Search

We summarize recent contributions in the broad area of age of information (AoI). In particular, we describe the current state of the art in the design and optimization of low-latency cyberphysical systems and applications in which sources send time-stamped status updates to interested recipients. These applications desire status updates at the recipients to be as timely as possible; however, this is typically constrained by limited system resources. We describe AoI timeliness metrics and present general methods of AoI evaluation analysis that are applicable to a wide variety of sources and systems. Starting from elementary single-server queues, we apply these AoI methods to a range of increasingly complex systems, including energy harvesting sensors transmitting over noisy channels, parallel server systems, queueing networks, and various single-hop and multi-hop wireless networks. We also explore how update age is related to MMSE methods of sampling, estimation and control of stochastic processes. The paper concludes with a review of efforts to employ age optimization in cyberphysical applications.

With the emergence of real-time cyberphysical systems, status updates are becoming an important form of communication. Vehicular messaging, security reports from homes and offices, surveillance video, and video feedback from remote-controlled systems all represent status updates at networked monitors that need to be as timely as possible. However, this is typically constrained by limited network resources. This tension has led to the introduction of new performance metrics based on the Age of Information (AoI) that capture how timely is one’s knowledge of an entity or process. Optimization based on AoI metrics of both the networks and the senders’ updating policies has yielded new and even surprising results.

When receivers rely on stochastic energy harvesting, power outages will reduce the reliable communication rate. To model the receiver, we decompose the processing tasks in two parts: (1) sampling or Analog-to-Digital Conversion (ADC), which includes all RF front-end processing, and (2) decoding. This work considers a time-slotted system in which a source transmits coded packets through a time-invariant channel to a receiver with a finite battery and a decoder whose energy consumption can be adapted from slot to slot. Based on the relative energy costs of sampling and decoding and a stochastic model for the energy harvesting, we determine sampling and decoding policies that maximize the packet throughput. When the receiver is battery-constrained, we show that the throughput is maximized by a deferred decoding policy that samples packets at every opportunity but decodes backlogged packets using only excess energy that would otherwise be discarded. This result is shown to hold for Markov-modulated energy harvesting processes with arbitrary memory. In addition, when the average energy harvesting rate is not sufficient to decode all packets, a modified policy that defers decoding only when the backlog is below a threshold is shown to perform well when the threshold is carefully chosen.

Base stations with a large number of transmit antennas have the potential to serve a large number of users at high rates. However, the receiver processing in the uplink relies on channel estimates which are known to suffer from pilot interference. In this work, making use of the similarity of the uplink received signal in CDMA with that of a multi-cell multi-antenna system, we perform a large system analysis when the receiver employs an MMSE filter with a pilot contaminated estimate. We assume a Rayleigh fading channel with different received powers from users. We find the asymptotic Signal to Interference plus Noise Ratio (SINR) as the number of antennas and number of users per base station grow large while maintaining a fixed ratio. Through the SINR expression we explore the scenario where the number of users being served are comparable to the number of antennas at the base station. The SINR explicitly captures the effect of pilot contamination and is found to be the same as that employing a matched filter with a pilot contaminated estimate. We also find the exact expression for the interference suppression obtained using an MMSE filter which is an important factor when there are significant number of users in the system as compared to the number of antennas. In a typical set up, in terms of the five percentile SINR, the MMSE filter is shown to provide significant gains over matched filtering and is within 5 dB of MMSE filter with perfect channel estimate. Simulation results for achievable rates are close to large system limits for even a 10-antenna base station with 3 or more users per cell., Accepted for publication in IEEE Transactions on Wireless Communications

Resource sharing among mobile network operators is a promising way to tackle growing data demand by increasing capacity and reducing costs of network infrastructure deployment and operation. In this work, we evaluate sharing options that range from simple approaches that are feasible in the near-term on traditional infrastructure to complex methods that require specialized/virtualized infrastructure. We build a simulation testbed supporting two geographically overlapped 4G LTE macro cellular networks and model the sharing architecture/process between the network operators. We compare Capacity Sharing (CS) and Spectrum Sharing (SS) on traditional infrastructure and Virtualized Spectrum Sharing (VSS) and Virtualized PRB Sharing (VPS) on virtualized infrastructure under light, moderate and heavy user loading scenarios in collocated and noncollocated E-UTRAN deployment topologies. We also study these sharing options in conservative and aggressive sharing participation modes. Based on simulation results, we conclude that CS, a generalization of traditional roaming, is the best performing and simplest option, SS is least effective and that VSS and VPS perform better than spectrum sharing with added complexity.

Despite considerable progress, the capacity region of fading broadcast channels with channel state known at the receivers but unknown at the transmitter remains unresolved. We address this subject by introducing a layered erasure broadcast channel model in which each component channel has a state that specifies the received signal levels in an instance of a deterministic binary expansion channel. We find the capacity region of this class of broadcast channels. The capacity achieving strategy assigns each signal level to the user that derives the maximum weighted expected rate. The outer bound is based on a channel enhancement that creates a degraded broadcast channel for which the capacity region is known. This same approach is then used to find inner and outer bounds to the capacity region of fading Gaussian broadcast channels. The achievability scheme employs a superposition of binary inputs. For intermittent additive white Gaussian noise (AWGN) channels and for Rayleigh fading channels, the achievable rates are observed to be within 1-2 bits of the outer bound at high SNR. We also prove that the achievable rate region is within 6.386 bits/s/Hz of the capacity region for all fading AWGN broadcast channels.

We compare the performance of half-duplex relays in downlink cellular system against a baseline system without relays. We simulate the performance of (i) a collaborative power addition scheme, where the relay boosts the received power (P-CPA) at the mobile locations, and (ii) a CPA scheme with power control (PC-CPA) at the base station and relays. Evaluations are done in the context of a 19-cell, 57-sector set-up in which each of the served users must be delivered a message. The user messages are taken to have the same size and 90% of users in the network must be served. Improvements over the baseline due to relay deployments are measured in terms of increase in common rate of users as well as power savings in terms of reduction in peak or average power transmitted by base stations. In the CPA schemes with base stations and relays transmitting at full power, the peak power saving is 1.46 dB, alternately, the throughput improvement over a 1 bit/sec/Hz baseline rate is 21%. In the PC-CPA scheme, the peak power saving is 2.6 dB and the average total power in the system can be reduced by 3 dB.

We consider a secret communication scenario where Alice wants to transmit secretly to Bob in presence of a passive eavesdropper Eve. The Alice-Bob channel is a fixed-SNR AWGN channel, while the Alice-Eve channel is a fast Rayleigh fading channel, with the channel states only known to Eve. Alice knows the statistics of Alice-Eve channel, but not the exact realizations. We investigate the achievable secrecy rates for this channel model with Gaussian signaling and discrete signaling. For Gaussian signaling, several transmission strategies according to the main channel's relative channel gain are proposed and evaluated. For discrete signaling, achievable secrecy rates with Quadrature Amplitude Modulation (QAM) are evaluated. When Bob's channel is much better than Eve's channel, simple Gaussian signaling can perform close to the upper bound, and is better than the rate achieved with M-QAM. When Bob's channel gain is on average worse than the eavesdropper's average channel gain, positive secrecy rate can still be achieved for Gaussian signaling with artificial noise injection and a burst signaling strategy. Moreover, M-QAM can outperform Gaussian signaling. The key factor that enables secret communication in this case is that both M-QAM and artificial noise limit the leakage of information when Eve's channel is unusually good.

In a relay network with a single source-destination pair, we examine the achievable rates with amplify-and-forward (AF) relaying strategy. Motivated by applications in sensor networks, we consider power-constrained networks with large bandwidth resources and a large number of nodes. We show that the AF strategy does not necessarily benefit from the large available bandwidth. We characterize the optimum AF bandwidth and show that transmitting in the optimum bandwidth allows the network to operate in the linear regime where the achieved rate increases linearly with the available network power. We then present the optimum power allocation among the AF relays. The solution, which can be viewed as a form of maximum ratio combining, indicates the favorable relay positions in the network. Motivated by the large bandwidth resources we further consider a network that uses orthogonal transmissions at the nodes. While the above result for the optimum bandwidth still holds, a different set of relays should optimally be employed. In this case, the relay power solution can be viewed as a form of water-filling. The optimum AF bandwidth and the relay powers can be contrasted to the decode-and-forward (DF) solution. In a network with unconstrained bandwidth, the DF strategy will operate in the wideband regime to minimize the energy cost per information bit (S. Verdu, 2002), (O. Oyman et al., 2004). The wideband DF strategy requires again a different choice of relays; in the case of orthogonal signaling, the data should be sent through only one DF relay (I. Maric et al., 2004). Thus, in general, in a large scale network, a choice of a coding strategy goes beyond determining a coding scheme at a node; it also determines the operating bandwidth as well as the best distribution of the relay power.

The capacity of mobile Infostation network can be greatly increased, if, in addition to direct short-range communications between mobile nodes and fixed infostations, nodes also communicate amongst themselves whenever they meet. However, this requires cooperation among mobile nodes that are not necessarily spontaneous for commercial applications. We propose means to create opportunistic cooperation in the context of contention distribution in selfish mobile infostation networks. First, we assume that all nodes have a common interest in all files. We stipulate a social contract such that a bilateral file exchange takes place only when either node obtains something it wants from the exchange. Resulting capacity depends on mobility, the number of files being disseminated, and node density. In addition to the existence of multiuser diversity, our results indicate the existence of data diversity-throughput increases as the number of files of interest to all nodes increases. We also consider the case where nodes have dissimilar interests. Results show that as the level of interest overlap decreases, network performance degrades dramatically. We propose an alternate user strategy in the partially overlapping-interests case and show that network throughput is significantly improved by allowing better use of multiuser diversity. We conclude that through opportunistic cooperation, both data and multiuser diversities exist in noncooperative mobile infostation networks.

Dynamic allocation of spectrum prior to transmission is an important feature for next generation wireless networks. In this work, we develop and analyze a model for dynamic spectrum allocation, that is applicable for a broad class of practical systems. We consider multiple service providers (SPs), in the same geographic region, that share a fixed spectrum, on a non-interference basis. This spectrum is allocated to their customer end users for transmission to the SPs. Assuming that a user can obtain service from all the SPs, this work develops an efficient algorithm for spectrum allocation. The quality of service depends on system parameters such as number of users and SPs, the channel conditions between the users and SPs and the total transmit power of each user. The SPs have different efficiencies of reception. We adopt a user utility maximization framework to analyze this system. We develop the notion of spectrum price that enables a simple distributed spectrum allocation with minimal coordination among the SPs and users. Given the user utility functions and the system parameters, we characterize the spectrum price and the users' optimal bandwidth allocations. Our work provides theoretical bounds on performance limits of practical operator to user based dynamic spectrum allocation systems and also gives insights to actual system design.

Energy harvesting from the working environment has received increasing attention in the research of wireless sensor networks. Recent developments in this area can be used to replenish the power supply of sensors. However, power management is still a crucial issue for such networks due to the uncertainty of stochastic replenishment. In this paper, we propose a generic mathematical framework to characterize the policy for single hop transmission over a replenishable sensor network. Firstly, we introduce a Markov chain model to describe different modes of energy renewal. Then, we derive the optimal transmission policy for sensors with different energy budgets. Depending on the energy status of a sensor and the reward for successfully transmitting a message, we prove the existence of optimal thresholds that maximize the average reward rate. Our results are quite general since the reward values can be made application-specific for different design objectives. Compared with the unconditional transmit-all policy, which transmits every message as long as the energy storage is positive, the proposed optimal transmission policy is shown to achieve significant gains in the average reward rate.

Network simulation packages such as NS-2 and OPNET have been shown to be a limited option for cross-layer experimentation in wireless networking because they cannot faithfully capture the propagation and interference characteristics of wireless channels. Recent research on network cross-layer optimizations further raises this concern due to the close interaction between physical layer feedback and higher layer protocols. To overcome this shortcoming, wireless testbeds have been used wherein novel protocols and application concepts can be assessed in a realistic environment under controlled and repeatable conditions. Since average signal-to-noise-ratio (SNR) often determines the performance of a wireless link, our goal is to seek link SNR mapping methods that replicate real-world link SNRs onto an indoor testbed. Specifically, we devise and assess link SNR mapping methodologies for two different applications: hierarchical networks with a fixed access point (AP), and mesh networks. For the AP-based networks, we employ the minimum weight matching algorithm to minimize the root-mean-square (RMS) mapping error between the testbed and real-world SNRs. For the mesh networks, to avoid the technical difficulties inherent in ldquoforward mappingrdquo, we develop a ldquoreverse mappingrdquo method by which we turn a testbed configuration with specified link SNRs into a real-world configuration. By inducing the link gain difference between the testbed and the real-world distance-dependent path loss to have a log-normal distribution, a very close approximation to real-world shadow fading is achieved. We present results for a variety of indoor and outdoor real-world scenarios to demonstrate the generality of our method.

Capacity regions are established for several two-sender, two-receiver channels with partial transmitter cooperation. First, the capacity regions are determined for compound multiple-access channels (MACs) with common information and compound MACs with conferencing. Next, two interference channel models are considered: an interference channel with common information (ICCI) and an interference channel with unidirectional cooperation (ICUC) in which the message sent by one of the encoders is known to the other encoder. The capacity regions of both of these channels are determined when there is strong interference, i.e., the interference is such that both receivers can decode all messages with no rate penalty. The resulting capacity regions coincide with the capacity region of the compound MAC with common information.

We investigate optimum rate assignment scheme maximizing network throughput on the downlink of a multirate CDMA wireless network. Systems employing orthogonal variable spreading factor (OVSF) codes as well as systems employing multiple codes have been studied. Our objective is to maximize the network throughput under constraints on total transmit power, total bandwidth and individual QoS requirements specified in terms of minimum rates. First, users are ordered based on their transmit energy per bit requirements to achieve the target received energy per bit to interference power spectral density ratio at the receivers. Based on the initial ordering, we prove that for systems employing multiple codes, greedy rate assignment yields maximum network throughput. For systems employing variable spreading codes, we show that greedy rate assignment is optimal if the minimum rate requirement of a user is larger than or equal to the minimum rate requirement of any other user with a larger transmit energy per bit requirement. Simulation results verify the superiority of the greedy algorithm under various system and channel assumptions

This work examines a transmission system which adapts a finite set of code rates and a continuously varying transmit power. We propose a technique for finding the average reliable throughput (ART)-maximizing policy satisfying an average power constraint for a slow fading additive white Gaussian noise (AWGN) channel. ART is a measure motivated by the information outage and can, for example, be argued to characterize the long-term average throughput of a data packet transmission system with a transmit queue and a feedback protocol which requests retransmission of erroneously received packets. Given the size of the code rate set L, the ART-maximizing policy has the following properties. 1. For a given set of code rates, the optimum allocation policy suggests quantizing the fading state space into a set of L+1 corresponding intervals. For each quantization interval the optimal policy specifies a minimum transmitted power assignment which guarantees zero information outage. The optimum average power assignments across quantization intervals have a waterfilling relationship with respect to the interval channel quality measure. 2. The joint optimization of quantization intervals and the corresponding rate assignments are shown to have multiple local maxima. Nevertheless, this optimization problem can be reduced to a simple one-dimensional search over a parameter which determines the outage interval. Numerical results show that, in a Rayleigh-fading channel, there is only a 1-dB gap between the ergodic capacity and the throughput of a two-rate adaptive transmission system when the throughput is less than 6 bits/s/Hz. A special case of our optimal policy assignment is the optimal power and rate policy for an adaptive M-QAM system.

We address the minimum-energy broadcast problem under the assumption that nodes beyond the nominal range of a transmitter can collect the energy of unreliably received overheard signals. As a message is forwarded through the network, a node will have multiple opportunities to reliably receive the message by collecting energy during each retransmission. We refer to this cooperative strategy as accumulative broadcast. We seek to employ accumulative broadcast in a large scale loosely synchronized, low-power network. Therefore, we focus on distributed network layer approaches for accumulative broadcast in which loosely synchronized nodes use only local information. To further simplify the system architecture, we assume that nodes forward only reliably decoded messages. Under these assumptions, we formulate the minimum-energy accumulative broadcast problem. We present a solution employing two subproblems. First, we identify the ordering in which nodes should transmit. Second, we determine the optimum power levels for that ordering. While the second subproblem can be solved by means of linear programming, the ordering subproblem is found to be NP-complete. We devise a heuristic algorithm to find a good ordering. Simulation results show the performance of the algorithm to be close to optimum and a significant improvement over the well known BIP algorithm for constructing energy-efficient broadcast trees. We then formulate a distributed version of the accumulative broadcast algorithm that uses only local information at the nodes and has performance close to its centralized counterpart.

For a symbol-asynchronous (but chip-synchronous) single-cell code-division multiple-access (CDMA) system, we define a system-wide quantity called the total squared asynchronous correlation (TSAC) which, for arbitrary signature sets, depends on the users' delay profile. We develop a lower bound for TSAC that is independent of the users' delays. We show that if the signature set achieves this TSAC lower bound, then the user capacity of the asynchronous CDMA system using matched filters becomes the same as that of a single-cell synchronous CDMA system; in this case, there is no loss in user capacity due to asynchronism. We present iterative signature adaptation algorithms, which, when executed sequentially by the users, appear to converge to these optimum signature sequences; however, the existence, for all user delay profiles, of signature sequences achieving this lower bound remains a significant open problem.

Throughput maximization of an adaptive transmission system with a finite number of transmission power levels and code rates for communication over slow fading channels is analyzed, based on the concept of information outage. Properties of throughput maximizing policies lead to an iterative algorithm that yields good system designs. Numerical results show that carefully designed discrete adaptive transmission systems with a small number of power levels and code rates can achieve throughput values close to ergodic capacity.

This article combines the concepts of ergodic capacity and capacity versus outage for fading channels, and explores variable-rate transmissions under a service outage constraint in a block flat-fading channel model. A service outage occurs when the transmission rate is below a given basic rate. We solve the problem of maximizing the expected rate subject to the average power constraint and the service outage probability constraint. When the problem is feasible, the optimum power policy is shown to be a combination of water filling and channel inversion allocation, where the outage occurs at a set of channel states below a certain threshold. The service outage approach resolves the conflicting objectives of high average rate and low outage probability.

For a multicell code-division multiple-access (CDMA) system, we propose a partial decorrelator that decodes a user by suppressing only the in-cell interferers. As a result, each user suffers only from other-cell interference and enhanced receiver noise. By analysis, we show that in random CDMA systems, the partial decorrelator outperforms the conventional receiver, within the operating regime of the conventional receiver. In simulation, we observe that when users have equal received powers at their respective receivers, a multicell system with partial decorrelator receivers yields roughly 1.5 times the capacity of the conventional system.

Code-division multiple-access (CDMA) systems are interference limited, and therefore efficient interference management is necessary to enhance the capacity of a CDMA system. In this paper, we consider combining two effective receiver-based interference management strategies: multiuser detection (temporal filtering) and receiver beamforming (spatial filtering). We formulate and examine the performance of several two-dimensional linear filter structures, which are all based on minimum mean squared error (MMSE) criterion but differ in how the MMSE problems are defined in the temporal and spatial domains, i.e., jointly or in cascade. It is shown that while the joint optimum MMSE filter achieves the maximum signal-to-interference ratio (SIR) among all possible matrix filters, the constrained optimum MMSE filter which results in a single temporal and single spatial filter, outperforms all combined single-user/multiple-user approaches and cascaded optimization approaches either uniformly or asymptotically. The constrained optimum MMSE filter is near-far resistant in all but very highly loaded systems and enjoys low complexity.

Motivated by the emergence of programmable radios, we seek to understand a new class of communication system where pairs of transmitters and receivers can adapt their modulation/demodulation method in the presence of interference to achieve better performance. Using signal to interference ratio as a metric and a general signal space approach, we present a class of iterative distributed algorithms for synchronous systems which results in an ensemble of optimal waveforms for multiple users connected to a common receiver (or colocated independent receivers). That is, the waveform ensemble meets the Welch (1974) bound with equality and, therefore, achieves minimum average interference over the ensemble of signature waveforms. We derive fixed points for a number of scenarios, provide examples, look at ensemble stability under user addition and deletion as well as provide a simplistic comparison to synchronous code-division multiple-access. We close with suggestions for future work.

The optimum receiver to detect the bits of multiple code-division multiple access (CDMA) users has an exponential complexity in the number of active users in the system. Consequently, many suboptimum receivers have been developed to achieve good performance with less complexity. We take the approach of approximating the solution of the optimum multiuser detection problem (OMUD) using nonlinear programming relaxations. First, we observe that some popular suboptimum receivers indeed correspond to relaxations of the optimal detection problem. In particular, one proposed approximation method yields to iterative solutions which correspond to previously proposed heuristic nonlinear detectors. Using a nonlinear programming approach, we identify the convergence properties of these iterative detectors. Secondly, we propose a relaxation that yields a receiver which we call the generalized minimum mean squared error detector. We give a simple iterative implementation of the detector. Its performance is evaluated and comparisons to other suboptimum detection schemes are given.

Among the ambitious challenges to be met by the third-generation systems is to provide high-capacity flexible services. Code-division multiple access (CDMA) emerges as a promising candidate to meet these challenges. It is well known that CDMA systems are interference-limited, and interference management is needed to maximally utilize the potential gains of this access scheme. Several methods of controlling and/or suppressing the interference through power control, multiuser detection (temporal filtering), and receiver beamforming (spatial filtering) have been proposed to increase the capacity of CDMA systems up to date. We investigate the capacity increase that is possible by combining power control with intelligent temporal and spatial receiver filter design. The signal-to-interference ratio maximizing joint temporal-spatial receiver filters in unconstrained and constrained filter spaces are derived. Two-step iterative power control algorithms that converge to the optimum powers and the joint temporal and spatial receiver filters in the corresponding filter domains are given. A power control algorithm with a less complex filter update procedure is also given. We observe that significant savings in total transmit power are possible if filtering in both domains is utilized compared with conventional power control and joint optimal power control and filtering in only one domain.

Second- and third-generation (2G and 3G) wireless systems have been designed primarily for voice, a connection-oriented, delay-sensitive service requiring a specified bit rate. In contrast, data services are often connectionless, delay insensitive, and have no specific bit-rate requirements. These differences suggest that ubiquitous (anytime/anywhere) coverage may not be a strict requirement for wireless data networks and in fact may needlessly complicate the design. This line of thought leads to systems that provide isolated high bit-rate "pockets" of coverage close to base station antennas through multilevel modulation and increased spectrum reuse allowed by pocket isolation. Specific issues that are relevant for such tier architectures range from the physical layer extending to radio resource management and even application layers. We describe some issues for wireless data targeting the following: transceiver techniques and radio resource management.

This paper examines truncated window decorrelators for an asynchronous direct-sequence code-division multiple-access system supporting users transmitting at different bit rates. We decode a user by extending the observation window over a sufficient number of its bits. To characterize practical window sizes, simple upper and lower bounds for the asymptotic efficiency of both the truncated window and infinite window decorrelators are developed. Empirical results show that as the length of the observation window increases, the bounds converge rapidly to the asymptotic efficiency of the infinite window decorrelator. The complexity of the receiver depends strongly on the ratio of the maximum to minimum bit rates.

For code-division multiple-access (CDMA) wireless systems employing multiuser detection, the varied bit-error rate (BER) requirements of multimedia traffic dictate the use of transmitted power control. Using a decorrelator in an asynchronous multirate direct-sequence CDMA system, it may be necessary for different users to combat the noise enhancement and the propagation losses to varying degrees depending on individual requirements. In this context, we propose a power control algorithm for a multirate decorrelator that is suitable for a class of BER-based link quality objectives. If the uplink channel gain of the desired user is known, then it is straightforward for each user to choose the transmitted power needed to meet its target BER objective. In practice, however, the uplink channel gain is often difficult to measure. To avoid this measurement, we employ stochastic approximation methods to develop a simple iterative power control algorithm. In this algorithm, each mobile uses the output of its own decorrelator to update its transmitted power in order to achieve its BER objective. We show that when a user's bits have nonzero asymptotic efficiencies, the power control algorithm converges quickly in the mean square sense to the minimum power at which a user achieves its quality-of-service objective.

Infostations provide a new way to look at the problem of providing high-data-rate wireless access. By allowing delayed message delivery, we can lift the constraint on ubiquitous coverage inherited from voice cellular systems. The reduction of coverage results in significant capacity gains, showing the possibility for low-cost broadband wireless data services. We give an overview of ongoing research on the Infostation concept.

This paper presents the concept of “mobile ATM,” a proposal for third-generation (3G) mobile communication network infrastructure capable of supporting flexible evolution of radio technologies from today's cellular and data services towards future wireless multimedia services. Mobile ATM provides generic mobility management and QoS-based transport capabilities suitable for integration of multiple radio access technologies including cellular voice, wireless data, and future broadband wireless services. The architecture of a mobile ATM network is outlined in terms of the newly-defined “W-UNI” interface at the radio link and “M-UNI” and “M-NNI” interfaces within the fixed network. The concept of a “proxy-UNI” interface which supports unified access for WATM and non-ATM mobile terminals through corresponding interworking functions (IWF) is explained, leading to an understanding of how different radio access technologies are supported by the same ATM-based core network infrastructure. Generic mechanisms for handoff and location management within the core mobile network are discussed, and related protocol extensions over the “W-UNI” and “M-UNI/NNI” interfaces are proposed. The issue of “crossover switch (COS)” selection in mobile ATM is considered, and a unified handoff signaling syntax which supports flexibility in COS selection is described. Typical signaling sequences for call connection and handoff using the proposed protocols are outlined. Experimental results from a proof-of-concept mobile ATM network prototype are presented in conclusion.

This paper studies the effects of user mobility and handoff path rerouting on the traffic distributions in a mobile network environment. In mobile ATM networks, extra traffic load may be added to network links due to user mobility and handoff path rerouting. This requires higher network link capacity and possible topology reengineering in order to support the same quality of service (QoS) for mobile services. To capture the dynamic variations in mobile ATM networks, we propose to use a flow model. The model represents the mobile-generated traffic as a set of stochastic flows over a set of origin-destination (OD) pairs. The user mobility is defined by transfer probabilities of the flows and the handoff path rerouting algorithm is modeled by a transformation between the routing functions for traffic flows. The analysis shows that user mobility may cause temporal variations as well as smoothing effects on the network traffic. Using the flow network model, typical handoff path rerouting algorithms are evaluated through both analytical and experimental approaches. The evaluation methodology can be used for either redesigning the network topology for a given path rerouting algorithm or selecting a path rerouting algorithm for a given network topology under a specific mobile service scenario.

The signal-to-interference ratio (SIR) has been highlighted in the literature to be an efficient criterion for several radio resource management algorithms such as power control and handoff. We address the problem on how to obtain fast and accurate measurements of this quantity in a practical context. We develop a general SIR estimation technique for code division multiple access (CDMA) cellular systems, that is based on a signal subspace approach using the sample covariance matrix of the received signal. Analysis and simulation results for an IS-95 like system show that the SIR can be estimated to within 80% of the actual SIR after less than seven frames, or within 90% of the actual SIR after less than 15 frames. We also study a computationally less expensive SIR tracking algorithm based on updating the signal subspace. We show that the algorithm works well in the context of a rapidly time varying channel.

The eight papers in this special issue focus on delay and disruption tolerant wireless communication. The papers cover routing and network coding for spare mobile ad hoc networks, cross-layer design for sensor networks, satellite communication, and DTN architectural issues.

For wireless communication systems, iterative power control algorithms have been proposed to minimize the transmitter power while maintaining reliable communication between mobiles and base stations. To derive deterministic convergence results, these algorithms require perfect measurements of one or more of the following parameters: (1) the mobile's signal-to-interference ratio (SIR) at the receiver; (2) the interference experienced by the mobile; and (3) the bit-error rate. However, these quantities are often difficult to measure and deterministic convergence results neglect the effect of stochastic measurements. We develop distributed iterative power control algorithms that use readily available measurements. Two classes of power control algorithms are proposed. Since the measurements are random, the proposed algorithms evolve stochastically and we define the convergence in terms of the mean-squared error (MSE) of the power vector from the optimal power vector that is the solution of a feasible deterministic power control problem. For the first class of power control algorithms using fixed step size sequences, we obtain finite lower and upper bounds for the MSE by appropriate selection of the step size. We also show that these bounds go to zero, implying convergence in the MSE sense, as the step size goes to zero. For the second class of power control algorithms, which are based on the stochastic approximations method and use time-varying step size sequences, we prove that the MSE goes to zero. Both classes of algorithms are distributed in the sense that each user needs only to know its own channel gain to its assigned base station and its own matched filter output at its assigned base station to update its power.

The decorrelating detector is known to eliminate multiaccess interference when the signature sequences of the users are linearly independent, at the cost of enhancing the Gaussian receiver noise. In this paper, we present a blind adaptive decorrelating detector which is based on the observation of readily available statistics. The algorithm recursively updates the filter coefficients of a desired user by using the output of the current filter. Due to the randomness of the information bits transmitted and the ambient Gaussian channel noise, the filter coefficients evolve stochastically. We prove the convergence of the filter coefficients to a decorrelating detector in the mean squared error (MSE) sense. We develop lower and upper bounds on the MSE of the receiver filter from the convergence point and show that with a fixed step size sequence, the MSE can be made arbitrarily small by choosing a small enough step size. With a time-varying step size sequence, the MSE converges to zero implying an exact convergence. The proposed algorithm is distributed, in the sense that no information about the interfering users such as their signature sequences or power levels is needed. The algorithm requires the knowledge of only two parameters for the construction of the receiver filter of a desired user: the desired user's signature sequence and the variance of the additive white Gaussian (AWG) receiver noise. This detector, for an asynchronous code division multiple access (CDMA) channel, converges to the one-shot decorrelating detector.

As users, services, databases, and computers become increasingly mobile, so fades the era of the fixed network. Modern networks are becoming mobile networks which must accommodate a broad range services with differing mobility characteristics. Consequently, there is an impetus to understand mobility and its effect on communications systems. Of particular interest are the unique stresses imposed by mobile computing and especially mobile computer programs (agents). As an aid to greater understanding, we propose a theoretical framework for the study of mobility tracking based on user/service/host location probability distributions. We show how this methodology, using stochastic ordering and information theory, can enable quantitative comparison of various mobility management schemes as well as insight into the mobility tracking problem over a wide range of mobility characteristics. This general approach should aid both applications and future research.

High terminal traffic densities are expected in urban multiuser radio systems. An efficient allocation of resources is the key to high system capacity. In this paper, a distributed dynamic resource allocation (DDRA) scheme based on local signal and interference measurements is proposed for multiuser radio networks. It offers "soft capacity" for time division multiple access (TDMA) and frequency division multiple access (FDMA) systems, bounded above by N per base station, where N is the total number of channels in the system. The decisions are made local to a terminal and its base and are essentially independent of the rest of the system. A distributed dynamic channel assignment scheme is used to assign channels to new calls. This scheme assigns a channel that offers the maximum carrier to interference ratio (CIR) to a new call. A distributed constrained power control (DCPC) scheme based on CIR measurements is used for power control. The channel assignment scheme and the power control scheme are coupled to obtain an interactive resource allocation scheme. We compare the capacity of a system which uses the distributed dynamic resource allocation scheme described above with the capacity of a system which uses the channel assignment scheme alone. The system capacity is measured by simulation as the number of terminals that can be served by the system with a CIR above an acceptable minimum. In a 1D cellular system, coupling the channel assignment scheme with power control is discussed. Simulations were also used to show the effect of varying the maximum transmitter power on system capacity.

In packet reservation multiple access (PRMA) the receiver in the mobile terminal is required to listen continuously to monitor the acknowledgment messages broadcasted at the end of every time slot. A new scheme for the integration of voice and data based on PRMA is proposed. The voice and the data subsystems are logically separated. The total available bandwidth is divided into three regions-voice information, voice contention, and data regions. The available bandwidth is dynamically partitioned between the above three regions subject to the fulfillment of the quality of service (QoS) requirements of the voice users. The voice subsystem has been modeled as a Markov chain and an exact analytical method used to compute the voice packet dropping probability is described. A nonlinear programming problem is formulated to optimize the bandwidth allocated for the data users. Solutions to this nonlinear programming problem that are very close to optimum have been obtained heuristically. Numerical results indicate that a significant amount of data traffic can be supported without sacrificing the voice capacity of the system.

In cellular wireless communication systems, transmitted power is regulated to provide each user an acceptable connection while limiting the interference seen by other users. Previous work has focused on maximizing the minimum carrier to interference ratio (CIR) or attaining a common CIR over all radio links. However, previous work has assumed the assignment of mobiles to base stations is known and fixed. In this work, we integrate power control and base station assignment. In the context of a CDMA system, we consider the minimization of the total transmitted uplink power subject to maintaining an individual target CIR for each mobile. This minimization occurs over the set of power vectors and base station assignments. We show that this problem has special structure and identify synchronous and asynchronous distributed algorithms that find the optimal power vector and base station assignment. >

In cellular wireless communication systems, transmitted power is regulated to provide each user an acceptable connection by limiting the interference caused by other users. Several models have been considered including: (1) fixed base station assignment where the assignment of users to base stations is fixed, (2) minimum power assignment where a user is iteratively assigned to the base station at which its signal to interference ratio is highest, and (3) diversity reception where a user's signal is combined from several or perhaps all base stations. For the above models, the uplink power control problem can be reduced to finding a vector p of users' transmitter powers satisfying p/spl ges/I(p) where the jth constraint p/sub j//spl ges/I/sub j/(p) describes the interference that user j must overcome to achieve an acceptable connection. This work unifies results found for these systems by identifying common properties of the interference constraints. It is also shown that systems in which transmitter powers are subject to maximum power limitations share these common properties. These properties permit a general proof of the synchronous and totally asynchronous convergence of the iteration p(t+1)=I(p(t)) to a unique fixed point at which total transmitted power is minimized. >

The authors describe a multilayer connection control architecture for broadband communications. A graph framework is introduced to describe network layers of network design, path configurations, dynamic call routing, burst switching, and asynchronous transfer mode (ATM) cell switching. These hierarchical layers of switching are performed at decreasing time scales, respectively. Switching at the higher layer is performed to reduce blocking at the next smaller time scale. A layered notion of equivalent bandwidth for satisfying layered grade-of-service parameters is introduced for making connections at these time scales. The authors then focus on the path configuration layer. Two path setup methods, namely, physical and virtual path setup, are described. Mathematical programs minimizing path bandwidth usage subject to meeting grade-of-service requirements are formulated for both methods. The relative merits of these methods are compared. In one example, physical path setup is shown to require roughly 50% more bandwidth than virtual path setup. >

The optimum multiuser detection problem was shown to be NP-hard, i.e., its computational complexity increases exponentially with the number of users (Verdu 1986, 1989). In this letter, we show that the optimum multiuser detection problem for a synchronous code-division multiple access (CDMA) system is equivalent to the minimum capacity cut problem in a related network and propose an optimum multiuser detection algorithm with polynomial computational complexity for a certain class of signature sequences. The minimum cut problem is solvable in polynomial time if the capacities of the links not incident to source and sink are nonnegative. This condition in the optimum detection problem is equivalent to all cross correlations between the signature sequences of the users being negative. One example of such a set of signature sequences is obtained when shifted versions of the maximal length sequences (or m-sequences) are used. In this case the cross correlation between users i and j is given as /spl Gamma//sub ij/=-1/G for all i,j, where G is the processing gain.