Frontline staff of emergency shelters face challenges such as vicarious trauma, compassion fatigue, and burnout. The technology they use is often not designed for their unique needs, and can feel burdensome on top of their already cognitively and emotionally taxing work. While existing literature focuses on data-driven technologies that automate or streamline frontline decision-making about vulnerable individuals, we discuss scenarios in which staff may resist such automation. We then suggest how data-driven technologies can better align with their human-centred decision-making processes. This paper presents findings from a qualitative fieldwork study conducted from 2022 to 2024 at a large emergency shelter in Canada. The goal of this fieldwork was to co-design, develop, and deploy an interactive data-navigation interface that supports frontline staff when making collaborative, high-stakes decisions about individuals experiencing homelessness. By reflecting on this fieldwork, we contribute insight into the role that administrative shelter data play during decision-making, and unpack staff members' apparent reluctance to outsource decisions about vulnerable individuals to data systems. Our findings suggest a ''data-outsourcing continuum,'' which we discuss in terms of how designers may create technologies to support compassionate, data-driven decision-making in nonprofit domains.

The top priority of a Housing and Homelessness System of Care (HHSC) is to connect people experiencing homelessness to supportive housing. An HHSC typically consists of many agencies serving the same population. Information technology platforms differ in type and quality between agencies, so their data are usually isolated from one agency to another. Larger agencies may have sufficient data to train and test artificial intelligence (AI) tools but smaller agencies typically do not. To address this gap, we introduce a Federated Learning (FL) approach enabling all agencies to train a predictive model collaboratively without sharing their sensitive data. We demonstrate how FL can be used within an HHSC to provide all agencies equitable access to quality AI and further assist human decision-makers in the allocation of resources within HHSC. This is achieved while preserving the privacy of the people within the data by not sharing identifying information between agencies without their consent. Our experimental results using real-world HHSC data from a North American city demonstrate that our FL approach offers comparable performance with the idealized scenario of training the predictive model with data fully shared and linked between agencies.

Risk prediction estimates the probability of future adverse outcomes for high-risk individuals to enable early intervention. Among all machine learning models, deep learning models can enhance risk predictions with respect to mental health (MH), where administrative healthcare data (Admin-HD) contain complex, irregular temporal information that a single model may not fully capture. This study aims to develop an ensemble hybrid deep-learning model (EnH-DL) to improve performance and reduce errors on unseen data compared to available deep-learning models. The model was evaluated in a cohort of individuals diagnosed with addiction or mental illness (AMH) to predict the risk of outcomes, such as the first healthcare encounter indicating homelessness (FHE-H) and the first healthcare encounters involving police (FHE-P). A sliding window and matrix-based representation were used in the preprocessing phase. Gated recurrent units (GRUs) with time decay, a one-dimensional (1D) convolutional neural network (CNN), and an attention function were integrated to build the EnH-DL. The results showed an average improvement in the area under the curve (AUC) by 2.5% and sensitivity by over 1.5%. An error reduction of over 0.22 indicates improved model reliability for unseen data. Tested in a clinical demand window to simulate real-world settings, the model achieved an 83% AUC and 79% sensitivity for FHE-H on a highly imbalanced test set. In conclusion, EnH-DL outperformed existing models for multiple MH outcomes using Admin-HD.

In most industrial applications, failed nodes will be repaired, but these repairs take time. For critical system applications, network operators need to understand how their networks function immediately after a failure but before a repair is possible. In this paper, we introduce an extension to the frame-level optimized routing/ scheduling algorithm to improve reliability and energy efficiency and compare it with the other industrial routing algorithms considering the oil refinery wireless sensor networks. We present a structured performance evaluation approach for studying the impact of the routing/scheduling algorithm on the post-failure/pre-repair regime. Simulation results show that the proposed algorithm exerts a positive impact on network performance: highly-reliable, low-latency, energyefficient, and fitting with most industrial applications.

This paper presents a detailed study for indoor wireless environments, where transmit power, rate and target bit error rate (BER) are varied to increase spectral efficiency. The study is conducted for the recently proposed joint fading and two-path shadowing (JFTS) channel model, which is shown to be accurate for modeling non-Gaussian indoor WLAN environments. Analysis is done for both average and instantaneous BER constraints without channel coding, where only a discrete finite set of constellations is available. Numerical results show that, for a JFTS channel i) varying only the transmission rate (modulation constellation size) achieves more improvement in spectral efficiency compared to varying transmit power only, and ii) varying rate and/or power subject to instantaneous BER (I-BER) constraint offers better performance than when subject to average BER (A-BER) constraint.

This paper studies how to maximize the lifetime of ISA100.11a and Wireless highway addressable remote transducer (WiHART) compatible sensor networks for a petroleum refinery scenario. When accounting for the energy consumption of a typical refinery process sensor and the node microprocessor, only a relatively small percentage of battery energy on average is spent on wireless communication. However, this paper will demonstrate that optimizing network operation can still considerably extend network lifetime. The longest lifetimes are achieved using a new network optimization approach that accounts for the frame structure of ISA100.11a/WiHART. Results are generated using a full network protocol stack simulation that incorporates three different network optimization approaches and includes the energy consumption of the wireless transceiver, sensor, and microprocessor.

Performance of common digital modulation techniques is analyzed over indoor wireless environments modeled through the recently proposed joint fading and two-path shadowing (JFTS) channel model. Mathematically tractable expressions for the instantaneous signal-to-noise ratio statistics, average bit error rates, and achievable channel cutoff rates are derived. Analytical results are used to: 1) investigate the impact of different JFTS model parameters and different modulation techniques on bit error rates and cutoff rates and 2) demonstrate how the JFTS channel model affects system performance in comparison with conventional empirical channel models. Finally simulation results are used to corroborate this analysis and evaluate the usefulness of such an analysis.

Unmanned aerial vehicles, or drones, have the potential to significantly reduce the cost and time of making last-mile deliveries and responding to emergencies. Despite this potential, little work has gone into developing vehicle routing problems (VRPs) specifically for drone delivery scenarios. Existing VRPs are insufficient for planning drone deliveries: either multiple trips to the depot are not permitted, leading to solutions with excess drones, or the effect of battery and payload weight on energy consumption is not considered, leading to costly or infeasible routes. We propose two multitrip VRPs for drone delivery that address both issues. One minimizes costs subject to a delivery time limit, while the other minimizes the overall delivery time subject to a budget constraint. We mathematically derive and experimentally validate an energy consumption model for multirotor drones, demonstrating that energy consumption varies approximately linearly with payload and battery weight. We use this approximation to derive mixed integer linear programs for our VRPs. We propose a cost function that considers our energy consumption model and drone reuse, and apply it in a simulated annealing (SA) heuristic for finding suboptimal solutions to practical scenarios. To assist drone delivery practitioners with balancing cost and delivery time, the SA heuristic is used to show that the minimum cost has an inverse exponential relationship with the delivery time limit, and the minimum overall delivery time has an inverse exponential relationship with the budget. Numerical results confirm the importance of reusing drones and optimizing battery size in drone delivery VRPs.

The performance of rate adaptive M-ary quadra- ture amplitude modulation (M-QAM) and adaptive trellis-coded M-QAM in large open office indoor wireless environments is studied in this paper. An appropriate composite fading/shadowing channel model termed the Joint Fading and Two-path Shadowing (JFTS) model is adopted for the indoor wireless environment. Mathematically tractable expressions for the spectral efficiency and average bit error rate (ABER) of adaptive coded and uncoded M-QAM over the JFTS channel are derived. Analytical results demonstrate the performance of adaptive M-QAM over different JFTS channel configurations, and simulation results corroborate the derived analytical ABER expressions.

Minimizing the cost of deploying and operating a wireless sensor network (WSN) involves deciding how to partition a budget between competing expenses such as node hardware, energy, and labor. Most commercial network operators account for interest rates in their budgeting exercises, providing a financial incentive to defer some costs until a later time. In this paper, we propose a net present cost (NPC) model for WSN capital and operating expenses that accounts for interest rates. Our model optimizes the number, size, and spacing between expenditures in order to minimize the NPC required for the network to achieve a desired operational lifetime. In general, this optimization problem is non-convex, but if the spacing between expenditures is linearly proportional to the size of the expenditures, and the number of maintenance cycles is known in advance, the problem becomes convex and can be solved to global optimality. If non-deferrable recurring costs are low, then evenly spacing the expenditures can provide near-optimal results. With the provided models and methods, network operators can now derive a payment schedule to minimize NPC while accounting for various operational parameters. The numerical examples show substantial cost benefits under practical assumptions.

This paper introduces an analytical model for characterizing the instantaneous hit ratio and instantaneous average hit distance of a traditional least recently used (LRU) cache hierarchy. The analysis accounts for the use of two variants of the Time-to-Live (TTL) weak consistency mechanism. The first is the typical TTL scheme (TTL-T) used in the HTTP/1.1 protocol where expired objects are refreshed using conditional GET requests. The second is TTL immediate ejection (TTL-IE) where objects are ejected as soon as they expire. The analysis also accounts for two sharing protocols: Leave Copy Everywhere (LCE) and Promote Cached Objects (PCO). PCO is a new sharing protocol introduced in this paper that decreases the user's perceived latency and is robust under nonstationary access patterns.

The performance of Turbo coded Binary Phase Shift Keying (BPSK) over the Joint Fading and Two-path Shadowing (JFTS) environment is analyzed. Exact analytical expression for the Pairwise Error Probability (PEP) of Turbo codes over fully interleaved JFTS channels is presented using the probability distribution of the squared independent and identically distributed JFTS random variables. Finally the Turbo coded Average Bit Error Rate (ABER) of a wireless communication system is simulated over JFTS fading / shadowing channels and compared with the derived analytical result.

The simultaneous use of wireless and power line communications (PLC) channels provides a convenient method for increasing the coverage and throughput of indoor networks. In this paper, we compare coding diversity and modulation diversity schemes that both utilize parallel wireless and PLC links. The signal to noise ratio (SNR) values used in this analysis are determined by conducting a series of average link gain measurements in an office environment. Measurement results show that both wireless and PLC SNRs have a wide range, but neither type of media is guaranteed to dominate performance for a given link. The empirical SNR values are used in a Monte Carlo simulation to evaluate the possible throughput advantages of coding and modulation wireless-PLC media diversity.

A new expression for the Cumulative Distribution Function (CDF) of the Joint Fading and Two-path Shadowing (JFTS) distribution is derived in this paper. The derived theoretical CDF expression is shown to agree with the experimental results. The CDF expression is used to derive an outage expression for non-diversity transmission which is then used to illustrate the performance of adaptive transmission over the JFTS link.

The performance of Binary Phase Shift Keying (BPSK) in a Joint fading and Two-path Shadowing (JFTS)environment is analyzed. Closed form expression for the exact Average Bit Error Rate (ABER) of coherent BPSK scheme is presented using the Moment Generating Function (MGF) of the JFTS distribution. Finally the coherent BPSK ABER of a wireless communication system is simulated over JFTS fading / shadowing channels with and without non- iterative Forward Error Correction (FEC) coding and compared with the analytical ABER expression.

It is often advocated that a solution to the problem of interference to digital subscriber line networks (DSL) from a power line communications (PLC) network is to prevent the PLC networks from utilizing the DSL spectrum. However, this solution will render PLC networks inoperable with the introduction of wide-band DSL technology like G.Fast. We propose utilizing an interference cancelling scheme to ensure the co-existence of DSL and PLC networks within the home environment. A measurement campaign is conducted where a set of 480 measurements are collected within a residential house to characterize the PLC-to-DSL interference environment for two DSL modem installation scenarios. The interference cancelling scheme is based on an adaptive frequency domain interference canceller (FDIC) that utilizes the common mode (CM) PLC interference to estimate the differential mode (DM) PLC interference. The effectiveness of the FDIC, which is insensitive to the non-stationarity of the PLC channel, is demonstrated using analysis that incorporates the measured PLC-to-DSL coupling channels.

Recent advances in power line communications (PLC) have made it popular for in-home networking. This makes PLC an increasingly relevant source of interference for digital subscriber line (DSL) networks within the home environment. This paper presents measured PLC-to-DSL coupling channels for a worst case DSL deployment scenario. We then propose an interference cancelling scheme based on a frequency domain interference canceller (FDIC) that utilizes the common mode (CM) PLC interference to estimate and remove the differential mode (DM) PLC interference. The mean square error (MSE) of the proposed FDIC is derived and compared to the minimum MSE achieved by an optimum Wiener filter. Improvement in the signal to interference plus noise ratio (SINR) achieved by using the FDIC is also presented. Both mathematical analysis and simulation results demonstrate the effectiveness of the proposed FCID in reducing the DM PLC interference on the DM DSL signal.

Over its lifetime, a Wireless Sensor Network (WSN) loses connectivity as more and more of its battery-powered nodes fail. In this paper, we study how to repair such a network by the gradual deployment of new sensor nodes. We provide algorithms that not only economically adjust the number of replaced nodes but also improve the network by placing the new nodes in better locations. This new approach substantially increases the lifetime of the repaired WSN compared to replacing all nodes at their old positions.

This paper introduces a novel analytical model for estimating the cache hit ratio as a function of time. The cache may not reach the steady-state hit ratio when the number of Web objects, object popularity, and/or caching resources themselves are subject to change. Hence, the only way to quantify the hit ratio experienced by Web users is to calculate the instantaneous hit ratio. The proposed analysis considers a single Web cache with infinite or finite capacity. For a cache with finite capacity, two replacement policies are considered: Least Recently Used (LRU) and First-In-First-Out (FIFO). Based on the insights from the proposed analytical model, we propose a new replacement policy, called Frequency-Based-FIFO (FB-FIFO). The results show that FB-FIFO outperforms both LRU and FIFO, assuming that the number of Web objects is fixed. Assuming that new popular objects are generated periodically, the results show that FB-FIFO adapts faster than LRU and FIFO to the changes in the popularity of the cached objects when the cache capacity is large relative to the number of newly generated objects.

Deploying wireless sensor networks (WSNs) from unmanned aerial vehicles (UAVs) can reduce the cost of large rollouts and make it safer to deploy sensors in disaster areas. However, aerial deployment can lead to nodes with arbitrary orientations and, thus, to misaligned antennas. While this problem was observed during experiments, it has not been systematically studied so far. This paper considers an aerially deployed network that utilizes routing designed to minimize latency and improve reliability. A new antenna model is used to demonstrate the performance degradation caused by aerial deployment. By mitigating a large share of this degradation, cooperative relaying substantially reduces the energy consumption of the network.

Performance of indoor home networks can be improved by simultaneous use of wireless and powerline communication (PLC) channels. A narrowband model representing an OFDM subcarrier is used to analyze the performance of several diversity combining schemes including optimum combining (OC), saturated metric combining (SMC) and maximal ratio combining (MRC). Results from BER analysis show that SMC achieves good performance in highly impulsive noise and is relatively insensitive to error in noise parameter estimates. Indoor measurements from 3 detached homes show that parallel wireless and PLC channels have a wide, but similar, signal-to-noise ratio (SNR) range. Measurement data is used with link throughput analysis to show that wireless/PLC diversity can be used to minimize the likelihood of low throughput links.

Optimum and suboptimum combining is investigated for a 2-branch diversity system containing unique Class-A noise in each branch. Expressions for log-likelihood ratio (LLR) reveal that the optimum scheme can be viewed as a linear combiner which is conditioned on the Class-A state. Bit-error rate (BER) performance curves for BPSK demonstrate that use of a saturated Gaussian metric for low-complexity signal combining results in good performance. However, maximal ratio combining (MRC) performs poorly due to mismatch between the MRC LLR and the LLR for optimum schemes.

This paper presents a method for supporting wireless media streaming using a cache that is distributed across the mobile devices in the network. The performance of this scheme is compared to traditional institutional server (IS) caching on a network with a bandwidth constrained wireless backhaul. In addition to traditional caching hit ratio metrics, the paper studies how caching affects the call drop ratio due to limited backhaul bandwidth. These results indicate that the distributed caching method provides better service than IS caching as the number of users is increased. Finally, this paper also presents a scheme for conserving mobile device energy by limiting its participation in the caching scheme. Results show that most of the benefit of the distributed cache can be realized even with relatively few cache assists from each client.

This work investigates how wireless network performance affects a rescue robot that is running a simultaneous localization and mapping (SLAM) algorithm. The SLAM algorithm is used to generate a map of an unknown disaster site. Odometry and laser range data collected by the robot is transferred via an ad-hoc wireless network to a central access point (AP) that is running the SLAM algorithm. Simulation is used to determine how losses, latency and the use of relays in the network affect the quality and completeness of the SLAM maps. This is illustrated using new metrics for SLAM map quality and completeness that are based on Hausdorff distance.

Wireless devices are often connected to power outlets in residential data and smart-home networks. As a result, physical layer performance can be improved by using the power distribution tree as a diversity channel. This paper proposes a hardware-efficient, low intermediate-frequency (low-IF) transceiver architecture which allows existing wireless protocols to be used over both wireless and power-line communication (PLC) channels. A signal model for this form of hybrid transmission is presented assuming Rayleigh flat-fading and Middleton Class A impulsive noise in the wireless and PLC channels, respectively. Analysis of maximal-ratio combining (MRC) reveals that detector input noise is also Class A-distributed. Expressions for average bit-error rate (BER) of a BPSK subcarrier show that BER is a function of PLC impulsiveness and significant improvement can be achieved with diversity and PLC SNR > 10 dB. In regions of low and high wireless SNR, BER curves are approximately linear with slope of 0 and -1, respectively. The inflection point between these two regions can be used by transceivers to select between PLC-only and hybrid transmission modes.

The use of mobile nodes within a wireless sensor network are an asset since they can considerably extend the lifetime of that network. In order for mobile sensor nodes to be effective in most cases, their position must be known. Dead reckoning (DR) is a simple location method that is well suited to complexity constrained sensor nodes. The contribution of this paper is to present a Gaussian model for DR positioning error that is based on measurements collected using a popular robot chassis. The model is verified using Monte Carlo simulations that incorporate the empirical DR error.

This paper presents a technique for using propagation measurements to perform a site-specific technical and economic comparison of indoor and outdoor orthogonal frequency division multiple access (OFDMA) infrastructure. This work is motivated by the fact that fourth generation (4G) network operators have a choice when provisioning a network to serve indoor users. An operator can choose to retrofit existing outdoor cellular macro-cell base station sites with 4G equipment or to deploy new compact indoor pico-cell base stations. This paper will illustrate how multi-antenna propagation measurements can be collected and used to estimate the throughput of an indoor or outdoor base station. This information will then be incorporated into an economic analysis that determine what sort of network will have the lowest operating and capital costs while still meeting user requirements. This approach is illustrated using a university campus case study.

This paper quantifies the multi-user wireless diversity benefit of basing opportunistic transmission on large scale shadowing. This technique is primarily aimed at wireless sensor nodes. The processing capability of these nodes is limited and transmissions between sensor nodes are very sporadic. It is therefore easier for these devices to track large scale shadowing variations than the small scale shadowing variations normally used for opportunistic transmission. This paper will derive closed form expressions that compare the average SNR improvement provided by opportunistic transmission when based on large scale and small scale channel effects. Closed form bit error rate (BER) expressions will also be used to illustrate that opportunistic transmission based on shadowing can achieve very good performance improvements for modestly sized scheduling groups and realistic indoor shadowing standard deviation values.

In this paper, we consider the design of caching infrastructure to enhance the client-perceived performance of mobile wireless clients retrieving multimedia objects from the Internet. We consider three primary issues: location of the cache, size of the cache, and management policy for the cache. We consider both infrastructure-oriented caching at the Access Point (AP), as well as peer-assisted caching at the mobile clients. Simulation is used as the methodology for evaluation and comparison of caching strategies. The simulation results show that AP caching is generally more effective than client-side caching, that adequate performance is achievable with a mix of rather modest AP and client-side caches, and that Least Frequently Used (LFU) is the most effective cache replacement policy. Additional simulation experiments show that our results are robust across different request generation rates and client turnover rates.

A dense urban cellular environment contains many different locations where a line-of-sight or specular signal component from the base station is present. The small scale fading at these locations is best characterized using the Ricean distribution. However, the K-factor of that distribution will vary from one location to the next. This paper presents a statistical model for dense urban vehicular non-stationary Ricean fading where K- factor changes gradually due to movement through changing surroundings. Using analysis of empirical radio channel measurements, a model is developed to represent K-factor variation as a stochastic process. An auto-regressive (AR) model is used to ensure the autocorrelation of the simulated K-factor process matches the empirical data. The model is verified by using it to simulate a non-stationary Ricean small scale fading envelope and comparing it to the fading envelope seen in the measurements.

This work presents a new amplify-and-forward (AF) cooperative multiple input multiple output (MIMO) transmission scheme based on phase sweep transmit diversity. In a single hop cooperative link, the relay node imposes a phase sweep on the signal it receives from the source node. This phase sweeping causes fast fading when the signals from the source and relay nodes combine at the destination. On low velocity or static links, this fast fading improves channel code performance. The method used to implement the phase sweeping results in a relay node design that is much simpler than other AF schemes while still providing a comparable performance improvement.

This paper investigates the potential for future multiple antenna wireless local area network technologies such as 802.11n to perform indoor network-based positioning using angle of arrival (AOA) estimation. A multiple-input multiple-output (MIMO) channel measurement system is used to determine the statistical accuracy of the indoor AOA estimation when performed at an 802.11n wireless access point (AP). Two different channel parameter estimation algorithms are used to perform AOA estimation; a simple maximum-likelihood (ML) scheme and the space-alternating generalized expectation-maximization (SAGE) technique. Results indicate that general channel parameter estimation algorithms, such as SAGE, are ill suited to estimate AOA for positioning purposes. However, results show that with the use of a specialized channel parameter estimation algorithm, such as the simple ML algorithm, quality AOA estimates for positioning might be achieved with low computational complexity. A positioning simulation that incorporates the AOA estimates from the simple ML algorithm achieves a positioning accuracy of 1.7 m with the help of an extended Kalman filter.

This paper compares how using either indoor or outdoor base stations affects the multiple input/multiple output (MIMO) orthogonal frequency division multiplexing (OFDM) physical layer performance experienced by an indoor user. This study starts by collecting outdoor-to-indoor and indoor-to-indoor MIMO propagation measurements in a campus environment. To ensure a fair comparison, the measurement receiver is positioned at the same set of indoor locations for both sets of measurements. The propagation measurement data is then used directly in a MIMO-OFDM system simulation in order to determine whether using either indoor or outdoor infrastructure will offer a physical layer performance advantage. The conclusion of the paper is that both indoor and outdoor base stations offer very similar performance for the environment characterized by the measurements.

This paper presents a wireless sensor network (WSN) transmit power control algorithm designed to minimize WSN node energy consumption. The algorithm determines transmit power levels using an optimization that accounts for energy consumed by the physical and link layers of the protocol stack. This cross-layer optimization incorporates a physical layer model that uses knowledge of the WSN medium access control (MAC) layer algorithm to accurately model multiple access interference (MAI). Analytical and simulation results show that accounting for MAI in this fashion results in a significant energy savings relative to comparable WSN power control algorithms.

This work uses spatial radio channel measurements to evaluate how much IEEE 802.11b wireless local area network (WLAN) capacity could be improved by using spatial division multiple access (SDMA). The radio channel measurements are collected for three different indoor network configurations using a sectorized antenna suitable for use in an actual 802.11b access point. The measurements are then used directly in 802.11b physical layer simulations in order to evaluate SDMA performance.

This paper investigates the use of physical layer symbol error rate (SER) optimization to minimize wireless sensor network (WSN) energy consumption. Increasing the SER maintained by the physical layer can save energy by lowering transmit power. However, this also causes an increase in the amount of energy spent on frame retransmissions. A technique for SER optimization that balances these two effects will be presented. The variation in average link delay that results when this technique is applied to a WSN will also be explored

This work improves channel decoder performance on the code-division multiple-access (CDMA) forward link through more accurate calculation of the channel code trellis path metrics used to decode convolutional and turbo codes. This is achieved by performing the metric calculations with better channel state estimates. Channel state estimation involves determining desired signal amplitude and interference plus noise variance at the channel decoder input. Two options are presented for performing this estimation. Standard estimation is a simple scheme that results from assuming all CDMA forward link interference and noise can be lumped into a single additive white Gaussian noise process. Improved estimation is a new and more accurate technique that separately accounts for the intracell interference and intercell interference plus thermal noise processes. Simulations show that the decoding of convolutional and turbo codes is significantly improved by the more accurate channel state information provided by improved estimation.

A new trellis path metric is derived for the CDMA mobile MAP and logMAP turbo decoders. This metric accounts for the non-Gaussian received symbol probability distribution seen at the output of a mobile RAKE receiver when the RAKE combining weights are subject to channel estimation error. Since an exact analytical expression for this distribution is difficult to find, the metric is instead derived by finding the characteristic function of an approximation to the distribution. Simulations are then used to compare how the CDMA forward link performs when the mobile uses either the conventional logMAP trellis path metric or the new metric. The results indicate that while the conventional metric is still the best choice when channel estimation error is small, the new metric provides a significant performance improvement when channel estimation error is large.

This work uses the second order statistics of the signal received by a CDMA mobile to determine what proportion of that signal consist of in-cell interference and what proportion is out-of-cell interference plus thermal noise. A least-squares estimator is derived and compared to the Creamer-Rao lower bound. The interference estimated are incorporated into the CDMA mobile channel decoder in order to improve the performance of convolutional and turbo codes on the CDMA forward link.

The channel code decoder in a CDMA mobile performs channel state estimation to determine the reliability of each received encoded symbol. This reliability information is typically an estimate of received signal envelope and interference plus noise variance. Most papers that investigate CDMA forward link channel code performance assume that all interference and noise can be modeled as a single, stationary Gaussian process. This assumption leads to inaccurate channel state estimates since in-cell interference is non-stationary on the CDMA forward link. This paper presents a channel state estimation procedure for single antenna and Space Time Transmit Diversity (STTD) transmission that accounts for non-stationary in-cell interference. Simulations are used to illustrate how this scheme improves convolutional and turbo code performance.

Many IS-95 CDMA networks currently deployed in the field are forward link capacity limited. The introduction of IS-2000 is intended to improve forward link performance and increase system capacity. However, the performance improvement provided by IS-2000 will vary with propagation environment. A technique for collecting forward channel impulse response measurements using IS-95 pilot signals is presented. This technique is used to characterize the forward channel in residential and urban regions in Calgary, Canada. The propagation data is then processed in a simulation in order to generate a comparison of IS-95 and IS-2000 performance that is specific to these environments. The results illustrate how the propagation environment can affect the performance improvement provided by IS-2000.