Introduction to Electromagnetic Compatibility

In general, Micropower Impulse Radar (MIR) depends on Ultra-Wideband (UWB) transmission systems. UWB technology can supply innovative new systems and products that have an obvious value for radar and communications uses. Important applications include bridge-deck inspection systems, ground penetrating radar, mine detection, and precise distance resolution for such things as liquid level measurement. Most of these UWB inspection and measurement methods have some unique qualities, which need to be pursued. Therefore, in considering changes to Part 15 the FCC needs to take into account the unique features of UWB technology. MIR is applicable to two general types of UWB systems: radar systems and communications systems. Currently LLNL and its licensees are focusing on radar or radar type systems. LLNL is evaluating MIR for specialized communication systems. MIR is a relatively low power technology. Therefore, MIR systems seem to have a low potential for causing harmful interference to other users of the spectrum since the transmitted signal is spread over a wide bandwidth, which results in a relatively low spectral power density.

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Response to FCC 98-208 notice of inquiry in the matter of revision of part 15 of the commission's rules regarding ultra-wideband transmission systems

This monograph presents a unified framework for energy efficiency maximization in wireless networks via fractional programming theory. The definition of energy efficiency is introduced, with reference to single-user and multi-user wireless networks, and it is observed how the problem of resource allocation for energy efficiency optimization is naturally cast as a fractional program. An extensive review of the state-of-the-art in energy efficiency optimization by fractional programming is provided, with reference to centralized and distributed resource allocation schemes. A solid background on fractional programming theory is provided. The key-notion of generalized concavity is presented and its strong connection with fractional functions described. A taxonomy of fractional problems is introduced, and for each class of fractional problem, general solution algorithms are described, discussing their complexity and convergence properties. The described theoretical and algorithmic framework is applied to solve energy efficiency maximization problems in practical wireless networks. A general system and signal model is developed which encompasses many relevant special cases, such as one-hop and two-hop heterogeneous networks, multi-cell networks, small-cell networks, device-to-device systems, cognitive radio systems, and hardware-impaired networks, wherein multiple-antennas and multiple subcarriers are possibly employed. Energy-efficient resource allocation algorithms are developed, considering both centralized, cooperative schemes, as well as distributed approaches for self-organizing networks. Finally, some remarks on future lines of research are given, stating some open problems that remain to be studied. It is shown how the described framework is general enough to be extended in these directions, proving useful in tackling future challenges that may arise in the design of energy-efficient future wireless networks.

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Energy Efficiency in Wireless Networks via Fractional Programming Theory

Random Matrix Methods for Wireless Communications: Estimation

We study resource allocation for energy-efficient communication in multi-cell orthogonal frequency division multiple access (OFDMA) downlink networks with cooperative base stations (BSs). We formulate the resource allocation problem for joint BS zero-forcing beamforming (ZFBF) transmission as a non-convex optimization problem which takes into account the circuit power consumption, the limited backhaul capacity, and the minimum required data rate. We transform the considered problem in fractional form into an equivalent optimization problem in subtractive form, which enables the derivation of an efficient iterative resource allocation algorithm. In each iteration, a low-complexity suboptimal semi-orthogonal user selection policy is computed. Besides, by using the concept of perturbation function, we show that in the considered systems under some general conditions, the duality gap with respect to the power optimization variables is zero despite the non-convexity of the primal problem. Thus, dual decomposition can be used in each iteration to derive an efficient closed-form power allocation solution for maximization of the energy efficiency of data transmission (bit/Joule delivered to the users). Simulation results illustrate that the proposed iterative resource allocation algorithm converges in a small number of iterations, and unveil the trade-off between energy efficiency, network capacity, and backhaul capacity: (1) In the low transmit power regime, an algorithm which achieves the maximum spectral efficiency may also achieve the maximum energy efficiency; (2) a high spectral efficiency does not necessarily result in a high energy efficiency; (3) spectral efficiency is always limited by the backhaul capacity; (4) energy efficiency increases with the backhaul capacity only until the maximum energy efficiency is achieved.

Energy-Efficient Resource Allocation in Multi-Cell OFDMA Systems with Limited Backhaul Capacity

Conventional designs of OFDM-based cognitive radio (CR) systems mainly focus on the system throughput. Since nowdays the energy efficiency (EE) of wireless systems becomes more and more important, this paper intends to improve the system throughput for unit-energy consumption in OFDM-based CR systems. The energy-efficient power allocation problem of OFDM-based CR systems is studied under the total power constraint, the interference power constraint and the rate constraint. Since the energy-efficient power allocation problem is non-convex, in order to find the optimal power allocation at each subcarrier, we propose a novel method named water-filling factors aided search (WFAS) to solve the EE optimization problems with multiple constraints. The global e-optimality and the convergence of the proposed method are presented. The numerical results confirm the theoretical conclusions. The comparisons of the energy-efficient power allocation and the spectrum-efficient power allocation in OFDM-based CR systems are given under different constraints via numerical simulations as well.

Energy Efficiency Optimization for OFDM-Based Cognitive Radio Systems: A Water-Filling Factor Aided Search Method

Spectrum sensing is a key problem in cognitive radio (CR). Because of a low SNR, fading and sensing time constraints, a single CR may not be able to reliably sense the presence of primary radios, which motivates the study of sensing by multiple cognitive users. Here, the authors consider cooperative spectrum sensing (CSS) using a counting rule where several cognitive users sense whether primary users exist or not and send their decisions to the centre where the final decision is made. Optimal strategies under both the Neyman-Pearson criterion and the Bayesian criterion for CSS are derived using a counting rule. In addition, the authors present simple methods to calculate the optimal settings. Another contribution here is the analysis of a randomised rule at the centre, which is a long-existing problem in the field of distributed detection systems.

Optimisation of cooperative spectrum sensing in cognitive radio network

In this letter, we simplify the well-known semi-orthogonal user selection (SUS) algorithm for the multi-user multiple-input multiple-output (MU-MIMO) system with zero-forcing beamforming (ZFBF). Compared with the original SUS algorithm, the proposed user selection algorithm achieves the same performance, but with significantly less complexity. Simulation results show that the proposed algorithm can make a good tradeoff between performance and complexity for the MU-MIMO system with ZFBF.

Simplified Semi-Orthogonal User Selection for MU-MIMO Systems with ZFBF

In this paper, we present a new ultra-wideband (UWB) pulse design method for narrowband interference (NBI) suppression. With a short time duration, the obtained UWB pulses not only meet the Federal Communications Commission (FCC) spectral mask, but also dramatically suppress the mutual interference between UWB systems and multiple narrowband communication systems. This method successfully solves the coexistence problem between UWB systems and the existing narrowband systems without the need of reducing UWB pulse power spectral density (PSD) over the whole UWB frequency band. Therefore, the application range of UWB systems can be enlarged by increasing the transmitted UWB pulse power.

A new UWB pulse design method for narrowband interference suppression

Conventional designs of cognitive radio (CR) multiple-input multiple-output (MIMO) systems mainly focus on the system throughput Since nowdays the energy efficiency (EE) of wireless systems has become more and more important, this paper intends to improve the system throughput for unit-energy consumption in CR MIMO broadcast channels (BC) The EE optimization problem of CR MIMO BC is studied under the total power constraint, the interference power constraint and the minimum system throughput constraint Since the EE optimization problem is non-convex, in order to find the optimal solution, we transform it into an equivalent one-dimension problem with a quasi-concave objective function and use the golden section method to solve it Through simulations, we show the efficiency of the proposed algorithm

Jinchun Gao

Papers

Energy Efficiency Optimization for OFDM-Based Cognitive Radio Systems: A Water-Filling Factor Aided Search Method

Optimisation of cooperative spectrum sensing in cognitive radio network

Simplified Semi-Orthogonal User Selection for MU-MIMO Systems with ZFBF

A new UWB pulse design method for narrowband interference suppression

Energy Efficiency Optimization for Cognitive Radio MIMO Broadcast Channels