This paper provides an overview of power line communication (PLC) applications, challenges and possible evolution. Emphasis is put on two relevant aspects: a) channel characterization and modeling, b) filter bank modulation for spectral efficient transmission. The main characteristics of both the indoor channel (in-home, in-ship, in-car) and the outdoor low voltage and medium voltage channels are reported and compared. A simple approach to statistically model the channel frequency response (CFR) is described and it is based on the generation of a vector of correlated random variables. To overcome the channel distortions, it is shown that filter bank modulation can provide robust performance. In particular, it is shown that the sub-channel spectral containment of filtered multitone modulation (FMT) can provide high notching capability and spectral efficiency. Reduced complexity can be obtained with a cyclic filter bank modulation approach that we refer to as cyclic block FMT modulation (CB-FMT) which still provides higher spectral flexibility/efficiency than OFDM.
Mobile video services are becoming a dominant traffic category in emerging fourth generation (4G) cellular networks such as the 3GPP Long-Term Evolution (LTE) and LTE-Advanced (LTE-A). In particular, mobile video unicasting services based on 3GPP Dynamic Adaptive Streaming over HTTP (DASH) and multicasting/broadcasting services based on 3GPP evolved Multimedia Multicast/Broadcast Service (eMBMS) will require considerable resources for high-quality service delivery with high coverage probability. Faced with the challenge of energy efficient multimedia service provisioning over LTE/LTE-A, in this paper, we present simple analytical tools for evaluation of average service data rates, bandwidth and energy-consumption requirements applicable for different multimedia delivery services and LTE/LTE-A radio access network (RAN) configurations. Moreover, we introduce and evaluate novel energy and bandwidth performance measures defined per unit of service. As a result, we are able to compare the efficiency of different multimedia service delivery configurations over LTE/LTE-A. In particular, in this paper, as a running example we focus on eMBMS and compare the Energy of Service (EoS) of the two macro-cellular LTE/LTE-A configurations recently proposed in 3GPP: i) a single frequency network eMBMS (SFN-eMBMS), and ii) a single-cell eMBMS (SC-eMBMS). Furthermore, we extend this analysis to eMBMS provisioning over Heterogeneous Networks (HetNets) environment. However, the methodology presented is general and targets light-weight system design and comparison of bandwidth/energy costs of different LTE/LTE-A multimedia service delivery configurations.
This paper assesses the main challenges associated with the propagation and channel modeling of broadband radio systems in a complex environment of high speed and metropolitan railways. These challenges comprise practical simulation, modeling interferences, radio planning, test trials and performance evaluation in different railway scenarios using Long Term Evolution (LTE) as test case. This approach requires several steps; the first is the use of a radio propagation simulator based on ray-tracing techniques to accurately predict propagation. Besides the radio propagation simulator, a complete test bed has been constructed to assess LTE performance, channel propagation conditions and interference with other systems in real-world environments by means of standard-compliant LTE transmissions. Such measurement results allowed us to evaluate the propagation and performance of broadband signals and to test the suitability of LTE radio technology for complex railway scenarios.
Digital coherent receivers have gained significant attention in the last decade. The reason for this is that coherent detection, along with digital signal processing (DSP) allows for substantial increase of the channel capacity by employing advanced detection techniques. In this paper, we first review coherent detection technique employed in the receiver as well as the required receiver structure. Subsequently, we describe the core part of the receiver — DSP algorithms — that are used for data processing. We cover all basic elements of a conventional coherent receiver DSP chain: deskew, orthonormaliation, chromatic dispersion compensation/nonlinear compensation, resampling and timing recovery, polarization demultiplexing and equalization, frequency and phase recovery, digital demodulation. We also describe novel subsystems of a digital coherent receiver: modulation format recognition and impairment mitigation via expectation maximization, which may gain popularity with increasing importance of autonomous networks.
The next generation of information technology demands both high capacity and mobility for applications such as high speed wireless access capable of supporting broadband services. The transport of wireless and wireline signals is converging into a common telecommunication infrastructure. In this paper, we will present the Marie Curie Framework Program 7 project “Wireless and wireline service convergence in next generation optical access networks” (WISCON), which focuses on the conception and study of novel architectures for wavelength-division-multiplexing (WDM) optical multi-modulation format radio-over-fiber (RoF) systems; this is a promising solution to implement broadband seamless wireless -wireline access networks. This project successfully concluded in autumn 2013, and is being follow up by another Marie Curie project entitled “flexible edge nodes for dynamic optical interconnection of access and core networks” (FENDOI), which will be also briefly described.
When deploying a new mobile technology such as LTE, it is crucial to identify the factors that affect the radio network in terms of capacity and quality of service. In this context, network coverage is arguably the single most influential factor. This work presents a metaheuristic-optimization approach to automatically adapt the signal losses due to clutter, based on a set of field measurements. The optimization procedure is performed regionally, enabling the calculation of accurate radio-propagation predictions. The evaluation of the proposed approach is carried out on three different regions in Slovenia, where Telekom Slovenije, d.d., provides LTE coverage. The results show radio-propagation predictions of improved quality and the benefits of the presented approach over manual methods, both in terms of problem size and solution accuracy.
This paper studies an underlay-based cognitive two-way relay network which consists of a primary network (PN) and a secondary network (SN). Two secondary users (SUs) exchange information with the aid of multiple single-antenna amplify-and-forward relays while a primary transmitter communicates with a primary receiver in the same spectrum. Unlike the existing contributions, the transmit powers of the SUs and the distributed beamforming weights of the relays are jointly optimized to minimize the sum interference power from the SN to the PN under the quality-of-service (QoS) constraints of the SUs determined by their output signal-to-interference-plus-noise ratio (SINR) and the transmit power constraints of the SUs and relays. This approach leads to a non-convex optimization problem which is computationally intractable in general. We first investigate two necessary conditions that optimal solutions should satisfy. Then, the non-convex minimization problem is solved analytically based on the obtained conditions for single-relay scenarios. For multi-relay scenarios, an iterative numerical algorithm is proposed to find suboptimal solutions with low computational complexity. It is shown that starting with an arbitrarily initial feasible point, the limit point of the solution sequence derived from the iterative algorithm satisfies the two necessary conditions. To apply this algorithm, two approaches are developed to find an initial feasible point. Finally, simulation results show that on average, the proposed low-complexity solution considerably outperforms the scheme without source power control and performs close to the optimal solution obtained by a grid search technique which has prohibitively high computational complexity.
This paper investigates power allocation and outage performance for the MIMO full duplex relaying (MFDR) based on orthogonal space-time block Codes (OSTBC) in cognitive radio systems. OSTBC transmission is used as a simple way to obtain multi-antenna diversity gain. Cognitive MFDR systems offer the advantage not only of increasing spectral efficiency by spectrum sharing but also of extending the coverage through the use of relays. In cognitive MFDR systems, the primary user experiences interference from the secondary source and relay simultaneously due to the full duplexing. What is therefore needed is a way to optimize the transmission powers at the secondary source and relay. Therefore, we propose an optimal power allocation (OPA) scheme based on minimizing the outage probability in cognitive MFDR systems. We then analyze the outage probability of the secondary user in the noise-limited and interference-limited environments under Nakagami-m fading channels. Simulation results show that the proposed schemes achieve performance improvement in terms of outage probability.
Cognitive radio is one of the most promising wireless technologies and has been recognized as a new way to improve the spectral efficiency of wireless networks. In a cognitive radio network, secondary users exchange control information for network coordination such as transmitter-receiver handshakes, for sharing spectrum sensing results, for neighbor discovery, to maintain connectivity, and so on. Spectrum utilization and resource optimizations thus rely on information exchange among secondary users. Normally, secondary users exchange the control information via a predefined channel, called a common control channel (CCC). Most of the medium access control (MAC) protocols for cognitive radio networks were designed by assuming the existence of a CCC, and further assuming that it was available for every secondary user. However, the main drawback of using a static CCC is it is susceptible to primary user activities since the channel can be occupied by primary users at any time. In this paper, we propose a MAC protocol for cognitive radio networks with dynamic control channel assignment, called DYN-MAC. In DYN-MAC, a control channel is dynamically assigned based on spectrum availability. Thus, it can tolerate primary user activities. DYN-MAC also supports collision free network-wide broadcasting and addresses other major problems such as primary/secondary user hidden terminal problems.
In this paper, a low-complexity precoding scheme for minimizing the bit error rate (BER) subject to fixed power constraint for distributed antenna systems with non-Kronecker correlation over spatially correlated Rayleigh fading channels is presented. Based on an approximated BER bound and a newly defined compressed signal-to-noise ratio (CSNR) criterion, closed-form expressions of power allocation and beamforming matrix are derived for the developed precoding scheme. This scheme not only has the calculation of the power allocation less than and also obtain the BER performance close to that of the existing optimal precoding scheme. Simulation results show that the proposed scheme can provide BER lower than the equal power allocation and single mode beamforming scheme, has almost the same performance as the existing optimal scheme.
This paper presents a new, accurate multi-service model of a queueing system with state-dependent distribution of resources for each class of calls. The analysis of the considered queueing system was carried out at both the microstate and macrostate levels. The proposed model makes it possible to evaluate averaged parameters of queues for individual classes of calls that are offered to the system. In addition, the paper proposes a new algorithm for a determination of the occupancy distribution in the queueing system at the microstate level. The results of the calculations are compared with the results of a digital simulation for multi-service queueing systems with state-independent distribution of resources.
High-speed wireless access technologies have evolved over the last years setting new challenges for TCP. That is, to effectively utilize the available network resources and to minimize the effects of wireless channel errors on TCP performance. This paper introduces a new TCP variant, called TCP-BIAD aiming at enhancing TCP performance in broadband wireless access networks. We provide analytical expressions for evaluating the stability, throughput, fairness and friendliness properties of our proposal, and we validate our results by means of computer simulations. Initial results presented in this paper show that this approach achieves high network utilization levels in a wide range of network conditions, while maintaining an adequately fair and friendly behavior with respect to coexisting TCP flows.
We theoretically analyze the performance of free-space optical (FSO) systems using cooperative-ARQ (C-ARQ), a joint scheme of automatic-repeat-request (ARQ) and cooperative diversity, over atmospheric turbulence channels. We also propose a modified C-ARQ (M-C-ARQ) scheme that allows relay nodes to store a copy of frames for the more efficient response to transmission failure so that both transmission delay and energy consumption can be improved. Using Markov chain-based analytical models for both schemes, the system performance is analytically studied in terms of frame-error rate, goodput and energy efficiency, which directly reflect the transmission delay and energy consumption. Numerical results confirm that the proposed schemes outperform conventional ones. In addition, we discuss cross-layer design strategies for selecting parameters in both physical and link layers in order to optimize the performance of FSO systems over different atmospheric turbulence conditions and channel distances.
An integrated 2×28Gb/s dual-channel duobinary driver IC is presented. Each channel has integrated coding blocks, transforming a non-return-to-zero input signal into a 3-level electrical duobinary signal to achieve an optical duobinary modulation. To the best of our knowledge this is the fastest modulator driver including on-chip duobinary encoding and precoding. Moreover, it only consumes 652mW per channel at a differential output swing of 6Vpp.
The dynamic characteristics of the class E power amplifier with frequency modulation are derived. Such an analysis is essential for designing amplitude and frequency modulated amplifier systems such as an EER scheme. Conventionally, an analytical expression for the frequency response of a frequency modulated class E amplifier has not been derived yet. This omission is rectified here by modeling the circuit with both a low-frequency model and a high-frequency model. Further, a time domain waveform is derived from the frequency domain transfer function for some typical time varying drive signals. The analytical results for the frequency response of a 1-MHz class E amplifier are shown to match PSpice simulations and measured values well.
Maximizing network lifetime and optimizing aggregate system utility are important but usually conflict goals in wireless multi-hop networks. For the trade-off, we present a matrix game-theoretic cross-layer optimization formulation to jointly maximize the diverse objectives in such networks with network coding. To this end, we introduce a cross-layer formulation of general network utility maximization (NUM) that accommodates routing, scheduling, and stream control from different layers in the coded networks. Specifically, for the scheduling problem and then the objective function involved, we develop a matrix game with the strategy sets of the players corresponding to hyperlink and transmission mode, and design multiple payoffs specific to lifetime and system utility, respectively. In particular, with the inherit merit that matrix game can be solved with mathematical programming, our cross-layer programming formulation actually benefits from both game-based and NUM-based approaches at the same time by cooperating the programming model for the matrix game with that for the other layers in a consistent framework. Finally, our numerical experiments quantitatively exemplify the possible performance trad-offs with respect to the two variants developed on the multiple objectives in question while qualitatively exhibiting the differences between the framework and the other related works.
Time synchronization is important for frequency hopping, power management, scheduling, and basic operations of multi-hop ad-hoc networks. The main problem of existing time synchronization methods is that they depend on a particular node that has the fastest time information among neighbor nodes. The Cucker-Smale flocking model describes that global emergent behavior can be obtained by locally averaging the velocity of each bird. Inspired by this flocking model, we propose a time synchronization method not depending on a particular node. In the proposed method, each node revises its time information via the local-averaging procedure in a distributed manner. A self-correcting procedure is added to the proposed method in order to preserve the effect of time adjustment executed by the local-averaging procedure. The simulation results show that the proposed time synchronization method reduces the time difference among nodes, and enhances the performance of time synchronization in the context of IEEE 802.11-based ad-hoc networks.
This paper presents a data gathering protocol for wireless sensor network applications that require high throughput and topology adaptability under the premises of uniform traffic and energy-rich environments. Insofar as high throughput is concerned, TDMA is more suitable than CSMA. However, traditional TDMA protocols require complex scheduling of transmission time slots. The scheduling burden is the primary barrier to topology adaptability. Under the premises of uniform traffic and energy-rich environments, this paper proposes a token-scheduled multi-channel TDMA protocol named TKN-TWN to ease the scheduling burden while exploiting the advantages of TDMA. TKN-TWN uses multiple tokens to arbitrate data transmission. Due to the simplified scheduling based on tokens, TKN-TWN is able to provide adaptability for topology changes. The contention-free TDMA and multi-channel communication afford TKN-TWN the leverage to sustain high throughput based on pipelined packet forwarding. TKN-TWN further associates the ownership of tokens with transmission slot assignment toward throughput optimization. We implement TKN-TWN on Tmote Sky with TinyOS 2.1.1 operating system. Experimental results in a deployed network consisting of 32 sensor nodes show that TKN-TWN is robust to network changes caused by occasional node failures. Evaluation also shows that TKN-TWN is able to provide throughput of 9.7KByte/s.
Proxy Mobile IPv6 (PMIPv6) was standardized to reduce the long handoff latency, packet loss and signaling overhead of MIPv6 protocol and to exempt the mobile node from any involvement in the handoff process. However, the basic PMIPv6 does not provide any buffering scheme for packets during MNs handoff. In addition, all the binding update messages are processed by a Local Mobility Anchor (LMA) which leads to increase the handoff latency. Previous works enhanced PMIPv6 performance by applying fast handoff mechanisms to reduce the packet loss during handoffs; however, the LMA is still involved during the location update operations. In this paper, we present a new fast handoff scheme based on a cluster-based architecture for the PMIPv6 named Fast handoff Clustered PMIPv6 (CFPMIPv6); it reduces both the handoff signaling and packet loss ratio. In the proposed scheme, the Mobility Access Gateways (MAGs) are grouped into clusters with a one distinguished Head MAG (HMAG) for each cluster. The main role of the HMAG is to carry out the intra-cluster handoff operations and provide fast and seamless handoff services. The proposed CFPMIPv6 is evaluated analytically and compared with the previous work including the basic PMIPv6, Fast PMIPv6 based on Multicast MAGs group (MFPMIPv6), and the Fast Handoff using Head MAG schemes (HFPMIPv6). The obtained numerical results show that the proposed CFPMIPv6 outperforms all the basic PMIPv6, MFPMIP6, and HFPMIPv6 schemes in terms of the handoff signaling cost.
Open-access femtocell networks assure the cellular user of getting a better and stronger signal. However, due to the small range of femto base stations (FBSs), any motion of the user may trigger handover. In a dense environment, the possibility of such handover is very frequent. To avoid frequent communication disruptions due to phenomena such as the ping-pong effect, it is necessary to ensure the effectiveness of the cell selection method. Existing selection methods commonly uses a measured channel/cell quality metric such as the channel capacity (between the user and the target cell). However, the throughput experienced by the user is time-varying because of the channel condition, i.e., owing to the propagation effects or receiver location. In this context, the conventional approach does not reflect the future performance. To ensure the efficiency of cell selection, user's decision needs to depend not only on the current state of the network, but also on the future possible states (horizon). To this end, we implement a learning algorithm that can predict, based on the past experience, the best performing cell in the future. We present in this paper a reinforcement learning (RL) framework as a generic solution for the cell selection problem in a non-stationary femtocell network that selects, without prior knowledge about the environment, a target cell by exploring past cells' behavior and predicting their potential future states based on Q-learning algorithm. Then, we extend this proposal by referring to a fuzzy inference system (FIS) to tune Q-learning parameters during the learning process to adapt to environment changes. Our solution aims at minimizing the frequency of handovers without affecting the user experience in terms of channel capacity. Simulation results demonstrate that · our solution comes very close to the performance of the opportunistic method in terms of capacity, while fewer handovers are required on average. · the use of fuzzy rules achieves better performance in terms of received reward (capacity) and number of handovers than fixing the values of Q-learning parameters.
This paper proposes the assignment of resource blocks (RBs) to reduce the peak-to-average power ratio (PAPR) of orthogonal frequency division multiplexing (OFDM) in a multi-user OFDM system. This system ranks the users according to the channel state information (CSI) for RB assignment. In our proposed technique, an RB is assigned to either the first- or second-ranked mobile station (MS) to minimize the PAPR of the OFDM signal. While this process reduces the PAPR, the throughput is also reduced because of the user diversity gain loss. A PAPR-throughput tradeoff is then established. Theoretical analyses and computer simulations confirm that when the number of MSs becomes large, the PAPR-throughput tradeoff is eased because of the minimal effect of the diversity gain loss. Therefore, significant PAPR reduction is achieved with only a slight degradation in the throughput.
Multicell cooperation is a promising technique to mitigate the inter-cell interference and improve the sum rate in cellular systems. Limited feedback design is of great importance to base station cooperation as it provides the quantized channel state information (CSI) of both the desired and interfering channels to the transmitters. Most studies on multicell limited feedback deal with scenarios of a single receive antenna at the mobile user. This paper, however, applies limited feedback to cooperative multicell multiple-input multiple-output (MIMO) systems where both base stations and users are equipped with multiple antennas. An optimized feedback strategy with random vector quantization (RVQ) codebook is proposed for interference aware coordinated beamforming that approximately maximizes the lower bound of the sum rate. By minimizing the upper-bound on the mean sum-rate loss induced by the quantization errors, we present a feedback-bit allocation algorithm to divide the available feedback bits between the desired and interfering channels for arbitrary number of transmit and receive antennas under different interfering signal strengths. Simulation results demonstrate that the proposed scheme utilizes the feedback resource effectively and achieves sum-rate performance reasonably close to the full CSI case.
By exploiting the inherent sparsity of wireless propagation channels, the theory of compressive sensing (CS) provides us with novel technologies to estimate the channel state information (CSI) that require considerably fewer samples than traditional pilot-aided estimation methods. In this paper, we describe the block-sparse structure of the fast time-varying channel and apply the model-based CS (MCS) for channel estimation in orthogonal frequency division multiplexing (OFDM) systems. By exploiting the structured sparsity, the proposed MCS-based method can further compress the channel information, thereby allowing a more efficient and precise estimation of the CSI compared with conventional CS-based approaches. Furthermore, a specific pilot arrangement is tailored for the proposed estimation scheme. This so-called random grouped pilot pattern can not only effectively protect the measurements from the inter-carrier interference (ICI) caused by Doppler spreading but can also enable the measurement matrix to meet the conditions required for MCS with relatively high probability. Simulation results demonstrate that our method has good performance at high Doppler frequencies.
The use of cooperative nodes is effective for enhancing the reliability of wireless data transmission between a source and a destination by means of transmit diversity effect. However, in its application to wireless multi-hop networks, how to form cooperative node candidates and how to select multiple cooperative nodes out of them have not been well investigated. In this paper, we propose a multiple cooperative node selection method based on a criterion composed of “quality” and “angle” metrics, which can select and order adequate cooperative nodes. Computer simulation results show that the proposed method can effectively reduce the packet error rate without any knowledge on node location.
The increasing demand of indoor location based service (LBS) has promoted the development of localization techniques. As an important alternative, fingerprinting localization technique can achieve higher localization accuracy than traditional trilateration and triangulation algorithms. However, it is computational expensive to construct the fingerprint database in the offline phase, which limits its applications. In this paper, we propose an efficient indoor positioning system that uses a new empirical propagation model, called regional propagation model (RPM), which is based on the cluster based propagation model theory. The system first collects the sparse fingerprints at some certain reference points (RPs) in the whole testing scenario. Then affinity propagation clustering algorithm operates on the sparse fingerprints to automatically divide the whole scenario into several clusters or sub-regions. The parameters of RPM are obtained in the next step and are further used to recover the entire fingerprint database. Finally, the location estimation is obtained through the weighted k-nearest neighbor algorithm (WkNN) in the online localization phase. We also theoretically analyze the localization accuracy of the proposed algorithm. The numerical results demonstrate that the proposed propagation model can predict the received signal strength (RSS) values more accurately than other models. Furthermore, experiments also show that the proposed positioning system achieves higher localization accuracy than other existing systems while cutting workload of fingerprint calibration by more than 50% in the offline phase.
The Global Position System (GPS), which is well known as a global tool for positioning, is also the primary system for time transfer. GPS can deliver very precise time to every corner of the world. Usually, a GPS receiver indicates the precise time by means of the 1PPS (one pulse per second) signal. This paper studies the precise time transfer system structure of GPS receivers and then proposes an effective PPS signal generation method with predictive synchronous loop, combining phase error prediction and dynamic threshold adjustment. A GPS time transfer system is implemented and measured in detail to demonstrate the validity of the proposed algorithm. Assuming the receiver clock rate of 16.368MHz, the proposed method can achieve the accuracy of ±20ns in the scope 1δ which can meet the requirements of the vast majority of occasions. Through a long period of testing, we prove the feasibility of this algorithm experimentally.