R. Michael Buehrer

Linear versus non-linear interference cancellation

In this paper we compare linear and non-linear interference cancellation for systems employing code division multiple access (CDMA) techniques. Specifically, we examine linear and non-linear parallel interference cancellation (also called multistage cancellation) in relationship to other multiuser detection algorithms. We show the explicit relationship between parallel interference cancellation and the decorrelator (or direct matrix inversion). This comparison gives insight into the performance of parallel interference cancellation (PIC) and leads to better approaches. We also show that non-linear PIC approaches with explicit channel estimation can provide performance improvement over linear PIC, especially when using soft non-linear symbol estimates. The application of interference cancellation to non-linear modulation techniques is also presented along with a discussion on minimum mean-squared error (MMSE) symbol estimation techniques. These are shown to further improve the performance of parallel cancellation.

Location Estimation Using Differential RSS with Spatially Correlated Shadowing

In this paper, we propose a new localization technique using differential received signal strength (DRSS) which does not require signal source cooperation for location estimation. Specifically, we introduce a DRSS-based localization framework as well as its geometric interpretation for both local and global positioning to facilitate understanding of the approach. Then, a least-squares (LS) optimization framework is formulated for DRSS-based location estimation (DRLE) which makes full use of the DRSS measurements available. Our study shows that the localization performance of DRLE and its RSS-based counterpart (RLE) is substantially affected by spatially correlated shadow fading under which their localization behaviors are found to be different. Finally, we argue that DRLE has practical advantages over other positioning techniques, and show that its location accuracy is comparable or even superior to RLE.

Code Division Multiple Access (CDMA)

Abstract This book covers the basic aspects of Code Division Multiple Access or CDMA. It begins with an introduction to the basic ideas behind fixed and random access systems in order to demonstrate the difference between CDMA and the more widely understood TDMA, FDMA or CSMA. Secondly, a review of basic spread spectrum techniques are presented which are used in CDMA systems including direct sequence, frequency-hopping and time-hopping approaches. The basic concept of CDMA is presented, followed by the four basic principles of CDMA systems that impact their performance: interference averaging, universal frequency reuse, soft handoff, and statistical multiplexing. The focus of the discussion will then shift to applications. The most common application of CDMA currently is cellular systems. A detailed discussion on cellular voice systems based on CDMA, specifically IS-95, is presented. The capacity of such systems will be examined as well as performance enhancement techniques such as coding and spatial filt...

Cognitive Engine Design for Link Adaptation: An Application to Multi-Antenna Systems

In this paper, we present a Cognitive Engine (CE) design for link adaptation and apply it to a system which can adapt its use of multiple antennas in addition to modulation and coding. Our design moves forward the state of the art in several ways while having a simple structure. Specifically, the CE only needs to observe the number of successes and failures associated with each set of channel conditions and communication method. From these two numbers, the CE can derive all of its functionality. First, it can estimate confidence intervals of the packet success rate (PSR) using the Beta distribution. A low computational approximation to the CDF of the Beta distribution is also presented. Second, the designed CE balances the tradeoff between learning and short-term performance (exploration {vs.} exploitation) by applying the Gittins index. Third, the CE learns the radio abilities independently of the operation objectives. Thus, if an objective changes, information regarding the radios abilities is not lost. Finally, prior knowledge such as capacity, BER curves, and basic communication principles are used to both initialize the CEs knowledge and maximize the learning rate across different channel conditions. The proposed CE is demonstrated to have the ability to learn in a dynamic scenario and quickly approach maximal performance.

Impact of exclusion region and spreading in spectrum-sharing ad hoc networks

In wireless ad hoc network medium access control (MAC) protocol design, it is important to incorporate an exclusion region around a receiver, such that nodes inside the exclusion region are not allowed to transmit, to limit the interference caused to the receiver. In this paper, we investigate the performance trends of a spread-spectrum-based network with respect to outage constraints and derive its relationship with the size of the exclusion region and the spreading factor. A non-spread-spectrum-based network is a special case with a spreading factor of one. We show that there exists an optimal size for the exclusion region with respect to maximizing the performance of the network which depends upon the spreading factor used in the network. It is also shown that the throughput of the network degrades while the throughput of individual users improves with an increase in spreading factor. These results are used to show that spectrum-sharing (SS) schemes based on interference-avoidance are desirable from a network performance perspective while interference-averaging-based SS schemes are desirable from the perspective of the performance of individual users.

Asynchronous time-of-arrival-based source localization

In this paper, asynchronous wireless source localization using time-of-arrival (TOA) measurements is studied. In TOA localization, the travel time of the signal between the source node and anchor nodes is measured and used to estimate range. In synchronous networks, the anchor nodes know when the source node starts transmission. In asynchronous networks, however, the source transmit time is unknown and TOA measurements have a positive bias due to the synchronization error which could lead to a large localization error. One way to tackle this problem is to use time-difference-of-arrival (TDOA) measurements which do not depend on the source transmission time. However, in this work, applying an alternative approach, we estimate the source transmit time as a nuisance parameter jointly with the source location. The optimal maximum likelihood (ML) estimator is derived. To avoid the ML convergence problem, a novel semidefinite programming (SDP) technique is proposed by converting the noncovex ML problem into a convex one. Computer simulations showing superior performance of the proposed SDP estimator are conducted.

Improving positioning in LTE through collaboration

This paper represents a preliminary study of cooperative positioning in Long Term Evolution (LTE) systems. Many applications, such as location-based services and Enhanced 911 (E911), require that the locations of users in a cellular system are available. The global navigation satellite system (GNSS) is the most accessible positioning systems which are widely used in cellphones. However, poor operation in indoor and dense environments leads us to use cellular localization as a backup solution. In cellular localization, the locations of users are determined via measurements obtained within the network without aid of any external sources (e.g., GNSS). Observed time difference of arrival (OTDOA) is a positioning technique introduced in Release 9 of the 3GPP LTE specification. In OTDOA technique, the User Equipment (UE) measures the time difference of signals between several eNodeBs (base stations in LTE) and uses a trilateration algorithm to find its location. In the current 3GPP LTE specification, the UE can only collect measurements from eNodeBs. Therefore, in many situations, the UE is not able to communicate to a sufficient number of eNodeBs and cannot find its location without ambiguity. In this paper, we propose a cooperative localization technique for LTE systems in which the UE communicates not only with eNodeBs but also with other UEs. It will be shown that cooperative localization can significantly improve the localizability in the network, meaning that more UEs can be localized. Cooperative localization also enhances the accuracy which is highly beneficial for some applications, especially E911. A series of computer simulations are conducted to show the benefits of cooperative localization where the 3GPP simulation parameters are assumed.

Cooperative sensor localization with NLOS mitigation using semidefinite programming

Cooperative time-of-arrival-based sensor localization in a non-line-of-sight (NLOS) environment is investigated. Cooperative sensor localization plays an important role in indoor networks where GPS is limited. However, indoor networks suffer from NLOS propagation which degrades localization accuracy significantly. In this paper, we assume that the estimator is able to discriminate NLOS connections from line-of-sight (LOS) connections. We introduce a novel semidefinite programming (SDP) approach for cooperative localization which exploits NLOS connections to enhance the accuracy of localization. The performance of the proposed algorithm is compared with that of the maximum likelihood estimator and previously considered algorithms. Computer simulations show the excellent performance of the proposed SDP approach.

Improving GPS-based vehicle positioning for Intelligent Transportation Systems

Intelligent Transportation Systems (ITS) have emerged to utilize different technologies to enhance the performance and quality of transportation networks. Many applications of ITS need to have a highly accurate location information from the vehicles in a network. The Global Positioning System (GPS) is the most common and accessible technique for vehicle localization. However, conventional localization techniques which mostly rely on GPS technology are not able to provide reliable positioning accuracy in all situations. This paper presents an integrated localization algorithm that exploits all possible data from different resources including GPS, radio-frequency identification, vehicle-to-vehicle and vehicle-to-infrastructure communications, and dead reckoning. A localization algorithm is also introduced which only utilizes those resources that are most useful when several resources are available. A close-to-real-world scenario has been developed to evaluate the performance of the proposed algorithms under different situations. Simulation results show that using the proposed algorithms the vehicles can improve localization accuracy significantly in situations when GPS is weak.

Toward a Tractable Analysis of Localization Fundamentals in Cellular Networks

When dedicated positioning systems, such as GPS, are unavailable, a mobile device has no choice but to fall back on its cellular network for localization. Due to random variations in the channel conditions to its surrounding base stations (BS), the mobile device is likely to face a mix of both favorable and unfavorable geometries for localization. Analytical studies of localization performance (e.g., using the Cramér-Rao lower bound) usually require that one fix the BS geometry, and favorable geometries have always been the preferred choice in the literature. However, not only are the resulting analytical results constrained to the selected geometry, this practice is likely to lead to overly-optimistic expectations of typical localization performance. Ideally, localization performance should be studied across all possible geometric setups, thereby also removing any selection bias. This, however, is known to be hard and has been carried out only in simulation. In this paper, we develop a new tractable approach where we endow the BS locations with a distribution by modeling them as a Poisson point process (PPP), and use tools from stochastic geometry to obtain easy-to-use expressions for key performance metrics. In particular, we focus on the probability of detecting some minimum number of BSs, which is shown to be closely coupled with a network operators ability to obtain satisfactory localization performance (e.g., meet FCC E911 requirements). This metric is indifferent to the localization technique (e.g., TOA, TDOA, AOA, or hybrids thereof), though different techniques will presumably lead to different BS hearability requirements. In order to mitigate excessive interference due to the presence of dominant interferers in the form of other BSs, we incorporate both BS coordination and frequency reuse in the proposed framework and quantify the resulting performance gains analytically.