A new trade-off scheme for MIMO OFDM-based cognitive radio systems over correlated fading channels

A joint pre- and post-coder (JPROC) is proposed for MIMO OFDM-based cognitive radio systems over correlated fading channels. The main aim is to have a trade-off between licensed networks and un-licensed networks in the underlay scenario. To handle the un-desired interferences on the main networks, the eigen-values of this JPROC should be small in each licensed network, as much as possible, whereas un-licensed users have higher rates. Frequency selective MIMO fading channels are coded with orthogonal space-time-frequency block codes (OSTFBCs) to improve the bad effects of these small eigen-values on the signal to noise ratio (SNR) in the main network. On the other hand, the system is operated in both transmit- and receivecorrelation scenarios. We have the correlation matrices at all the transmitters imperfectly. This is because there is any error in the estimation of the transmit- and the receive- angle spreads. The matrix of the JPROC is obtained by solving a robust convex optimization problem in the multi-user scenario. The optimization problem is represented under some constraints such as the outage probability of eavesdropping as a criterion for secrecy. An upper-band of the pair-wise error probability is minimized, while controlling the produced interferences. The effective performance of this JPROC is finally shown using simulations

Adaptive Power Allocation and Control in Time-Varying Multi-Carrier MIMO Networks

In this paper, we examine the fundamental trade-off between radiated power and achieved throughput in wireless multi-carrier, multiple-input and multiple-output (MIMO) systems that vary with time in an unpredictable fashion (e.g. due to changes in the wireless medium or the users' QoS requirements). Contrary to the static/stationary channel regime, there is no optimal power allocation profile to target (either static or in the mean), so the system's users must adapt to changes in the environment "on the fly", without being able to predict the system's evolution ahead of time. In this dynamic context, we formulate the users' power/throughput trade-off as an online optimization problem and we provide a matrix exponential learning algorithm that leads to no regret - i.e. the proposed transmit policy is asymptotically optimal in hindsight, irrespective of how the system evolves over time. Furthermore, we also examine the robustness of the proposed algorithm under imperfect channel state information (CSI) and we show that it retains its regret minimization properties under very mild conditions on the measurement noise statistics. As a result, users are able to track the evolution of their individually optimum transmit profiles remarkably well, even under rapidly changing network conditions and high uncertainty. Our theoretical analysis is validated by extensive numerical simulations corresponding to a realistic network deployment and providing further insights in the practical implementation aspects of the proposed algorithm.Comment: 25 pages, 4 figure

Spectrum sensing in cognitive radio using multitaper method based on MIMO-OFDM techniques

The current inefficient utilization of frequency spectrum has alerted regulatory bodies to streamline improvements. Cognitive radio (CR) has recently received considerable attention and is widely perceived as a promising improvement tool in estimating, or equivalently sensing, the frequency spectrum for wireless communication systems. The cognitive cycle in CR systems is capable of recognizing and processing better spectrum estimation (SE) and hence promotes the efficiency of spectrum utilization. Among different SE methods, the multi-taper method (MTM) shows encouraging results. Further performance improvement in the SE for CR can be achieved by applying multiple antennas and combining techniques. This paper proposes a constructive development of SE using MTM, abbreviated as MTSE, and by employing multiple-input multiple-output (MIMO), parsed into separate parallel channels using singular value decomposition (SVD), and maximum ratio combining (MRC) configurations. Deviating from these improvements, however, multicarrier systems such as orthogonal frequency division multiplexing (OFDM) show inferior sensing performances due to the noise multiplicity generated and combined from all subcarrier channels. By means of the quadrature matrix form, the probabilities for such integrated settings of SE have been derived to reach at their approximate asymptotes. Numerical simulations revealed specific better performances stemmed from coupling the fashionable MTSE and MIMO technologies

DR9.3 Final report of the JRRM and ASM activities

Deliverable del projecte europeu NEWCOM++This deliverable provides the final report with the summary of the activities carried out in NEWCOM++ WPR9, with a particular focus on those obtained during the last year. They address on the one hand RRM and JRRM strategies in heterogeneous scenarios and, on the other hand, spectrum management and opportunistic spectrum access to achieve an efficient spectrum usage. Main outcomes of the workpackage as well as integration indicators are also summarised.Postprint (published version

Spectral-energy efficiency trade-off for next-generation wireless communication systems

The data traffic in cellular networks has had and will experience a rapid exponential rise. Therefore, it is essential to innovate a new cellular architecture with advanced wireless technologies that can offer more capacity and enhanced spectral efficiency to manage the exponential data traffic growth. Managing such mass data traffic, however, brings up another challenge of increasing energy consumption. This is because it contributes into a growing fraction of the carbon dioxide (CO2) emission which is a global concern today due to its negative impact on the environment. This has resulted in creating a new paradigm shift towards both spectral and energy efficient orientated design for the next-generation wireless access networks. Acquiring both improved energy efficiency and spectral efficiency has, nonetheless, shown to be a difficult goal to achieve as it seems improving one is at the detriment to the other. Therefore, the trade-off between the spectral and energy efficiency is of paramount importance to assess the energy consumption in a wireless communication system required to attain a specific spectral efficiency. This thesis looks into this problem. It studies the spectral-energy efficiency tradeoff for some of the emerging wireless communication technologies which are seen as potential candidates for the fifth generation (5G) mobile cellular system. The focus is on the orthogonal frequency division multiple access (OFDMA), mobile femtocell (MFemtocell), cognitive radio (CR), and the spatial modulation (SM). Firstly, the energy-efficient resource allocation scheme for multi-user OFDMA (MU-OFDMA) system is studied. The spectral-energy efficiency trade-off is analysed under the constraint of maintaining the fairness among users. The energy-efficient optimisation problem has been formulated as integer fractional programming. We then apply an iterative method to simplify the problem to an integer linear programming (ILP) problem. Secondly, the spectral and energy efficiency for a cellular system with MFemtocell deployment is investigated using different resource partitioning schemes. Femtocells are low range, low power base stations (BSs) that improve the coverage inside a home or office building. MFemtocell adopts the femtocell solution to be deployed in public transport and emergency vehicles. Closed-form expressions for the relationships between the spectral and energy efficiency are derived for a single-user (SU) MFemtocell network. We also study the spectral efficiency for MU-MFemtocells with two opportunistic scheduling schemes. Thirdly, the spectral-energy efficiency trade-off for CR networks is analysed at both SU and MU CR systems against varying signal-to-noise ratio (SNR) values. CR is an innovative radio device that aims to utilise the spectrum more efficiently by opportunistically exploiting underutilised licensed spectrum. For the SU system, we study the required energy to achieve a specific spectral efficiency for a CR channel under two different types of power constraints in different fading environments. In this scenario, interference constraint at the primary receiver (PR) is also considered to protect the PR from harmful interference. At the system level, we study the spectral and energy efficiency for a CR network that shares the spectrum with an indoor network. Adopting the extreme-value theory, we are able to derive the average spectral efficiency of the CR network. Finally, we propose two innovative schemes to enhance the capability of (SM). SM is a recently developed technique that is employed for a low complexity multipleinput multiple-output (MIMO) transmission. The first scheme can be applied for SU MIMO (SU-MIMO) to offer more degrees of freedom than SM. Whereas the second scheme introduces a transmission structure by which the SM is adopted into a downlink MU-MIMO system. Unlike SM, both proposed schemes do not involve any restriction into the number of transmit antennas when transmitting signals. The spectral-energy efficiency trade-off for the MU-SM in the massive MIMO system is studied. In this context, we develop an iterative energy-efficient water-filling algorithm to optimises the transmit power and achieve the maximum energy efficiency for a given spectral efficiency. In summary, the research presented in this thesis reveals mathematical tools to analysis the spectral and energy efficiency for wireless communications technologies. It also offers insight to solve optimisation problems that belong to a class of problems with objectives of enhancing the energy efficiency