Accurate navigation is essential for underwater vehicles like AUVs, which often operate in deep or remote areas. However, complex ocean dynamics, cumulative inertial-measurement unit (IMU) drift, and diverse noise sources often result in erratic and unreliable position estimates. To overcome these challenges, we proposed a method that combines underwater acoustic signals with onboard motion sensor data to improve the underwater position tracking system. The proposed system uses a long baseline (LBL) acoustic array of surface buoys to capture the Time-difference-of-Arrival (TDoA) of a multi-pulse beacon. We extract arrival times using a superimposed-envelope-spectrum (SES) detector, which exploits the beacon’s periodic structure to stay reliable even in heavy noise. These acoustic measurements are fused with six-degree-of-freedom IMU data using a particle filter (PF). The filter suppresses IMU drift and reveals how long dead-reckoning remains reliable before an acoustic update becomes essential. Simulation results demonstrated that our PF-TDoA fusion method achieved up to 40% reduction in mean localization error compared to traditional fusion filters and optimization method. In the experiment, we compared the simulated IMU prediction with real-world acoustic measurements, and the resulting fused position estimated remained within 3 m of Global Positioning System (GPS)-reported trajectory, demonstrating robust performance under operational conditions. • We introduce a feature-based TDoA detector that reduces false alarms in heavy noise. • We fuse 6-DOF IMU and acoustic ranges in a PF to schedule pings only when needed. • We present a geometry-aware robust NLLS solver for accurate 3-D trilateration.

Underwater Acoustic Communication (UAC) has garnered significant attention due to its applications in marine science, defence, and exploration. With the vast majority of the Earth’s surface covered by water, there is a growing demand for reliable and effective communication techniques in underwater environments. However, the underwater acoustic channel is the most challenging channel due to its harsh characteristics, which significantly hinder the reliability and performance of UAC systems. Orthogonal Time Frequency Space (OTFS) modulation has emerged as a promising solution for next-generation UAC systems to address high Doppler and high mobility scenarios. It has demonstrated tolerance to fast time-varying channel characteristics and enhanced resilience to Doppler shifts and multipath interference. These make OTFS suitable for the complex underwater environment. This study presents the first comprehensive review of the key challenges and state-of-the-art research and development of OTFS in underwater operations. It highlights the suitability and relevance of OTFS modulation for UAC. It also reviews recent advancements in channel estimation techniques tailored for OTFS-UAC systems. Potential future directions in sparse signal recovery for robust channel estimation and equalization, adaptive techniques, energy efficiency, and possible MAC protocols are also discussed to build a foundation for the next-generation UAC systems.

The Internet of Underwater Things (IoUT) is transforming underwater communication by enabling essential mission-critical applications such as precise navigation, emergency response coordination, diver safety, robust security and surveillance systems, and real-time environmental monitoring. However, Underwater Acoustic Communication (UAC), which serves as the primary communication medium for IoUT, experiences substantial challenges, including limited bandwidth availability, severe signal attenuation and Doppler-induced frequency shifts, especially pronounced in mobile underwater environments. These challenges degrade throughput and increase latency, making it difficult to meet the strict delay and reliability demands of mission-critical IoUT applications. Without adaptive solutions, real-time underwater communication remains unreliable and inefficient. This paper introduces an Adaptive Guard band and Power control resource allocation scheme for mission critical applications (AGP-MCA), specifically designed to improve underwater communication. The AGP-MCA framework optimizes the acoustic spectrum based on the criticality of IoUT applications. AGP-MCA dynamically adjusts guard bands to effectively mitigate Doppler caused by mobile nodes and strategically manages transmission power to reduce power consumption significantly, and handles non-critical data through buffering. We formulate a comprehensive mathematical optimization model and employ a Whale Optimization Algorithm (WOA)-based meta heuristic approach to achieve near-optimal solutions while ensuring minimal computational complexity. Extensive simulations demonstrate that AGP-MCA enhances throughput, reduces both end-to-end delay and power consumption, and consistently outperforms existing protocols and configurations without adaptive guard bands. Further, it offers a robust and power-efficient solution for real-time mission-critical IoUT applications.

IoT sensors are made of physical materials, and due to natural decay in materials, sensor data drifts over time. Even though sensors are calibrated after deploying at the site, the accumulation of errors in sensor measurements due to sensor drifts renders the data progressively irrelevant, creating significant issues for end applications. In this article, we propose a software-driven drift detection and calibration framework based on probabilistic observation in latent space using variational autoencoders (VAEs). The proposed method utilizes the latent distribution of the generative model from sampled observational data, which are collected during the calibration phase of the deployed sensors. Variational inference in VAEs is employed to approximate the true posterior distribution for detecting sensor drifts, incorporating metrics such as Kullback-Leibler (KL) divergence. Additionally, reconstruction loss is utilized for calibrating the sensors. Both simulated and real-world sensor data are used to evaluate the proposed method. Experimental results demonstrate significant improvement over existing drift detection and calibration techniques.

Underwater communication plays a crucial role in monitoring the aquatic environment on Earth. Due to their unique characteristics, underwater acoustic channels present unique challenges including lengthy signal transmission delays, limited data transfer bandwidth, variable signal quality, and fluctuating channel conditions. Furthermore, the reliance on battery power for most Underwater Wireless Acoustic Networks (UWAN) devices, coupled with the challenges associated with battery replacement or recharging, intensifies the challenges. Underwater acoustic communications are heavily constrained by available resources (e.g., very limited bandwidth, and limited energy storage). Consequently, the role of medium access control (MAC) protocol which distributes available resources among nodes is critical in maintaining a reliable underwater communication system. This study presents an extensive review of current research in MAC for UWAN. This study presents an extensive review of current research in MAC for UWAN. The paper explores the unique challenges and characteristics of UWAN, which are critical for the MAC protocol design. Subsequently, a diverse range of energy-efficient MAC techniques are categorized and reviewed. Potential future research avenues in energy-efficient MAC protocols are discussed, with a particular emphasis on the challenges to enable the broader implementation of the Green Internet of Underwater Things (GIoUT).

Underwater wireless communication networks (UWCNs) can support a wide range of applications in the underwater domain including: mining and drilling, coastline monitoring, border surveillance and submarine/mine detection. Some of these applications are sensitive in nature (e.g., military) and demand stringent security requirements for data communications. In order to prevent malicious attacks (e.g., jamming) in these UWCNs, robust security countermeasures must be implemented. Additionally, sensitive data communications must be protected. However, computationally expensive security protocols, such as encryption, can severely shorten UWCN lifetime, where battery-powered nodes already suffer from scarce energy supplies. In this work, we exploit content caching as a countermeasure for jamming and utilize selective encryption of sensitive data to simultaneously maximize network security and node residual energy in UWCNs. Our work formulates the joint security and residual energy maximization challenge as an optimization problem in which results indicate that the proposed technique can guarantee secure communications without sacrificing network lifespan.

In Industrial Internet of Things (IIoT), the volume of generated traffic can be high, causing concerns over issues, such as high energy consumption and longer access delay. Caching IIoT content at the network nodes is a promising solution to address these concerns. However, cached IIoT content at the network nodes is vulnerable to malicious attacks, which can cause significant disruptions in industrial operations. In order to monitor and prevent such malicious activities, trusted systems/nodes with supervisory control can be placed at the network nodes. In this article, we introduce the concept of the trusted caching node (TCN) for IIoT. TCNs cache popular IIoT content and ensure robust security to the connected links. This article finds the optimum location for the TCNs and selects secured-routes for content distribution. We formulate a joint optimization problem and minimize the cost related to probable content breach and energy consumption. We also design a low-complexity heuristic algorithm to solve this problem in real-time. The simulation results demonstrate that our proposed solution achieves significant performance gain and ensures secured IIoT content delivery.

Proactive content caching at the network-edge is envisioned as a key technique to reduce backhaul congestion and latency in popular content delivery. Data storage units, however, require additional energy, which offers a challenge to researchers who intend to reduce energy consumption up to 90% in next generation networks. The concept of powering data storage units by renewable energy aligns with this energy reduction target. In this article, we introduce a proactive caching strategy, which caches content in helper nodes in a cooperative manner considering intermittent renewable energy and variable content load for various hours of the day. The hypothesis is that the amount of renewable energy available to various helper nodes varies depending on the node location and time of the day. The content load across helper nodes also varies with time. As such, if helper nodes work cooperatively by considering the available renewable energy and content load at each helper node, the aggregate non-renewable energy consumption for content caching can be further reduced. We model the research challenge as an optimization problem. Furthermore, we also present a heuristic solution. Our proposed scheme achieves a significant reduction in non-renewable energy consumption by 23% over the existing green solution.

Streaming services have become increasingly popular in recent years, causing an upsurge in video traffic. The continuing upsurge will put enormous stress on existing network infrastructures. This has motivated researchers to find innovative solutions to address this challenge. Proactive content caching at the network edge is considered one such innovative solution, which can reduce backhaul congestion during evening peak hours. Consequently, researchers have introduced numerous approaches to cache content at the network edge. While the focus so far is on reducing the congestion, security issues in relation to content breach at caching nodes have not been adequately addressed so far. Content storage units at the network edge are more vulnerable to malicious attacks, and the loss incurred in this process can be significant. In this paper, we introduce a security aware caching technique to reduce the amount of potential loss caused by security attacks. We investigate the trade-off between the savings achieved from the implementation of proactive caching at caching nodes and the probable loss caused by security attacks. We model the research question as an optimization problem, and provide an optimal solution, which selects the suitable content to be cached at the most suitable nodes so that the loss caused by content breach becomes marginal. Simulation results show that our proposed technique significantly minimizes the loss caused by security attacks.

While the concept of ultra-dense small cell networks (SCNs) has brought a number of significant opportunities for the telecommunication industry, it has also introduced a major challenge for researchers, who must develop techniques to reduce the sharp increase in power consumption that will be required to backhaul traffic from SCNs to the core network. In this research, we investigate the green backhauling challenge for a fifth generation (5G) wireless communication network that uses both the passive optical network (PON) and millimeter wave (mmWave) backhauling to support its diverse groups of customers and applications. Our approach is based on the fact that the energy efficiency figures for the PON and the mmWave technologies are different under a given load condition. The PON technology is more energy efficient under heavy load conditions, whereas the mmWave technology offers better energy efficiency under low load conditions. As such, in response to varying traffic loads during various hours of the day, a fixed backhauling strategy is insufficient to guarantee the minimum power consumption and the required data rates. We formulate an optimization problem that considers the estimated hourly traffic load and determines the most energy efficient backhauling strategy for various hours of the day. Considering the complexity of the optimization problem, we also propose an energy efficient heuristic solution to solve this problem. Simulation results indicate that the proposed solution provides up to 32 percent more energy savings than the existing solution.

The concept of heterogeneous networks and small cells is likely to be a key addition to the fifth generation (5G) wireless communication standard, the prospect of which has motivated 5G researchers to investigate the coverage and integration of various small cells. Heterogeneous networks with small cells offer key benefits such as high frequency reuse, huge data rates and low power consumption for mobile nodes. High frequency reuse is particularly important given the exponential growth of data rates and the looming frequency scarcity problem. Another major consideration for 5G is the energy efficiency as with the exponential growth of demand, power consumption in the information and communication technology (ICT) sector is also expected to significantly increase. While the concept of small cells in heterogeneous networks addresses the frequency scarcity problem to a great extent, unless otherwise carefully managed, a large number of uncoordinated and lightly loaded small cells significantly increase the overall power consumption, contrary to the green communication target of the 5G standard. In this paper, we focus on an energy efficient resource management and planning system that investigates the impact of growing number of small cells in a macro cell. We present an analytical model for calculating the optimum number of small cells that need to be kept awake at various hours of a day for meeting the quality of service demands from all users. Simulation results show significant power consumption improvement than an existing model.

The deployment of mobile small cells has been identified as an effective strategy in delivering high data rates and providing seamless connectivity to a group of vehicular users. Although this approach can facilitate high data rates and ubiquitous wireless access, it introduces a new set of challenges, for instance, frequent changes in the interference set, requirements for more spectrum, high energy consumption and frequent handover. In this paper, we present a multi-hop mobile small cell network (SCN) that can facilitate wireless access to mobile nodes that do have direct transmission links to small cell base stations. We then formulate a solution to the frequency allocation problem for a multi-hop mobile SCN based on an optimization model. Considering the complexity of the optimization solution, we present a backhaul- aware frequency allocation solution based on the time-varying graph coloring concept. Simulation results confirm that the proposed solution outperforms an existing greedy solution by a significant margin in terms of throughput, spectral efficiency and fairness index.

ABSTRACT Call admission control (CAC) scheme serves as a useful tool for the WiMAX technology, which ensures that resources are not overcommitted and thereby, all existing connections enjoy guaranteed quality of service (QoS). CAC schemes largely rely on readily available information like currently available resources and bandwidth demand of the new call while making an acceptance or rejection decision once a new request arrives. Since wireless channels are not as reliable as wired communication, CAC scheme in WiMAX communication faces a serious challenge of making a right estimate of the usable channel capacity (i.e., effective throughput capacity) while computing the available resources in various communication scenarios. Existing CAC schemes do not consider the impact of mobility at vehicular speeds when computing the usable link capacity and available resources. The main limitation of such CAC scheme is that when a mobile node moves at a slower speed and makes a connection request to the base station (BS), the BS evaluates the situation based on the currently available information. The BS in such cases, is short‐sighted and often overestimates the available resources as it completely ignores the scenario when the SS reaches its top speed within a very short time after a CAC decision is made, causing a significant drop in usable throughput. In this paper, we address this limitation of existing WiMAX CAC schemes and propose a new CAC scheme that estimates the usable link capacity for WiMAX communication at vehicular speeds and uses this information while making a CAC decision. We also present a CAC scheme that takes the speed distribution model of a mobile node into account during the CAC decision making process. Simulation results confirm that the proposed scheme achieves lower dropping rate and improved QoS compared to existing schemes. Copyright © 2011 John Wiley & Sons, Ltd.

Poor cell-edge throughput is a well recognized problem in wireless communication technologies including 4G. Inter-cell interference (ICI), low signal to noise ratio (SNR) and inability to use an efficient modulation scheme in a low SNR environment are major problems in cell-edge regions in a multi- cell communication environment, which severely limits the spectral efficiency and cell-edge throughput. Mobility at vehicular speeds adds another dimension of problem for cell-edge users mainly because bit error rate increases exponentially with increasing vehicular speeds due to the multipath problem. 4G standards like LTE-A and WiMAX are currently considering various options to address this problem of low cell-edge throughput. One such option is to split the total radio resource among the cell center and cell-edge region, which allows frequency reuse, reduces ICI in cell-edge area, and supports CoMP transmission. In this paper, we show that simple resource splitting strategy like this, is not sufficient to support wireless communications at vehicular speeds. We propose a game theoretic model to resource management in 4G networks, which works well with nodes moving at high vehicular speeds. The ultimate benefit of the proposed scheme includes lower connection dropping rates for mobile nodes and higher revenue return for the service providers.

High speed wireless communication technologies such as Worldwide Interoperability for Microwave Access (WiMAX) have revolutionized the way of our day-to-day communication and opened opportunities for many innovative applications. The 802.6m version of WiMAX offers data rates up to 1 Gbps for fixed communications and supports mobility up to 350 km/h. While WiMAX technology's capacity to deliver high data rates in a fixed environment is beyond any doubt, the standard is not fully optimized yet for mobile communication at high vehicular speeds. At high vehicular speeds, rapid changes in surrounding environments, cause severe fading at the receiver, resulting a drastic fall in throughput and unless any proactive measure is taken to combat this problem, throughput becomes insufficient to support many applications, particularly those with multimedia contents. Bit Error Rate (BER) estimation is an integral part of any proactive measure and recent studies suggest that Nakagami-m model performs better for modeling channel fading in wireless communications at high vehicular speeds. No work has been reported in literature that estimates BER at high vehicular speeds in WiMAX communication using Nakagami-m model. In this paper, we develop and present an analytical model to estimate BER in WiMAX at vehicular speeds using Nakagami-m fading model. The proposed model is adaptive and can be used with resource management schemes designed for fixed, nomadic, and mobile WiMAX communications.

Intelligent transportation system (ITS) has enjoyed a tremendous growth in the last decade and the advancement in communication technologies has played a major role behind the success of ITS. Due to the nature of communication in vehicular environments, wireless access is considered as an integral part of any ITS system. The IEEE 1609.4 has evolved as a standard for wireless access for vehicular environment (WAVE), which describes multichannel access operations over the 5.9GHz dedicated short range communications (DSRC) spectrum. Communication Channels in the 1609.4 are grouped into service and control channels. Control channels (CCHs) are used for transmission of safety and management messages (e.g., traffic congestion data, data for emergency services) whereas service channels (SCHs) are used for the nodes to transmit service data (e.g., voice,video). In existing channel access mechanism, a node stays in the control channel to receive safety and management messages and then switches to service channel for data transmission. The key problem with this channel access mechanism is that half of the service channel intervals remain idle and unused as all nodes have to listen to control channel during that interval, which makes the WAVE system underutilized and inefficient. In this paper, we propose a medium access control (MAC) protocol for WAVE system to improve the channel utilization and reliability of safety messages. The proposed protocol has been developed based on the concept of cognitive radio and it outperforms the existing channel access mechanism by a significant margin in terms of channel utilization. Simulation results confirm that the proposed cognitive MAC protocol increases the channel utilization up to 70% compared to the IEEE 1609.4 standard, and maintains reliability for the safety related data transmission.

Voice and video over IP (VVoIP) applications are becoming very popular in Wi-Fi enabled portable/handheld devices, because of recent technological advancements and lower service costs. Video IP telephony service (an enhanced service of voice over IP (VoIP)) and video conferencing over IP networks are good examples of modern IP applications. Different from normal voice & video streaming, these applications demand symmetric throughputs for upstream and downstream. Existing Wi-Fi standards (e.g. IEEE 802.11e EDCA) however fail to provide symmetric throughput due to traffic bottleneck at access points. In this paper, we introduce a new real-time data performance attribute called IP traffic symmetry ratio (IPSR) and use IPSR to propose a round-robin scheduler with minimum overheads for video IP telephony and other similar applications. We refer to this scheduler as TI-MAC (Traffic Intelligent - MAC). The scheduler has been implemented and tested in actual hardware, and compared against IEEE 802.11e EDCA. The proposed scheduler shows significant improvements over existing standards by supporting more number of stations with strict QoS criteria.

A band-pass frequency selective surface (FSS) which is designed on energy saving glass (ESG) with a layer of hard coating to improve the transmission of RF/Microwave signals through modern buildings is presented. A square loop and top loaded cross dipoles FSSs are combined to produce a dual band-pass filter, to improve the transmission of the most common UMTS and Wi-Fi signals, while maintaining the IR insulation properties of the ESG. An optimized design is presented, which attenuates less than 10 dB within the required microwave bands, while only reducing both the total coating area and IR attenuation by 12.35%. A stable response is achieved between 0° - 60° incident angles, for both TE and TM polarizations. Parametric studies on geometrical dimensions, substrate permittivity and thickness also help clarify the effects of these parameters upon the overall performance of FSS on hard coating ESG and the process of FSS design optimization.

The IEEE 802.16e standard, also known as mobile WiMAX, has emerged as an exciting mobile wireless communication technology that promises to offer both high throughput and guaranteed quality of service (QoS). Call admission control (CAC) scheme serves as a useful tool for WiMAX, which ensures that resources are not overcommitted and thereby, all existing connections enjoy guaranteed QoS. Existing CAC schemes largely depend on readily available information like currently available resources and bandwidth demand of the new call while making an acceptance or rejection decision once a new request arrives. Since wireless channels are not as reliable as wired communication, CAC scheme in WiMAX communication faces a serious challenge of making a right estimate of the usable channel capacity (i.e., effective throughput capacity) while computing the available resources in various communication scenarios. Existing CAC schemes do not consider the impact of mobility at vehicular speeds when computing the usable link capacity and available resources. In this paper, we propose a new CAC scheme that estimates the usable link capacity for WiMAX communication at various vehicular speeds and uses this information while making a CAC decision. The proposed CAC scheme takes the speed distribution model of a mobile node into account during the CAC decision making process. Simulation results confirm that the proposed scheme achieves lower dropping rate and improved QoS compared to existing schemes.

The IEEE 802.16e standard has emerged as an exciting mobile wireless broadband technology that promises to deliver both high throughput and guaranteed quality of service (QoS). Call admission control (CAC) scheme serves as a great utility for WiMAX, which ensures that resources are not over committed and thereby, all existing connections enjoy guaranteed quality of service. Existing CAC schemes largely depend on computation of available resources while making an acceptance or rejection decision once a new request arrives. Since wireless channels are not as reliable as wired communication, CAC scheme in WiMAX communication faces a serious challenge of making a right estimate of the usable channel capacity while computing the available resources at various communication scenarios. Existing CAC schemes do not consider the impact of mobility at vehicular speeds when computing the usable link capacity and available resources. In this paper, we propose a new CAC scheme that estimates the usable link capacity for WiMAX communication at various vehicular speeds and uses this information while making a CAC decision. Extensive simulation results show that the proposed scheme achieves lower dropping rate and improved QoS compared to existing schemes.

Video surveillance on public transport is a useful tool to fight against anti-social behaviour like vandalism, harassment, graffiti and terrorism. Real-time video surveillance on moving public transport faces serious technological challenges mainly due to limited throughput offered by existing communication technologies at high vehicular speeds. Success of real-time video surveillance on public transport heavily depends on future communication technologies like WiMAX. WiMAX has emerged as an exciting technology with promises to offer high throughput and improved quality of services (QoS), key requirements for video surveillance on public transport. WiMAX however, offers limited throughput at high vehicular speeds mainly because of multipath fading that causes high bit error rate at the receiver at vehicular speeds. In our previous works, we showed that it is possible to estimate the bit error rate at the receiver end at various vehicular speeds in WiMAX and accordingly, some proactive measures can be adopted to improve the throughput to some extents. Overall throughput however, may still be insufficient to support the streaming video data from all the cameras mounted on a public transport at high vehicular speeds. In this paper, we propose a new scheme that estimates utility for different cameras and puts some low utility cameras offline and thereby maintains high utility of the video surveillance system when the throughput at high vehicular speeds become insufficient. Simulation results confirm the effectiveness of the proposed scheme.

Using p-Cycles to protect against single span failures in Wavelength-Division Multiplexing (WDM) networks has been widely studied. p-Cycle retains not only the speed of ring-like restoration, but also achieves the capacity efficiency over mesh networks. However, in selecting an optimal set of p-cycles to achieve the minimum spare capacity and fast computational time is an NP-hard problem. To address this issue, we propose a heuristic approach to iteratively select and refine a set of p-cycles, which contains two algorithms: the Heuristic p-Cycle Selection (HPS) algorithm, and the Refine Selected Cycles (RSC) algorithm. Our simulation results show that the proposed approach is within 3.5% redundancy difference from the optimal solution with very fast computation time even for large networks.

We propose a joint optimization model for capacity design of networks with p-cycles. The model is based on a modified definition of network fundamental cycles and the available straddling links. Concepts about visible and hidden straddling links, which are essential components of our model are also introduced. This is the first ILP model for joint optimization of p-cycle network that can be solved without enumerating p-cycle candidates, and has the ability to achieve optimum solutions. In addition, the complexity of our proposed model is much smaller than any conventional models, particularly when applying to a planar network. This model is suitable large size networks and for shared risk link group networks or backbone networks protected by p-cycle schemes.

The bufferless fluid flow model (BFFM) is often used in the literature for loss performance analysis. We propose an efficient and effective means of investigating cell loss using the BFFM. We define the cell loss rate function (CLRF) and use it to characterize the loss performance of traffic sources in the BFFM. Stochastic ordering theory is used to study the CLRF. The introduction of the stochastic ordering theory not only simplifies the theoretical analysis but also makes it possible to extend the scope of applications and theoretical analysis presented. A cell loss upper bound for heterogeneous on-off sources is proposed. The proposed cell loss upper bound is tighter than those previously proposed in the literature. A connection admission control (CAC) scheme using online measurements is designed based on the cell loss upper bound. Extensive simulation is carried out to study the performance of the CAC scheme. Particular attention is paid to the impact of inaccuracies in user-declared traffic parameters on the performance of the CAC scheme. Simulation results indicate that the proposed CAC scheme can ensure QoS guarantee, is robust to inaccuracies in declared traffic parameters, and is capable of achieving high link utilization.

On-off traffic source models are extensively used in connection admission control (CAC) schemes because of their simplicity and their ability to model real traffic sources. However, the calculation of the probability mass function of heterogeneous on-off sources entails a convolution operation which cannot be carried out in real time. Based on a bufferless fluid flow model this paper proposes the cell loss rate function (CLRF) and uses it for studying cell loss in bufferless systems. The properties of heterogeneous on-off sources in bufferless systems are extensively discussed using CLRF. A tight cell loss upper bound for heterogeneous on-off sources is proposed which results in great computational savings. The upper bound is applied in the CAC scheme. Simulation studies are presented which indicate that the upper bound is tight and the CAC scheme has a very good performance.