Cooperative Precoding with Limited Feedback for MIMO Interference Channels

Multi-antenna precoding effectively mitigates the interference in wireless networks. However, the resultant performance gains can be significantly compromised in practice if the precoder design fails to account for the inaccuracy in the channel state information (CSI) feedback. This paper addresses this issue by considering finite-rate CSI feedback from receivers to their interfering transmitters in the two-user multiple-input-multiple-output (MIMO) interference channel, called cooperative feedback, and proposing a systematic method for designing transceivers comprising linear precoders and equalizers. Specifically, each precoder/equalizer is decomposed into inner and outer components for nulling the cross-link interference and achieving array gain, respectively. The inner precoders/equalizers are further optimized to suppress the residual interference resulting from finite-rate cooperative feedback. Further- more, the residual interference is regulated by additional scalar cooperative feedback signals that are designed to control transmission power using different criteria including fixed interference margin and maximum sum throughput. Finally, the required number of cooperative precoder feedback bits is derived for limiting the throughput loss due to precoder quantization.Comment: 23 pages; 5 figures; this work was presented in part at Asilomar 2011 and will appear in IEEE Trans. on Wireless Com

An Opportunistic Error Correction Layer for OFDM Systems

In this paper, we propose a novel cross layer scheme to lower power\ud consumption of ADCs in OFDM systems, which is based on resolution\ud adaptive ADCs and Fountain codes. The key part in the new proposed\ud system is that the dynamic range of ADCs can be reduced by\ud discarding the packets which are transmitted over 'bad' sub\ud carriers. Correspondingly, the power consumption in ADCs can be\ud reduced. Also, the new system does not process all the packets but\ud only processes surviving packets. This new error correction layer\ud does not require perfect channel knowledge, so it can be used in a\ud realistic system where the channel is estimated. With this new\ud approach, more than 70% of the energy consumption in the ADC can be\ud saved compared with the conventional IEEE 802.11a WLAN system under\ud the same channel conditions and throughput. The ADC in a receiver\ud can consume up to 50% of the total baseband energy. Moreover, to\ud reduce the overhead of Fountain codes, we apply message passing and\ud Gaussian elimination in the decoder. In this way, the overhead is\ud 3% for a small block size (i.e. 500 packets). Using both methods\ud results in an efficient system with low delay

Software-Defined Radio Demonstrators: An Example and Future Trends

Software-defined radio requires the combination of software-based signal processing and the enabling hardware components. In this paper, we present an overview of the criteria for such platforms and the current state of development and future trends in this area. This paper will also provide details of a high-performance flexible radio platform called the maynooth adaptable radio system (MARS) that was developed to explore the use of software-defined radio concepts in the provision of infrastructure elements in a telecommunications application, such as mobile phone basestations or multimedia broadcasters

Performance analysis of SNRbased scheduling policies in asymmetric broadcast ergodic fading channels

We analyze the performance of SNR-based scheduling algorithms in broadcast ergodic fading channels where multiuser selection diversity is exploited. At each channel state, the user with the highest weighted signal-to-noise ratio is selected to be transmitted. The use of weights associated to the users allows us to control the degree of fairness among users and to arrange them according to a prescribed quality of service. These weights parametrize the scheduling algorithms so each set of weights corresponds to a specific scheduling algorithm. Assuming Rayleigh fading broadcast channel, we derive a closed-form expression for the achievable user's rates as a function of the scheduling algorithm, the channel fading statistics of each user, and the transmit power. With the help of this expression, we solve some interesting inverse problems. For example, for a given arbitrary channel statistics we obtain the optimum scheduling algorithm to achieve a prescribed set of users' rates with minimum transmit power

Time-delay estimation in cognitive radio and MIMO systems

Ankara : The Department of Electrical and Electronics Engineering and the Institute of Engineering and Sciences of Bilkent University, 2010.Thesis (Master's) -- Bilkent University, 2010.Includes bibliographical references leaves 87-95.In this thesis, the time-delay estimation problem is studied for cognitive radio systems, multiple-input single-output (MISO) systems, and cognitive single-input multiple-output (SIMO) systems. A two-step approach is proposed for cognitive radio and cognitive SIMO systems in order to perform time-delay estimation with significantly lower computational complexity than the optimal maximum likelihood (ML) estimator. In the first step of this two-step approach, an ML estimator is used for each receiver branch in order to estimate the unknown parameters of the signal received via that branch. Then, in the second step, the estimates from the first step are combined in various ways in order to obtain the final time-delay estimate. The combining techniques that are used in the second step are called optimal combining, signal-to-noise ratio (SNR) combining, selection combining, and equal combining. It is shown that the performance of the optimal combining technique gets very close to the Cramer-Rao lower bound (CRLB) at high SNRs. These combining techniques provide various mechanisms for diversity combining for time-delay estimation and extend the concept of diversity in communications systems to the time-delay estimation problem in cognitive radio and cognitive SIMO systems. Simulation results are presented to evaluate the performance of the proposed estimators and to verify the theoretical analysis. For the solution of the time-delay estimation problem in MISO systems, ML estimation based on a genetic global optimization algorithm, namely, differential evolution (DE), is proposed. This approach is proposed in order to decrease the computational complexity of the ML estimator, which results in a complex optimization problem in general. A theoretical analysis is carried out by deriving the CRLB. Simulation studies for Rayleigh and Rician fading scenarios are performed to investigate the performance of the proposed algorithm.Koçak, FatihM.S

Programming techniques for efficient and interoperable software defined radios

Recently, Software-Dened Radios (SDRs) has became a hot research topic in wireless communications eld. This is jointly due to the increasing request of reconfigurable and interoperable multi-standard radio systems able to learn from their surrounding environment and efficiently exploit the available frequency spectrum resources, so realizing the cognitive radio paradigm, and to the availability of reprogrammable hardware architectures providing the computing power necessary to meet the tight real-time constraints typical of the state-of-art wideband communications standards. Most SDR implementations are based on mixed architectures in which Field Programmable Gate Arrays (FPGA), Digital Signal Processors (DSP) and General Purpose Processors (GPP) coexist. GPP-based solutions, even if providing the highest level of flexibility, are typically avoided because of their computational inefficiency and power consumption. Starting from these assumptions, this thesis tries to jointly face two of the main important issues in GPP-based SDR systems: the computational efficiency and the interoperability capacity. In the first part, this thesis presents the potential of a novel programming technique, named Memory Acceleration (MA), in which the memory resources typical of GPP-based systems are used to assist central processor in executing real-time signal processing operations. This technique, belonging to the classical computer-science optimization techniques known as Space-Time trade-offs, defines novel algorithmic methods to assist developers in designing their software-defined signal processing algorithms. In order to show its applicability some "real-world" case studies are presented together with the acceleration factor obtained. In the second part of the thesis, the interoperability issue in SDR systems is also considered. Existing software architectures, like the Software Communications Architecture (SCA), abstract the hardware/software components of a radio communications chain using a middleware like CORBA for providing full portability and interoperability to the implemented chain, called waveform in the SCA parlance. This feature is paid in terms of computational overhead introduced by the software communications middleware and this is one of the reasons why GPP-based architecture are generally discarded also for the implementation of narrow-band SCA-compliant communications standards. In this thesis we briefly analyse SCA architecture and an open-source SCA-compliant framework, ie. OSSIE, and provide guidelines to enable component-based multithreading programming and CPU affinity in that framework. We also detail the implementation of a real-time SCA-compliant waveform developed inside this modified framework, i.e. the VHF analogue aeronautical communications transceiver. Finally, we provide the proof of how it is possible to implement an efficient and interoperable real-time wideband SCA-compliant waveform, i.e. the AeroMACS waveform, on a GPP-based architecture by merging the acceleration factor provided by MA technique and the interoperability feature ensured by SCA architecture

Advanced signal processing for cognitive radio networks

10.1155/2010/715987Eurasip Journal on Advances in Signal Processing201071598