Achievable Transmission Rate Research Articles

Multi-Step FRET-Based Long-Range Nanoscale Communication Channel

Nanoscale communication based on Forster Resonance Energy Transfer (FRET) is a promising paradigm that allows future molecular-size machines to communicate with each other over distances up to 10 nm using the excited state energies of fluorescent molecules. In this study, we propose a novel nanoscale communication method based on multi-step FRET using identical fluorophores as relay nodes between communicating nanomachines, and utilizing multi-exciton transmission scheme in order to improve the limited range of the communication and achievable transmission rate over the nanoscale channel. We investigate two communication scenarios: immobile nanomachines communicating through a channel in a host material with linearly located relay nodes, and mobile nanomachines communicating through a channel in a 3-dimensional aqueous environment with randomly deployed relay nodes. We simulate the communication over these channels with realistic algorithms considering the high degree of randomness intrinsic to FRET phenomenon. Using the simulation results and following a Monte Carlo approach, we evaluate the performance of the channels by means of information theoretical capacity and interference probability. We show that multi-step FRET-based communication significantly outperforms the other biologically inspired nanocommunication techniques proposed so far in terms of maximum achievable data transmission rates. The results underline the compatibility and practicality of the FRET-based communication for several applications ranging from molecular computers to nanosensor networks.

Esense: Energy Sensing-Based Cross-Technology Communication

In this paper, we present Esense, a new paradigm of communication between devices that have fundamentally different physical layers. Esense is based on sensing and interpreting energy profiles. While our ideas are generic enough to be applicable in a variety of contexts, we illustrate the usefulness of our ideas by presenting novel solutions to existing problems in three distinct research domains. As part of these solutions, we demonstrate the ability to communicate between devices that follow two different standards: IEEE 802.11 and 802.15.4. We consider two scenarios here: 1) where there is no background traffic and 2) where there is background 802.11 traffic. In each case, we build an seta: a set of signature packet sizes that can be used for Esense communication. Specifically for the second case, we take a measurement-based alphabet set construction by considering WiFi traces from actual deployments. Based on practical observations and experiments, we theoretically quantify the maximum achievable transmission rate when using Esense. With background traffic, we could potentially construct an alphabet of size as high as 100. Such a large alphabet size promises efficient Esense communication. We show via a prototype implementation that effective communication is indeed feasible even when both sides use different physical layers.

Achievable Transmission Rate of the Secondary User in Cognitive Radio Networks with Hybrid Spectrum Access Strategy

A hybrid spectrum access strategy which is different from traditional underlay or overlay strategy is proposed for cognitive radio networks. In proposed strategy, the secondary users (SU) cooperatively sense the state of the primary user (PU) in a given spectrum band. Based on the sensing results and an additional requirement on the bit error rate, the SU adapts its transmit power and modulation level. Specifically, if the PU is inactive, the SU allocates its power subject to a peak transmit power constraint. Else if the PU is active, the average interference power constraint would be further imposed to protect the primary link. We assume that the maximal ratio combing (MRC) technique is available at the secondary receiver. Imperfect spectrum sensing and imperfect estimations of the channel power gain from the secondary transmitter to primary receiver are also considered. Achievable transmission rate of the SU over Rayleigh fading channel is formulated as an optimization problem and solved by using Lagrange dual decomposition method. Simulation results demonstrate that the transmission rate of the SU with hybrid strategy is significantly improved when compared with the traditional ones.

Quantum computing and communications – Introduction and challenges

Computer engineers are continuously seeking new solutions to increase available processing speed, achievable transmission rates, and efficiency in order to satisfy users’ expectations. While multi-core systems, computing clouds, and other parallel processing techniques dominate current technology trends, elementary particles governed by quantum mechanics have been borrowed from the physicists’ laboratory and applied to computer engineering in the efforts to solve sophisticated computing and communications problems. In this paper, we review the quantum mechanical background of quantum computing from an engineering point of view and describe the possibilities offered by quantum-assisted and quantum-based computing and communications. In addition to the currently available solutions, the corresponding challenges will also be surveyed.

Link Capacity Based Channel Assignment (LCCA) for Cognitive Radio Wireless Mesh Networks

Cognitive radio wireless mesh network (CRWMN) is expected as an upcoming technology with the potential advantages of both cognitive radio (CR) and the wireless mesh networks (WMN). In CRWMN, co-channel interference is one of the key limiting factors that affect the reception capabilities of the client and reduce the achievable transmission rate. Furthermore, it increases the frame loss rate and results in underutilization of resources. To maximize the performance of such networks, interference related issues need to be considered. Channel assignment (CA) is one of the key techniques to overcome the performance degradation of a network caused by the interferences. To counter the interference issues, we propose a novel CA technique which is based on link capacity, primary user activity and secondary user activity. These three parameters are fed to the proposed weightage decision engine to get the weight for each of the stated parameters. Thus, the link capacity based channel assignment (LCCA) algorithm is based on the weightage decision engine. The end-to-end delay, packet delivery ratio and the throughput is used to estimate the performance of the proposed algorithm. The numerical results demonstrate that the proposed algorithm is closer to the optimum resource utilization.

Dual Analysis of the Capacity of Spectrum Sharing Cognitive Radio with MRC under Nakagami-m Fading

In this study, the maximum achievable information transmission rate of spectrum sharing cognitive radio with maximal ratio combining (MRC) antenna diversity technique is investigated when the channel between the secondary transmitter and the primary receiver and that between the secondary transmitter and the secondary receiver suffer Nakagami-m fading. With an assumption that both channels encounter Nakagami-m fading and the transmission of the secondary transmitter is subject to average interference power constraint, the approximated expressions for analyzing the effective capacity and the ergodic capacity of cognitive radio users with MRC are presented. The two capacity models are compared. In the case of the effective capacity, it is shown that different applications or users with different quality of service (QoS) requirements can be supported in cognitive radio, and when the delay QoS decreases, the effective capacity approaches the ergodic capacity.

Power allocation for OFDM-based cognitive heterogeneous networks

In this paper, the capacity maximization and the spectrum utilization efficiency improvement are investigated for the Pico cells in broadband heterogeneous networks. In frequency-reuse model, the users attached to Macro base station are usually viewed as primary users, and those attached to Pico base station should be regarded as cognitive radio (CR) users. As both the primary users and the CR users communicate in parallel frequency bands, the performance of the system is limited by the mutual inter-carrier interference (ICI). In order to control ICI and maximize the achievable transmission rate of the CR users, an effective power allocation scheme is proposed to maximize the transmission rate of the CR users under a given interference threshold prescribed by the primary users. By transforming this suboptimal solution into an innovative matrix expression, the algorithm is easier to perform in practice. The simulation results demonstrate that the proposed algorithm provides a large performance gain in Pico cell capacity over the non-cooperative and equal power allocation schemes.

Subcarrier and Power Allocation for OFDMA-Based Cognitive Radio Systems With Joint Overlay and Underlay Spectrum Access Mechanism

In this paper, we study a subcarrier-and-power-allocation problem for orthogonal-frequency-division multiple-access (OFDMA)-based cognitive radio (CR) systems. In a departure from existing works in the literature that considered resource allocation for either an overlay spectrum access mechanism (OSAM) or an underlay spectrum access mechanism (USAM), we propose subcarrier-and-power-allocation schemes for a joint overlay and underlay spectrum access mechanism (JOUSAM). In particular, for such a CR system, the total transmission rate of CR users is maximized for a given power budget while keeping the interference introduced to the primary-user (PU) receivers' below given thresholds with a certain probability. As the optimal scheme can be highly complex, we also propose a low-complexity suboptimal subcarrier-and-power-allocation scheme. The selected numerical results show that a significant gain in terms of total achievable transmission rate can be obtained over an USAM or an OSAM. These selected numerical results also show that the proposed suboptimal scheme, which has a very low complexity, provides a significant improvement in performance over either underlay or overlay spectrum access mechanism. The proposed optimal scheme can lead to an unfairness among CR users in sharing the total transmission rate; therefore, we also propose a suboptimal subcarrier-allocation scheme that can guarantee a certain level of fairness among CR users.

Near-Optimal Waveform Design for Sum Rate Optimization in Time-Reversal Multiuser Downlink Systems

Utilizing channel reciprocity, the traditional time-reversal technique boosts the signal-to-noise ratio at the receiver with very low transmitter complexity. However, the large delay spread gives rise to severe inter-symbol interference (ISI) when the data rate is high, and the achievable transmission rate is further degraded in the multiuser downlink due to the inter-user interference (IUI). In this work, we study the weighted sum rate optimization problem by means of waveform design in the time-reversal multiuser downlink where the receiver processing is based on a single sample. Power allocation has a significant impact on the waveform design problem. We propose a new power allocation algorithm named Iterative SINR Waterfilling, which is able to achieve comparable sum rate performance to that of globally optimal power allocation. We further propose another approach called Iterative Power Waterfilling for multiple data streams. Iterative SINR Waterfilling provides better performance than Iterative Power Waterfilling in the scenario of high interference, while Iterative Power Waterfilling can work under multiple data streams. Simulation results show the superior performance of the proposed algorithms in comparison with other waveform designs such as zero-forcing and conventional time-reversal waveform.

Scalable Video Multicast Over Multi-Antenna OFDM Systems

We propose a framework for efficient scalable video multicast over downlink orthogonal frequency-division multiplexing (OFDM) systems with multiple transmit antennas. In conventional video multicast systems, the achievable transmission rate is determined by the user with the worst channel condition, and the system saturates the capacity when the number of users increases. To accommodate the heterogeneous channel conditions and device capabilities of various users, scalable video coding (SVC) encodes video streams into base and enhancement layers. We exploit the advances in multi-antenna OFDM and the layered nature of SVC, and propose a framework for scalable video multicast which guarantees the base layer quality for all users while making best use of limited resource for the enhancement layer of users with good channel conditions. We show that the resource allocation that includes the transmit precoding, subcarrier allocation, and bit and power allocation is a very difficult optimization problem. A low-complexity suboptimal algorithm is proposed which is suitable for practical implementations. Simulation results are provided to show the effectiveness of the proposed solution.

On Capacity and Optimal Scheduling for the Half-Duplex Multiple-Relay Channel

We study the half-duplex multiple-relay channel (HD-MRC) where every node can either transmit or listen but cannot do both at the same time. We obtain a capacity upper bound based on a max-flow min-cut argument and achievable transmission rates based on the decode-forward (DF) coding strategy, for both the discrete memoryless HD-MRC and the phase-fading HD-MRC. We discover that both the upper bound and the achievable rates are functions of the transmit/listen state (a description of which nodes transmit and which receive). More precisely, they are functions of the time fraction of the different states, which we term a schedule. We formulate the optimal scheduling problem to find an optimal schedule that maximizes the DF rate. The optimal scheduling problem turns out to be a maximin optimization, for which we propose an algorithmic solution. We demonstrate our approach on a four-node multiple-relay channel, obtaining closed-form solutions in certain scenarios. Furthermore, we show that for the received signal-to-noise ratio degraded phase-fading HD-MRC, the optimal scheduling problem can be simplified to a max optimization.

Interference Alignment with Cooperative Primary Receiver in Cognitive Networks

In cognitive radio systems, secondary users may transmit signals by aligning their signal directions to the primary user's unused directions. However, their achievable transmission rates are very low in moderate to high SNR regime because the primary user takes most of available degrees of freedom (DoF). In order to increase the secondary transmission rate, we consider the case that the primary receiver performs interference suppression filtering. By counting the number of variables and the number of equations in the interference alignment (IA) condition, we analyze the secondary users' achievable DoF, which is higher than the conventional scheme. Simulation results show that the primary receiver's participation in IA significantly increases the secondary rate with negligible primary rate reduction.

Low-Complexity Near-Optimum Multiple-Symbol Differential Detection of DAPSK Based on Iterative Amplitude/Phase Processing

Differentially encoded and noncoherently detected transceivers exhibit low complexity since they dispense with a complex channel estimation. In pursuit of high bandwidth efficiency, differential amplitude/phase (A/P)-shift keying (DAPSK) was devised using constellations of multiple concentric rings. To increase resilience against the typical high-Doppler-induced performance degradation of DAPSK and/or to enhance the maximum achievable error-free transmission rate for DAPSK-modulated systems, multiple-symbol differential detection (MSDD) may be invoked. However, the complexity of the maximum a posteriori (MAP) MSDD exponentially increases with the detection window size and hence may become excessive upon increasing the window size, particularly in the context of an iterative detection-aided channel-coded system. To circumvent this excessive complexity, we conceive a decomposed two-stage iterative A/P detection framework, where the challenge of having a nonconstant-modulus constellation is tackled with the aid of a specifically designed information exchange between the independent A/P detection stages, thus allowing the incorporation of reduced-complexity sphere detection (SD). Consequently, a near-MAP-MSDD performance can be achieved at significantly reduced complexity, which may be five orders of magnitude lower than that of the traditional MAP-MSDD in the 16-DAPSK scenario that was considered.

Information‐Theoretic Analysis of Underwater Acoustic OFDM Systems in Highly Dispersive Channels

This paper investigates the signal‐to‐interference ratio and the achievable rates of underwater acoustic (UA) OFDM systems over channels where time and frequency dispersion are high enough that (i) neither the transmitter nor the receiver can have a priori knowledge of the channel state information and (ii) intersymbol/intercarrier interference (ISI/ICI) cannot be neglected in the information‐theoretic treatment. The goal of this study is to obtain a better understanding of the interplay between interference and the achievable transmission rates. Expressions for these rates take into account the “cross‐channels” established by the ISI/ICI and are based on lower bounds on mutual information that assume independent and identically distributed input data symbols. In agreement with recent statistical analyses of experimental shallow‐water data, the channel is modeled as a multivariate Rician fading process with a slowly time‐varying mean and with potentially correlated scatterers, which is more general than the common wide‐sense stationary uncorrelated scattering model. Numerical assessments on real UA channels with spread factors around 10−1 show that reliable OFDM transmissions at 2 to 4 bits/sec/Hz are achievable provided an average signal‐to‐noise ratio of 15 to 20 dB.

Novel Reduced-Feedback Wireless Communication Systems

Modern communication systems apply channel-aware adaptive transmission techniques and dynamic resource allocation in order to exploit the peak conditions of the fading wireless links and to enable significant performance gains. However, conveying the channel state information among the users’ mobile terminals into the access points of the network consumes a significant portion of the scarce air-link resources and depletes the battery resources of the mobile terminals rapidly. Despite its evident drawbacks, the channel information feedback cannot be eliminated in modern wireless networks because blind communication technologies cannot support the ever-increasing transmission rates and high quality of experience demands of current ubiquitous services. Developing new transmission technologies with reduced-feedback requirements is sought. Network operators will benefit from releasing the bandwidth resources reserved for the feedback communications and the clients will enjoy the extended battery life of their mobile devices. The main technical challenge is to preserve the prospected transmission rates over the network despite decreasing the channel information feedback significantly. This is a noteworthy research theme especially that there is no mature theory for feedback communication in the existing literature despite the growing number of publications about the topic in the last few years. More research efforts are needed to characterize the trade-off between the achievable rate and the required channel information and to design new reduced-feedback schemes that can be flexibly controlled based on the operator preferences. Such schemes can be then introduced into the standardization bodies for consideration in next generation broadband systems. We have recently contributed to this field and published several journal and conference papers. We are the pioneers to propose a novel reduced-feedback opportunistic scheduling scheme that combines many desired features including fairness in resources distribution across the active terminals and distributed processing at the MAC layer level. In addition our scheme operates close to the upper capacity limits of achievable transmission rates over wireless links. We have also proposed another hybrid scheme that enables adjusting the feedback load flexibly based on rates requirements. We are currently investigating other novel ideas to design reduced-feedback communication systems.

Floating content for probabilistic information sharing

People are increasingly using online social networks for maintaining contact with friends and colleagues irrespective of their physical location. While such services are essential to overcome distances, using infrastructure services for location-based services may not be desirable. In contrast, we design and analyze a fully distributed variant of an ephemeral content sharing service, solely dependent on the mobile devices in the vicinity using principles of opportunistic networking. The result is a best effort service for floating content in which content is created locally, its availability is geographically limited and its lifetime and spreading depends on interested nodes being available. In this paper, we present our system design, algorithms, and protocol specification in detail. A set of real world experiments is then used to assess the achievable transmission rates and transmission ranges in such a system. We validate our previous analytical results and assess the performance of floating content in general and especially of different replication and deletion strategies by means of extensive simulations using a map-based mobility model in downtown Helsinki.

Information-Guided Transmission in Decode-and-Forward Relaying Systems: Spatial Exploitation and Throughput Enhancement

In addressing the issue of achieving high throughput in half-duplex relay channels, we exploit a concept of information-guided transmission for the network consisting of a source node, a destination node, and multiple half-duplex relay nodes. For further benefiting from multiple relay nodes, the relay-selection patterns are defined as the arbitrary combinations of given relay nodes. By exploiting the difference among the spatial channels states, in each relay-help transmission additional information to be forwarded is mapped onto the index of the active relay-selection pattern besides the basic information mapped onto the traditional constellation, which is forwarded by the relay node(s) in the active relay-selection pattern, so as to enhance the relay throughput. With iterative decoding, the destination node can achieve a robust detection by decoupling the signals forwarded in different ways. We investigate the proposed scheme considering "decode-and-forward" protocol and establish its achievable transmission rate. The analytical results on capacity behaviors prove the efficiency of the proposed scheme by showing that it achieves better capacity performance than the conventional scheme.

The Multicast Capacity of Large Multihop Wireless Networks

We consider wireless ad hoc networks with a large number of users. Subsets of users might be interested in identical information, and so we have a regime in which several multicast sessions may coexist. We first calculate an upper bound on the achievable transmission rate per multicast flow as a function of the number of multicast sources in such a network. We then propose a simple comb-based architecture for multicast routing, which achieves the upper bound in an order sense under certain constraints. Compared to the approach of constructing a Steiner tree to decide multicast paths, our construction achieves the same order-optimal results while requiring little location information and no computational overhead.

OSNR Monitoring for Higher Order Modulation Formats Using Asynchronous Amplitude Histogram

We propose an asynchronous-amplitude-histogram-based optical signal-to-noise ratio monitoring technique for higher order modulation formats. Simulation results show that the proposed technique enables a wide monitoring range for 25-GSym/s nonreturn-to-zero/return-to-zero 16- and 64-quadrature amplitude modulation systems with high monitoring sensitivity. The tolerance of the monitoring technique to other signal impairments such as chromatic dispersion and polarization-mode dispersion is also investigated. The proposed technique can be used along transmission links with simple low-cost hardware and/or in digital signal processing (DSP)-based coherent receivers without additional hardware, thus enabling next-generation optical networks using higher order modulation formats to achieve transmission rates of 100 Gb/s per channel and beyond.

Group-Orthogonal Code-Division Multiplex: A Physical-Layer Enhancement for IEEE 802.11n Networks

The new standard for wireless local area networks (WLANs), named IEEE 802.11n, has been recently released. This new norm builds upon and remains compatible with the previous WLANs standards IEEE 802.11a/g while it is able to achieve transmission rates of up to 600 Mbps. These increased data rates are mainly a consequence of two important new features: (1) multiple antenna technology at transmission and reception, and (2) optional doubling of the system bandwidth thanks to the availability of an additional 20 MHz band. This paper proposes the use of Group-Orthogonal Code Division Multiplex (GO-CDM) as a means to improve the performance of the 802.11n standard by further exploiting the inherent frequency diversity. It is explained why GO-CDM synergistically matches with the two aforementioned new features and the performance gains it can offer under different configurations is illustrated. Furthermore, the effects that group-orthogonal has on key implementation issues such as channel estimation, carrier frequency offset, and peak-to-average power ratio (PAPR) are also considered.