The rapid adoption of electric or hybrid vehicles (EVs) has called for wide deployment of charging stations. These stations can be launched/owned by different owners, referred to as charging station providers (CSPs), which make energy contracts with a smart grid provider (SGP). However, there exists a shortage of mutual economic strategy between the SGP and CSPs in an energy request/transfer competition due to the selfish nature among them. In this paper, we propose an economic model leveraging a multi-principal single-agent (referred to as common agency) contract policy, aiming at maximizing the utilities of multiple CSPs while optimizing the utility of the SGP in an EV network. In particular, we first develop the common agency-based contract problem as a non-cooperative energy contract optimization problem, in which each CSP can maximize its utility given the common constraints from the SGP and the contracts of other CSPs. To deal with this problem, we develop an iterative energy contract algorithm to find an equilibrium contract solution where the contracts from the CSPs can produce maximum utilities of the CSPs and satisfy the constraints of the SGP. Through numerical results, we show that our proposed model can improve the social welfare of the EV network up to 54% and the utilities of CSPs up to 60% compared with the baseline method in which each CSP obtains the amount of energy that is proportional to its energy request.

Among all wireless jammers, dealing with reactive ones is most challenging. This kind of jammer attacks the channel whenever it detects transmission from legitimate radios. With recent advances in self-interference suppression or in-band full-duplex radios, a reactive jammer can jam and simultaneously sense/discern/detect the legitimate transmission. Such a jammer is referred to as a smart reactive jammer. However, all existing solutions, e.g., frequency hopping and rate adaptation, cannot effectively deal with this type of jammer. This is because a smart reactive jammer with sufficient power budget can theoretically jam most, if not all, frequency channels at sufficiently high power. This work proposes to augment the transmitter with an ambient backscatter tag. Specifically, when the jammer attacks the channel, the transmitter deceives it by continuing to transmit data to attract the jammer while the tag backscatters data based on both the jamming signals and active signals from the jammer and transmitter, respectively. However, backscattering signals from multiple radio sources results in a high bit error rate (BER). Thus, we propose to use multiple antennas at the receiver. The theoretical analysis and simulation results show that by using multiple antennas at the receiver, the BER and hence the throughput of the system can be significantly improved. More importantly, we demonstrate that with our proposed solutions, the average throughput increases and the BER decreases when the jammer attacks with higher power levels. We believe that this is the first anti-jamming solution that can cope effectively with a high- or even unlimited-power jammers.

Spectrum sharing has been gaining its popular adoption as a potential solution to improve spectrum utilization in future wireless systems. Both Federal Communications Commission (FCC) and European Telecommunications Standards Institute (ETSI) support dynamic spectrum access (DSA) as an enabling technology for spectrum sharing. To effectively realize DSA in practice, users (from both defense and commercial sectors) are required to share their (radio) operational information, which risks exposing their security, privacy, and business plan to unintended agents. Protecting users' operating information is hence the key to DSA's success. In this paper, taking the FCC's spectrum access system (SAS) as a study case, we investigate the operational privacy issue of Incumbent Users (IUs) and honest/dishonest Secondary Users (SUs). For the case of IUs and honest SUs, we propose a privacy-preserving scheme for DSA by leveraging encryption and obfuscation methods (PSEO). To implement PSEO, we introduce an interference calculation scheme that allows users to calculate an interference budget without revealing operational information (e.g., antenna height, transmit power, location...), referred to as the blind interference calculation scheme (BICS). BICS also reduces the computing overhead of PSEO, compared with FCC's SAS by moving interference budgeting tasks to local users and calculating it in an offline manner. To further save the overhead in calculating the interference map, we introduce a quantization method and optimize the grid sizes of the terrestrial area of interest. Additionally, for the case of IUs and dishonest SUs, we propose a “punishment and forgiveness” (PF) mechanism, which draws support from SUs' reputation scores (RSs) and reputation histories (RHs), to encourage SUs to provide truthful information. Theoretical analysis and extensive simulations show that our proposed PSEO and PF-PSEO schemes can better protect all users' operational privacy under various privacy attacks, yielding higher spectrum utilization with less online overhead, compared with state of the art approaches.

In this paper, we propose novel approaches using state-of-the-art machine learning techniques, aiming at predicting energy demand for electric vehicle (EV) networks. These methods can learn and find the correlation of complex hidden features to improve the prediction accuracy. First, we propose an energy demand learning (EDL)-based prediction solution in which a charging station provider (CSP) gathers information from all charging stations (CSs) and then performs the EDL algorithm to predict the energy demand for the considered area. However, this approach requires frequent data sharing between the CSs and the CSP, thereby driving communication overhead and privacy issues for the EVs and CSs. To address this problem, we propose a federated energy demand learning (FEDL) approach which allows the CSs sharing their information without revealing real datasets. Specifically, the CSs only need to send their trained models to the CSP for processing. In this case, we can significantly reduce the communication overhead and effectively protect data privacy for the EV users. To further improve the effectiveness of the FEDL, we then introduce a novel clustering- based EDL approach for EV networks by grouping the CSs into clusters before applying the EDL algorithms. Through experimental results, we show that our proposed approaches can improve the accuracy of energy demand prediction up to 24.63% and decrease communication overhead by 83.4% compared with other baseline machine learning algorithms.

Both Federal Communications Commission (FCC) and European Telecommunications Standards Institute (ETSI) support dynamic spectrum access (DSA) as an enabling technology for spectrum sharing. To effectively realize DSA in practice, users (from both defense and civil sectors) are required to share their (radio) operational information. That risks exposing their security, privacy, and business plan to unintended agents. In this paper, taking FCC's spectrum access system (SAS) as a study case, we propose a privacy-preserving scheme for DSA by leveraging encryption and obfuscation methods (PSEO). To implement PSEO, we propose an interference calculation scheme that allows users to calculate interference budget without revealing their operation information (e.g., antenna height, transmit power, location...), referred to as blind interference calculation method (BICM). BICM also reduces the computing overhead of PSEO, compared with FCC's SAS by moving interference budgeting tasks to local users and calculating it in an offline manner. Extensive detailed analysis and simulations show that our proposed PSEO is able to better protect all users' operational privacy, guaranteeing efficient spectrum utilization with less online overhead, compared with state of the art approaches.

In this paper, a novel transmission scheme which is called three-dimensional modulation using beam hopping (3DModBH) and a new receiver algorithm are suggested. The new concepts improve the spectral efficiency and the reliability of the transmit signals of 5G networks by using the spatial domain of multiple small cells. The main distinguishing feature of 3DModBH transmission scheme is that it maps additional information bits by exploiting the spatial domain of multiple small cells or base stations (BSs). More specifically, the suggested 3DModBH uses the conventional two-dimensional (2-D) modulation techniques plus the spatial domain of multiple small cells or BSs to transmit the information bits, whereas the state-of-the-art transmission scheme (SoAT) uses only the conventional 2-D modulation techniques to transmit the data. We demonstrate the advantages of the novel scheme in small cell scenario under strong interference in 5G networks. We propose a new receiver algorithm to detect the transmitted information bits in practical interference limited scenario. The performance of 3DModBH scheme and the suggested receiver are compared with the SoAT in term of average bit error rate, receiver complexity, and average bits per channel use in practical 5G scenario.

Motivated by recent efforts in enabling economic models for spectrum sharing systems, in particular, for the Spectrum Access System in the US, we propose a game theoretic analysis of sublicensing between two types of access methods in such system - PAL and GAA. The aim of this paper is to illustrate how the operators' strategies affect their own payoffs and the overall utility in the Sublicenseing Game in a spectrum sharing system. We consider the problem of spectrum sharing among multiple operators who have to pay for a temporary PAL sublicense with the exclusive right to the PAL band or stay in the GAA band and share the spectrum for free with other GAA users. We first formulate this scenario as a noncooperative game, and then study the existence of a Nash equilibrium. Finally, to reduce the overall utility loss we let the spectrum sharing platform to coordinate individual operators by forming pair coalitions for them. According to our findings, when an operator has a large number of subscribers GAA band is the best response and a high PAL sublicense price holds back operators to access the PAL band. Additionally, making equal coalitions among operators can avoid overall utility loss.

Spectrum Access System (SAS) is a three tier spectrum sharing framework proposed by the FCC. In this framework the aggregate interference of tier-3 General Authorised Access (GAA) users should be below a predetermined threshold anywhere within the tier-2 Priority Access Licensee (PAL) exclusion zone. GAA are expected to use a diverse range of Radio Access Technologies (RATs) with different levels of loading. We propose an optimal transmit power and probability of spectrum utilisation allocation scheme for GAA users that meets the average aggregate interference constraint within the GAA network. Most of the capacity maximisation studies consider the instantaneous aggregated interference from secondary users. In this paper we present an average aggregated interference method to optimise the capacity of GAA users in a single channel. Simulation results suggest that we can significantly increase the capacity of the channel by considering the probability spectrum utilisation of GAA users.

To augment capacity of spectrum limited cellular systems, 3GPP proposed Licensed Assisted Access (LAA-LTE) while efforts are underway to standardize the standalone MulteFire (a small cell standalone version of LTE). LAA is expected to boost capacity of LTE via unlicensed spectrum (5GHz). On the other hand, recent advances in Self Interference Suppression (SIS) techniques allow radios to transmit and receive simultaneously on the same channel (i.e., in-band Full-Duplex, FD). As part of future wireless networks, Device-to-device (D2D) communications would find its great potential through this FD capability. However, due to high induced aggregate interference from FD and its impact on medium access probability, the rigorous and critical analysis is needed to find an optimum trade-off between performance efficiency and overheads. Using stochastic geometry and the random graph theory, in this article, we analyze the impact of different LTE network paradigms with HD/FD D2D devices. Moreover, the impact of state- of-the-art coexistence techniques (discontinuous transmission and listen-before-talk) recommended for LTE in unlicensed spectrum over HD/FD D2D network is also discussed. The analysis is supported with extensive simulation results that reveal insights of the coexistence mechanism efficiency employed by LTE, the impact of SIS and the cost of FD operation in D2D.

Spectrum Access System (SAS) allows incumbent military systems to share spectrum in a hierarchical manner with tier-2 Priority Access License (PAL) users and tier-3 General Authorized Access (GAA) users. FCC has recently allowed PAL owners to sublicense their channels. Therefore, when GAA channels are congested they can request a sublicense to access the PAL channel on a coordinated basis, which provides interference protection from other GAA users. In this paper, we propose a grid map to measure and monitor the secondary spectrum market for the purpose of spectrum trading with QoS guarantee. This work provides the subsequent spectrum trading models with a reasonable and dedicated interference graph for further optimization of spectrum allocation. Compared with traditional longterm spectrum licensing policy, short-term licensing makes the spectrum allocated effectively. We find the optimal resolution of the discrete grid map that maximizes the profit from sublicensing. Simulation results are provided to demonstrate how fine to grid the region and let the PAL owner achieve monetary benefit, in a given number of sensors.

A distributed antenna system (DAS) architecture is a key enabler for Cloud Radio Access Networks (CRAN) where geographically separated base stations are connected to a centralized processing and decision making unit. Many schemes have been proposed to leverage Fractional Frequency Reuse (FFR) and co- ordinated joint transmission between base stations to improve cell-edge performance for static network deployments. In this paper, we investigate dynamic decision making that whether co-ordinated joint transmission should be selected in the downlink of a FFR-aided DAS. We derive the transmitting Signal-to- Noise-Ratio (SNR) threshold for making these decisions and we show that this SNR plays a key role in the FFR- aided DAS analysis and can be used as a guide in the evaluation of DAS performance.

Licensed Shared Access is a European standardisation effort which promotes repository based quasi-static hierarchical spectrum sharing. In this scheme the sharing time base is in the order of months if not years. For widespread use of Licensed Shared Access, shrinking the sharing time base is crucial. In this paper we propose a scheme to reduce the sharing time base to seconds or minutes scale. We present a new technique named lightweight Radio Environment Map based on a Kalman Filter derived from geo-location aware spectrum measurements, which can be run at the shared access licensee end. Our objective is to determine the active area of a static or slowly moving incumbent. We consider a challenging scenario where a large fraction of measurements is missing and the available measurements are highly distorted. Performance of our incumbent active area detection approach is evaluated by simulating a low power incumbent in an urban cellular environment. Simulation results show a substantial improvement of missed detection area in comparison to the counterpart that does not use our lightweight Radio Environment Map.

The explosion of different types of wireless communications is leading to an impending spectrum famine. As a result, spectrum sharing has gained increasing interest from governments, industry and regulators, such as FCC in US and CEPT in Europe. Licensed Shared Access (LSA), developed by CEPT and ETSI, is a concept for an efficient use of current spectrum resources to enable keeping pace with increasing mobile data usage demands. In this paper, we present a truthful auction mechanism for spectrum sharing based on the LSA concept. This proposal is to allocate Incumbents' idle spectrum to Licensee Access Points from different operators for the purpose of commerce. We give insights into spectrum allocation methods based on auction mechanisms to obtain high revenue to attract Incumbents to join in the LSA architecture and operators to offload data from primary spectrum band. The proposed LSA Auction (LSAA) mechanism combines independent set selection by bidding and an elaborately designed group bid called Rank-bid, which further improves the revenue compared to related allocation methods. Our simulation results show that LSAA results in enhanced performance for Incumbent revenue and Licensee satisfaction.

Spectrum cartography is the process of constructing a map showing Radio Frequency signal strength over a finite geographical area. In our previous work we formulated spectrum cartography as a compressive sensing problem and we illustrated how cartography can be used in the context of discovering spectrum holes in space that can be exploited locally in cognitive radio networks. This paper investigates the performance of compressive sensing based approach to cartography in a fading environment where realtime channel estimation is not feasible. To accommodate for lack of channel information we take an iterative approach. We extend the well-known iteratively reweighted ℓ1minimisation approach by exploiting spatial correlation between two points in space. We evaluate the performance in an urban environment where Rayleigh fading is prominent. Our numerical results show a significant improvement in the probability of accurately making a spectrum sensing decision, in comparison to the well-known weighted approach and the traditional compressive sensing based method.

Licence-exempt secondary Long Term Evolution systems have been proposed recently, in attempt to meet the needs of rapidly growing wireless mobile applications. However, where the secondary network is spread over a large geographical area, traditional detect-and-avoid algorithms are less effective in providing interference protection to Primary Users while maximising the secondary throughput. Spectrum cartography is an emerging technique that can be used to discover spectrum holes in space. We propose a downlink power allocation algorithm using Kriging Spatial Interpolation and Compressive Sensing based spectrum cartography in an environment where large scale shadow fading is prominent. We evaluate the performance of our approach by simulating a secondary Urban Microcell network operating in TV White Space. Simulation results show a significant improvement in interference and throughput, in comparison to traditional detect-and-avoid algorithms.

This paper presents a novel downlink resource allocation scheme for OFDMA-based next generation wireless networks subject to inter-cell interference (ICI). The scheme consists of radio resource and power allocations, which are implemented separately. Low-complexity heuristic algorithms are first proposed to achieve the radio resource allocation, where graph-based framework and fine physical resource block (PRB) assignment are performed to mitigate major ICI and hence improve the network performance. Given the solution of radio resource allocation, a novel distributed power allocation is then performed to optimize the performance of cell-edge users under the condition that desirable performance for cell-center users must be maintained. The power optimization is formulated as an iterative barrier-constrained water-filling problem and solved by using the Lagrange method. Simulation results indicate that our proposed scheme can achieve significantly balanced performance improvement between cell-edge and cell-center users in multi-cell networks compared with other schemes, and therefore realize the goal of future wireless networks in terms of providing high performance to anyone from anywhere.

In this paper we propose a novel resource allocation scheme to achieve a balanced performance improvement for all users in a LTE network subject to inter-cell interference. In the proposed scheme the resource allocation process is implemented in two steps. In the first step interference coordination and scheduling are first conducted in a global manner to prevent cell-edge users from mutual interference. In the second step, optimal power allocation is conducted to maximize performance of cell-edge users while maintaining high performance of cell-center users. The optimal power allocation problem is solved using the Lagrange decomposition method. Simulation results show that our proposed scheme can significantly improve performance for all users in a multi-cell network and achieve a better performance balance between cell-edge and cell-center users.

The decode-and-forward relay technique has been introduced in next generation wireless networks (such as LTE) to extend coverage and improve performance, although it may generate additional inter-cell interference. Soft frequency reuse (SFR) has been proposed as the most promising frequency planning strategy to mitigate inter-cell interference in LTE systems. In this paper we propose an effective combination of relay networks and SFR, with a dedicated relay topology and the SFR-based resource allocation scheme. In the proposed relay network, each relay station (RS) can jointly serve cell-edge users from adjacent cells to increase efficiency. The proposed resource allocation scheme, on the other hand, is able to achieve throughput improvement for both cell-edge users and cell-center users by minimizing the interference impact in the system. The benefit of relay networks with SFR-based resource allocation in terms of 30% overall performance improvement over conventional non-relay networks can be realized as demonstrated by the simulation results.

Among the techniques proposed to reduce interference in cellular ODFMA networks, base station cooperation (BSC) is currently the technique known to achieve the highest network throughputs. Its deployment however is vastly expensive and cheaper alternatives are expected to play an important role in future wireless access standards. This contribution introduces relay-augmented networks based on the novel paradigm of (m,n)-relaying and shows how, by reaching performances close to those achievable by employing BSC, these qualify as an especially interesting option among the aforementioned alternatives.

This paper proposes a novel load distribution aware soft frequency reuse (LDA-SFR) scheme for inter-cell interference mitigation and performance optimization in next generation wireless networks. Our proposed scheme aims to provide a solution to effectively achieve inter-cell interference mitigation while maintaining high spectrum efficiency to all users in the cell. The proposed scheme consists of two novel algorithms: edge bandwidth reuse and centre bandwidth compensation. Using the edge bandwidth reuse algorithm, cell-edge users can take advantage of uneven traffic load and user distributions within each cell to expand their resource allocations. The center bandwidth compensation algorithm, on the other hand, provides a protection mechanism for cell-center users to avoid exhaustive edge bandwidth extension. Applying LDA-SFR to an LTE network and comparing its performance against that of existing soft frequency reuse (SFR) and adaptive soft frequency reuse (ASFR) schemes indicates that LDA-SFR is superior as it achieves fairness between cell-edge users and cell-center users in terms of average throughput improvement.

In next generation systems and networks, the incorporation of mechanisms achieving robust, predictable and self-adaptive behavior with minimum cost will be a key requirement. Towards this goal we introduce the notion of the "self-growing network". The latter, in its initial deployment stage, is limited to a single dedicated purpose (energy-efficient networking, spectrum efficient communications, control and surveillance use, etc) but can evolve/grow into a multi-purpose, versatile infrastructure, that serves a broader range of applications by utilising combinations of self-x and cooperating features.

This paper details the current work status of the ETSI Reconfigurable Radio Systems (RRS) Technical Committee (TC) and gives an outlook on the future evolution. In particular, Software Defined Radio (SDR) related study results are presented with a focus on SDR architectures for Mobile Devices (MD), such as mobile phones, etc., as well as for Reconfigurable Base Stations (RBS). For MDs, a novel architecture is presented enabling the usage of SDR principles in a mass market context. Cognitive Radio (CR) principles within ETSI RRS are concentrated on two topics, a Cognitive Pilot Channel (CPC) proposal and a Functional Architecture (FA) for Management and Control of Reconfigurable Radio Systems, including Dynamic Self-Organising Planning and Management, Dynamic Spectrum Management, Joint Radio Resource Management, etc. Finally, study results are indicated which are targeting a SDR/CR security framework

The course of events in the wireless communications area has driven the research towards the beyond third generation (B3G) systems. The B3G concept leans on the coexistence and co-operation of multiple, dissimilar radio access technologies (RATs). The reconfigurability concept has been developed to accommodate and exploit the advantages offered by B3G systems. Reconfigurability supports the B3G concept by providing equipment (terminals and network elements) with capabilities to dynamically select and adapt to the most appropriate RAT. In order for this to be realised, an enhanced equipment management and control functionality should be introduced. Such architecture is presented on this paper that focuses on the prototyping environment and the functional entities of the equipment reconfiguration management and control architecture. Also, the correlation between the concept of autonomic computing and this architecture is presented.

This contribution presents key functionalities and design approaches of a distributed system architecture as it is studied in the framework of the European E2R II project. An emphasis is laid on policy based self-governance, distributed reconfiguration concepts and corresponding cognitive support functionalities; this support is necessary to assure context awareness in the equipment in order to facilitate (enable) distributed decision making. The idea is to distribute decision making functionalities among network and user equipment elements in order to (i) limit the required calculation complexity on the network and user side for the determination of the optimum resource selection strategy, (ii) increase the reactivity of the equipment to any context change minimizing the required amount of human interaction and (iii) minimize the signaling overhead by broadcasting generic policy rules applicable to all users instead of targeting a user-by-user based reconfiguration approach. A simple use case illustrates how Game Theoretic tools can be used in order to derive suitable policies and how to perform decisions.

This contribution proposes an iterative channel impulse response (CIR) estimation scheme in the context of the pseudo-random-postfix OFDM (PRP-OFDM) modulation. While conventional techniques reduce noise and interference of OFDM data symbols on the CUR estimates by simple mean value calculation, the new proposal uses soft decoder outputs in order to perform iterative OFDM data symbol interference cancellation. In a typical example for 64QAM constellations, the mean-square-error (MSE) of the CIR estimates is improved by approx. 12 dB after three iterations. Based on PRP-OFDM postfixes only, it is thus possible to perform channel estimation for higher order constellations (64QAM and higher) with an initial CIR estimation over a small observation window (for 64QAM typically 30 to 40 OFDM symbols). Any loss in throughput due to additional redundancy for CIR estimation purposes, e.g. pilot tones, learning symbols, etc. is avoided at the cost of an increase in decoding complexity.

This contribution extends the recently proposed pseudo-random-postfix OFDM (PRP-OFDM) transceiver to the multiple transmit multiple receive (MTMR) antennae context. In this paper a new generic MTMR modulator is proposed that grants a low complexity semi-blind identification of all channels between any transmit and receive antenna based on order-one statistics. A new channel tracking strategy is detailed based on a moving average (MA) Doppler modeling that preserves the Jakes channel coefficients correlation properties. Moreover two transceiver architectures are presented with an Alamouti based apace-time (ST) block code: equalization schemes with or without postfix interference cancellation and related modulators. Performance is illustrated by simulations in the context of the 5.2 GHz OFDM WLAN IEEE 802.11a standard.

The paper details a new OFDM modulator based on the use of a pseudo random postfix (PRP-OFDM) and low complexity equalization architectures. The main advantage of this new modulation scheme is the ability to estimate and track channel variations blindly using order one statistics of the received signal. This scheme is thus very well suited in the presence of large Doppler spreads where channel tracking becomes essential. Moreover, the proposal of various equalization structures, derived from the zero padded transmission schemes, allows implementations ranging from low-complexity/medium performance to increased-complexity/high performance.