Bruce Fette

Wireless distributed computing: a survey of research challenges

Recent advancements in radio technology provide great flexibility and enhanced capabilities in executing wireless services. One of these capabilities that can provide significant advantages over traditional approaches is the concept of collaborative computing in wireless networks. With collaborative radio nodes, multiple independent radio nodes operate together to form a wireless distributed computing (WDC) network with significantly increased performance, operating efficiency, and abilities over a single node. WDC exploits wireless connectivity to share processing- intensive tasks among multiple devices. The goals are to reduce per-node and network resource requirements, and enable complex applications not otherwise possible, e.g., image processing in a network of small form factor radio nodes. As discussed in this article, WDC research aims to quantify the benefits of distributed processing over local processing, extend traditional distributed computing (DC) approaches to allow operation in dynamic radio environments, and meet design and implementation challenges unique to WDC with the help of recently available enabling technologies, such as software radios and cognitive radios.

Distributed scheduler design for multiuser detection enabled wireless mobile ad-hoc networks

There is a need for military and commercial wireless radio networks that can operate in dynamic environments while supporting high spectral efficiency with throughput guarantees and low latency. This is particularly challenging in wireless mobile ad-hoc networks (MANET). Multiuser detection (MUD) technology promises to address these needs. But most research in MUD technology to date has focused on the physical layer (PHY) challenges with little attention being paid to design of efficient MUD scheduler in medium access control layer (MAC). Our research described in this paper presents a distributed scheduler that addresses many challenging issues associated with a wireless MANET such as dynamic allocation of resources, handling of hidden and exposed nodes, QoS, and scalability. In particular, our research shows that the exposed node problem in MUD enabled radio systems is different from that in conventional interference avoidance systems. We provide guidelines to resolve this problem. Some simulation results are presented. The scheduler design is used in the DARPA Interference Multiple Access (DEVIA) communications program.

Fourteen Years of Cognitive Radio Development

Cognitive Radio principles were first described at a Keynote Speech by Dr. Joseph Mitola at the IEEE ICASSP Conference in Phoenix in 1999. In this talk Mitola described the principles of a Radio that could help its user to do many things. The vision includes a radio with an understanding of numerous domains ranging from the users daily routine to an understanding of how to find and efficiently use spectrum and avoid interference. This paper will review Cognitive Radio principles explored by the commercial and defense communities, assessing progress made in the many potential dimensions of Cognitive Radio as an assistant to the radio user. We will utilize the DARPA developed Advanced Wireless Network System / Wireless Network after Next (AWNS/WNaN) radio system and network as the example of a Cognitive Radio capability that provides high levels of adaptivity to the communications radio frequency (RF) environment and the warfighters mission.

Multiuser detection enabled medium access control in mobile ad hoc networks

Increasing spectral efficiency has been a constant challenge in wireless communications. Many military and commercial applications require that wireless networks operate in dynamic environments and provide high data rates. Multiuser detection (MUD) has been demonstrated to increase spectral efficiency by increasing spectrum reuse. Most MUD research to date has focused on the physical layer (PHY) technology. Our research has focused on design of an efficient wireless media access controller (MAC) for MUD enabled mobile ad-hoc networks (MANET). Beyond MUD, other issues addressed in this design include overhead efficiency, optimization of dynamic resource allocation, and support for dense topologies, mobility, scalability, and Quality of Service (QoS). The MAC design is used in the DARPA Interference Multiple Access (DEVIA) communications program. In this paper, a frame structure and architecture of the MAC design are presented. Technical challenges are discussed and motivating factors behind the design are highlighted. The MAC described in this paper has been prototyped and demonstrated in laboratory environment and field trial. Some test results are presented.

A 600 bps LPC voice coder

The authors describe a 600 bit/s vocoder that is based on the LPC-10 (linear prediction coding) vocoder model. The coder operates on the principle of selecting a point on the 600 bit/s rate distortion bound that is optimal given the rate of spectral change within a four-frame superframe of speech. The authors describe the tradeoffs in spectral coding, pitch coding, voice encoding, RMS encoding, synchronization, and forward error correction. The perceptual weighting criteria used are shown to select reasonable operating points on the rate distortion bound as speech spectra change from quasi-stationary to rapidly dynamic.<<ETX>>

PHY and MAC Design for Distributed Tx-Rx beamforming in Mobile Ad Hoc Networks

This paper studies physical (PHY) and MAC layer design for multi-antenna based mobile ad hoc networks (MANET). The central piece of the PHY layer design is a distributed transmit-receive (Tx-Rx) beam forming algorithm named the minimum interference leakage (MIL) beam former. With this algorithm, each pair of Tx-Rx nodes aims at maximizing the throughput of their own link while minimizing the interference leakage to the unintended ones. Besides the beam forming algorithm are other PHY functions, such as link selection and adaptation, and closed-loop power control (CLPC). To enable such a PHY design, we propose a slotted ALOHA-like MAC frame structure, based on which the PHY functional blocks can work in synergy to dramatically improve the network spectral efficiency. The simulation results show that the proposed design has nearly 100x gain over the single antenna baseline system using TDMA with QPSK rate 1/2, measured by the network area spectral efficiency.

Power aware scheduling and power control techniques for multiuser detection enabled wireless mobile ad-hoc networks

Multiuser Detection (MUD) based receivers theoretically require no power control (PC) as they have the ability to separate signals regardless of their relative power levels as long as these signals achieve a suitable SNR. In practice, receiver designs have finite dynamic range. In this paper, power aware scheduling (PAS) and power control (PC) algorithms are investigated to address the finite MUD dynamic range and performance results are shown. The final PAS algorithm and motivating factors behind the design selections made on the DARPA Interference Multiple Access (DIMA) program are highlighted as well as different approaches involving both scheduling and PC. The techniques selected on the DIMA program are currently operating as part of the DEVIA mobile real-time experiments.

Increasing Network Area Spectral Efficiency by combining multiple PHY techniques

Physical Layer (PHY) techniques such as Spatial Multiplexing, Eigen Beamforming, Eigen Beamnulling, Power Control, Spectrum Segmentation and Link Adaptation have been proved effective in improving the Network Area Spectral Efficiency of ad hoc networks. Several works have focused on optimizing the parameters of these PHY techniques individually to maximize different components of the Network Area Spectral Efficiency using an analytical approach. However, the impact of combining these PHY techniques has not been well studied. Moreover, it remains to be seen what kind of tradeoffs exist in a realistic scenario where the the parameters of the PHY techniques need to be selected in a distributed manner and there might not be scope for complex optimization. We use a heuristic based approach to combine these six PHY techniques in a distributed manner, and analyze the performance of the network in the presence of practical non-idealities. Simulation results indicate that the gain in network area spectral efficiency achieved by combining these PHY techniques is additive, and is atleast 3x better than any of the PHY techniques in isolation.

Improving Spectral Efficiency of MIMO Ad Hoc Network via Greedy MCS Packing

This paper presents a solution for improving the network spectral efficiency (NSE) of a MIMO ad hoc network by simultaneously increasing the number of concurrent links in the network while maximizing the spectral efficiency of each. Our approach combines multiple physical layer techniques and balances the trade-offs of them. Assuming only the channel state information to the intended receiver, a two-level iterative algorithm is designed and presented. The inner loop uses an algorithm, which we refer to as the greedy MCS packing(GMP), generates the generalized (eigen-) beam forming, performs power allocation and chooses proper modulation and coding scheme (MCS). The GMP attempts to maximize the rate while packing them in as few eigen-channels as possible. The outer loop is used for frequency sub-band selection. It uses a heuristic algorithm to choose the number of spectral segments used by each TX-RX pair to further reduce overall network interference. Simulation results show that our algorithm yields as much as 71% improvement over a related previous work, which also combines multiple MIMO techniques and considers finite MCS rate with imperfect channel information. We further investigate the improvements in network spectral efficiency (NSE) when our baseline GMP approach is augmented by nonlinear Successive Interference Cancellation (SIC) at the receiver. While the NSE gain brought by this SIC-enhanced receiver is quite limited, our simulation shows that more concurrent links can be supported compared with GMP scheme using an MMSE receiver.

Polarization-based zero forcing suppression with multiple degrees of freedom

Polarization-based suppression with zero forcing (ZF) is limited by similarities in the polarization-frequency response of the desired and interference signals. At subcarriers where the responses are similar, suppression of the interference also leads to suppression of the desired signal, and achievable cancellation ratios are correspondingly limited. A measure called the polarization power coupling (PPC) function is introduced for determining the impact of ZF on desired signal suppression. The PPC function provides a useful measure for predicting the magnitude of the suppression of the desired signal as a function of the subcarrier frequency. We consider the use of an additional degree of freedom (DOF), e.g., with a partially correlated or uncorrelated PPC response, to provide diversity detection for improving symbol error rate (SER) performance associated with recovery of the desired signal. The approach employs suppression diversity on a subcarrier-by-subcarrier basis and uses the PPC function to identify the ZF filter response leading to a better estimate of the desired signal symbols in each subcarrier. The method is shown to provide reduced suppression of the desired signal and to improved SER performance. An alternative use of the additional DOF is considered for suppression of a second source in a two-stage processing scheme, and a receiver architecture is proposed that exploits the diversity and suppression extensions enabled by an additional degree of freedom.