capacity scaling laws for MIMO ad hoc networks. Our goal is to find the achievable throughput of each node as the number of nodes in the network increases. We employ a MIMO network model that captures spatial multiplexing and interference cancellation. We show that for a MIMO network with n randomly located nodes, each equipped with α antennas and a rate of W on each data stream, the achievable throughput of each node is Θ(αW/√(n ln n)).

On optimal throughput-energy curve for multi-hop wireless networks

Network throughput and energy consumption are two important performance metrics for a multi-hop wireless network. Current state-of-the-art is limited to either maximizing throughput under some energy constraint or minimizing energy consumption while satisfying some throughput requirement. In this paper, we take a multicriteria optimization approach to offer a systematic study on the relationship between the two performance objectives. We show that the solution to the multicriteria optimization problem is equivalent to finding an optimal throughput-energy curve, which characterizes the envelope of the entire throughput-energy region. We prove some important properties of the optimal throughput-energy curve. For case study, we consider both linear and nonlinear throughput functions. In the linear case, we characterize the optimal throughput-energy curve precisely through parametric analysis, while in the nonlinear case, we use a piece-wise linear approximation to approximate the optimal throughput-energy curve with arbitrary accuracy. Our results offer important insights on exploiting the trade-off between the two performance metrics.

A DoF-Based Link Layer Model for Multi-Hop MIMO Networks

The rapid advances of MIMO to date have mainly stayed at the physical layer. Such fruits have not fully benefited MIMO research at the network layer mainly due to the computational complexity associated with the matrix-based model that MIMO involves. Recently, there have been some efforts to simplify link layer model for MIMO so as to facilitate research at the upper layers. These models only require simple numeric computations on MIMOs degrees-of-freedom (DoFs) to characterize spatial multiplexing (SM) and interference cancellation (IC). Thus, these models are much simpler than the original matrix-based model from the communications world. However, achievable DoF regions of these DoF-based models are not analyzed. In this paper, we re-visit this important problem of MIMO modeling. Based on accounting of how DoFs are consumed for SM and IC, we develop a tractable link layer model for multi-hop MIMO networks. We show that under common assumptions of DoF-based models and additional assumption of no dependency cycle, this model includes all the feasible solutions by the matrix-based model under SM and IC for any network topology. This work offers an important building block for theoretical research on multi-hop MIMO networks.

Toward simple criteria to establish capacity scaling laws for wireless networks

Capacity scaling laws offer fundamental understanding on the trend of user throughput behavior when the network size increases. Since the seminal work of Gupta and Kumar, there have been active research efforts in developing capacity scaling laws for ad hoc networks under various advanced physical layer technologies. These efforts led to many custom-designed solutions, most of which were intellectually challenging and lacked universal properties that can be extended to address scaling laws of ad hoc networks with other physical layer technologies. In this paper, we present a set of simple yet powerful tool that can be applied to quickly determine the capacity scaling laws for various physical layer technologies under the protocol model. We prove the correctness of our proposed criteria and demonstrate their usage through a number of case studies, such as ad hoc networks with directional antenna, MIMO, multi-channel multi-radio, cognitive radio, and multiple packet reception. These simple criteria will serve as powerful tools to networking researchers to obtain throughput scaling laws of ad hoc networks under different physical layer technologies, particularly those to be developed in the future.

On Capacity Scaling Law of Cognitive Radio Ad Hoc Networks

Cognitive radio is envisioned to be an enabling radio technology for future wireless networks. In this paper, we study the capacity scaling laws for cognitive radio ad hoc networks (CRNs), i.e., how each individual nodes capacity scales as the number of nodes in the network increases. This effort is critical to the fundamental understanding of the scalability of such network. However, due to the heterogeneity in available frequency bands at each node, the asymptotic capacity is much more difficult to develop than prior efforts for other types of wireless networks. To overcome this difficulty, we introduce two auxiliary networks

Toward Transparent Coexistence for Multihop Secondary Cognitive Radio Networks

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Throughput Maximization for Multi-Hop Wireless Networks with Network-Wide Energy Constraint

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Cherish every joule: Maximizing throughput with an eye on network-wide energy consumption

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