Infotech Oulu Annual Report 2014 - Communications Signal Processing (CSP)

Professors Markku Juntti, Jari Iinatti and Aarno Pärssinen
Department of Communications Engineering and the Centre for Wireless Communications, University of Oulu
markku.juntti(at)ee.oulu.fi, jari.iinatti(at)ee.oulu.fi, aarno.parssinen(at)ee.oulu.fi
http://www.infotech.oulu.fi/csp

 

Background and Mission

The mission of the Communications Signal Processing (CSP) Research Group (RG) operating within Centre for Wireless Communications (CWC) and Department of Communications Engineering (DCE) of Faculty of Information Technology and Electrical Engineering is to conduct world-class research, train world-class graduates, create new technology and IPRs, and support society by transferring technology to practical usage. CSP focuses on signal processing algorithm, architecture and device implementation technologies combined with appropriate electromagnetism based radio engineering and channel modelling tools. These are key enablers for the forth-coming system realizations.

The scope of the RG activity covers signal processing for wireless and communications systems as well as related radio and medical engineering. The core applications for which the technology is developed include wireless access systems and related devices, wireless sensor networks, and medical diagnostic and treatment systems and devices. The main application areas and practical systems for which the developed technology and scientific knowledge are targeted include primarily wireless access systems and related devices, including 3GPP Long Term Evolution (LTE) – Advanced and the so-called 5G systems beyond it, internet of things (IoT), and IEEE802.11 WLAN evolution, and various industrial and other sensor and actuator systems, networks and related devices, IEEE802.15 standard family evolution with special emphasis on health care and medical WBANs.

 

Scientific Progress

The research in the CSP RG is realized under five main research areas: wireless algorithms and architectures, crosslayer statistical inference, radio engineering, wireless medical communications and nanoscale communications and networks.

Wireless Algorithms and Architectures

Radio Resource Allocation Algorithms

Revived interest in physical layer security has led to a cascade of information theoretic results for various system topologies under different constraints. We have provided practically oriented solutions to the problem of maximizing achievable secrecy rates in an environment consisting of multiple legitimate and eavesdropping radio nodes. By assuming ‘genie’ aided perfect channel state information (CSI) feedback for both types of nodes, we first study two scenarios of interest. When independent messages are intended for all legitimate users (called ‘broadcast’ mode), provably convergent second order cone programming (SOCP) based iterative procedure is used for designing secrecy rate maximizing beamformers. In the same manner, when a common message is intended only for legitimate nodes (dubbed ‘multicast’ mode), SOCP based design is proposed for obtaining linear precoders that maximize the achievable secrecy rate. Subsequently, we leverage the analysis to the more real world scenario, where the CSI of the malicious nodes has to be somehow estimated and that of the legitimate users is corrupted with unavoidable errors. For this case, we devise provably convergent iterative semidefinite programming (SDP) procedures that maximize the achievable secrecy rates for both the beamforming based broadcast and the linearly precoded multicast modes. Finally, numerical results are reported that evaluate the performance of the proposed solutions as a function of different system parameters. We further maximized the achievable secrecy rate while performing antenna selection (AS) when we do not have perfect availability of instantaneous channel covariance matrices of the legitimate (L) and eavesdropper/wiretapper (E) nodes. Instead, we have at our disposal corrupted estimates of the channel covariance matrices. The error component of the estimated matrices is assumed to be weighted by a norm bounded error vector. For a class of norms, irrespective of the distribution of the error vector, we devise a so called convex inner approximation (CIA) semidefinite programming (SDP) based solution that yields a transmit precoder with the desired sparsity as dictated by the number of antennas to be selected. An example of achievable secrecy rate is shown in Figure 1.

Figure 1. Average secrecy rate vs. the TX power [25].

 

We have considered a multi-cell multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) system with multiple-users (MU) contending for the space-frequency resources in the downlink direction. The problem is to determine the transmit precoders by the base stations (BSs) in a coordinated manner to minimize the total number of backlogged packets in the BSs, which are destined for the users in the system. Since the problem is similar to the precoder design for a MIMO interference broadcast channel (IBC) system, traditionally it is solved by the weighted sum rate maximization (WSRM) objective with the number of backlogged packets as the corresponding weights, i.e, longer the queue size, higher the priority. In contrast, we address the queue minimizing downlink precoder design as a joint nonconvex optimization problem over space-frequency resources. We employ successive convex approximation (SCA) technique to solve the problem by a sequence of convex subproblems using inner approximations. Initially, we discuss the centralized joint space-frequency resource allocation (JSFRA) solutions based on SCA as well as by mean squared error (MSE) reformulation. Then we extend the distributed precoder design for the centralized schemes using primal and alternating directions method of multipliers (ADMM) method. We have verified the usability of proposed algorithms for future systems using state-of-the-art system-on-chip (SoC) platforms, e.g., Xilinx Zynq and Texas Instruments’ Keystone II illustrated in Figure 2.

Figure 2. Scheduler implementation architecture.

 

Transceiver Architectures

Requirements for higher data rates and lower power consumption set new challenges for hardware implementation of multiple-input multiple-output orthogonal frequency division multiplexing receivers. Simple detectors have the advantage of low complexity and power consumption, but they cannot offer as good performance as more complex detectors. Therefore, it would be beneficial to be able to adapt the detector algorithm to suit the channel conditions to minimize the receiver processing power consumption while satisfying the quality of service requirements. At low signal-to-noise ratio and/or low rank channel, more power and computation resources could be used for detection in order to guarantee reliable communication, while in good conditions, a simple and less power consuming detector could be used. Therefore, we compare the performance of different detection algorithms. The performance results are based on simulations in a long term evolution system where precoding and hybrid automatic repeat request are used. The effect of channel estimation on the performance is shown. Theoretical complexities of the detectors as numbers of arithmetic operations are presented. For evaluation purposes, we have designed pure hardware integrated circuit implementations with high level synthesis tools (HLS) using a 28 nm CMOS technology but also programmable domain-specific instruction-set processors (DSIPs) are designed.

Lattice reduction (LR) is a preprocessing technique for multiple-input multiple-output (MIMO) symbol detection to achieve better bit error-rate (BER) performance. We propose a modified LR algorithm, Lenstra-Lenstra-Lovasz (LLL) to meet high throughput. To reach energy efficiency requirements, we have proposed a customized domain-specific instruction-set (DSIP) multiprocessor for LR. The processor cores are based on transport triggered architecture (TTA) and consisting an instruction-set which can be programmed for other algorithms in the detection algorithm domain too, see Figure 3. The TTA cores are programmed with high level language. Each TTA core consists of several special function units to accelerate the program code. The multiprocessor takes 187 cycles to reduce a single matrix for LR. The architecture is synthesized on 90 nm technology and takes 405 k gates at 210 MHz.

Figure 3. Mutliprocessor lattice reduction architecture.

 

We have addressed the effect of transmitter nonidealities on the self-interference (SI) cancellation in full-duplex transceivers. The non-idealities considered include the nonlinearity of the power amplifier (PA), imbalance between in-phase and quadrature branches of the transmitter (IQ imbalance), phase noise and the time misalignment of SI and feed forwarded signal. Further, the effect of multi-path propagation of the SI signal is studied. Simulation results show that even simple techniques to compensate the non-linear operation of the PA and the multi-path propagation of the SI increase the SI cancellation performance.

Crosslayer Statistical Inference

We have considered sequential compressed acquisition and progressive reconstruction of spatially and temporally correlated sensor data streams in wireless sensor networks (WSNs) via compressed sensing (CS) as illustrated in Figure 4. We developed a sequential framework based on sliding window processing, in which the sink can efficiently reconstruct the current sensors’ readings from a sequence of periodically delivered CS measurements by exploiting the joint compressibility via Kronecker sparsifying bases. Specifically, we derived a recursive CS recovery method which utilizes the estimates from the preceding decoding instants via a regularization and reweighted ℓ1-minimization to improve the reconstruction accuracy of sensor data streams while reducing the necessary communications. As beneficial features, the method produces estimates for the current sensors’ readings without additional decoding delay, and, via adjusting the window size, it can dynamically trade-off between the CS recovery performance and decoding complexity. Numerical results show that our proposed method achieves higher reconstruction accuracy with a smaller number of required transmissions, and with lower decoding delay and complexity as compared to those of the state of the art CS methods. An example is illustrated in Figure 5.

Figure 4. Wireless sensor network system model [33].

 

Figure 5. Recovery error vs. communications cost [33].

 

We have provided analytical assessment that justify the performance tendencies of practical coding/decoding techniques for a binary data gathering wireless sensor network. We model the binary data gathering WSN by a binary chief executive officer (CEO) problem. The theoretical rate region is analyzed based on the Berger-Tung inner bound. We also derived the bit error probability (BEP) floor and its lower bound given the observation error probability by using the Poisson-binomial distribution approximation of the observation error occurrence and Shannon's rate-distortion function. The simulation results show that the bit error rate (BER) performance of our proposed technique is close to theoretical limits supported by the Berger-Tung inner bound. The extrinsic information transfer (EXIT) chart analysis is also used to verify the BER performance. Moreover, the simulation results show that the error floor is placed between the Poisson-binomial approximation and the rate-distortion lower bound.

Radio Engineering

Radio engineering is shaping it’s scope at the moment. In addition to already strong antenna and propagation research RF transceivers and their implementation aspects will be strengthened in the research portfolio. For that professor nomination process is on-going and project planning started.

Antennas and propagation

Antenna and propagation research has progressed under various topics. Antenna over-the-air measurements as well as 5G channel propagation measurements have been performed using developed measurement systems. Antenna structures have been developed both for wearable wireless medical and for infrastructure applications.

The advantages of a MIMO system have been under extensive research, and results show they are heavily dependent on the directional properties of the radio channel. To enable comparison between various MIMO terminals, they should be measured using comparable methods in realistic radio channel conditions. Signal throughput has been agreed in the CTIA forum to be the most significant figure of merit for testing LTE devices, because all the LTE services are digital and therefore the final performance of the LTE terminal can be quantified by its ability to transmit and receive digital data.

MIMOTA-2 research project started in June 2014 as a goal to study and compare different over-the-air (OTA) methods for MIMO terminal testing. Both experimental and simulation studies are used to evaluate the accuracy of the MIMO OTA test method. A goal of the simulations is to find cost effective and sufficiently accurate measurement configurations for different communication cases in different radio channel environments. The results are significant e.g. for CTIA standardization work for the MIMO terminal test methods.

A MIMO OTA measurement setup was built in the radio anechoic chamber and a measurement campaign was performed in autumn 2014. In the measurements, repeatable realistic MIMO radio channel conditions for urban environments are generated for mobile MIMO terminal throughput tests. The main goals of the campaign were to research minimum required radius of the measurement setup and to study human hand effects for MIMO terminals.

Figure 6. MIMO-OTA measurement system.

 

Antenna research in the field of wireless medical applications is focused on UWB on-body antennas. Instead of directly comparing the performance of the different types of antennas, the interaction between an antenna and a body is more interesting as well as radio wave propagation mechanism on a body. High-loss operation environment and the requirements for efficient antennas have led to the basic research in the electromagnetic field behavior close to the human body. The achieved theoretical results explain the antenna – human body interaction in wide frequency range and novel antenna structures based on this knowledge are developed. Further, theoretical findings are applied in 2.45 GHz frequency band and especially on the electromagnetic wave propagation around the human body, where significant improvements on received electric field strength are achieved. In addition, a new design method using artificial anisotropic material for controlling polarization properties has been developed. One application of this method is to decrease losses between planar antennas on a human body.

In a research oriented customer project a passive wideband antenna element was designed for active antenna system at 1.7-2.7 GHz bandwidth fulfilling targets of the research partner. The antenna structure was based on the dual-element dual-polarized sub-arrays.

Figure 7. Example of antenna radiating pattern [55].

 

A MIMO radio channel measurement system was developed during 2014. Instead of MIMO antenna arrays, virtual arrays were utilized in both the TX and RX ends. In a virtual array, a dual-polarized antenna is mechanically moved and rotated in freely selected grid. Typically antenna array is formed on a planar surface, but also conformal antennas, such as cylindrical or spherical, are easily achieved. Newly purchased PNA-X series four-port S-parameter analyzer serves as the TX/RX control, measurement and computing engine of the system.  For 5G systems, radio channels have been measured and modelled in several campaigns at 10GHz range and initial results are reported for relevant 5G research activities. Channel modelling will continue during 2015.

Figure 8. Propagation measurement system.

 

RF Transceivers

Activity has been ramped up with very small volume in October 2014. RF system design to support 5G concept studies has been started. First focus will be in RF feasibility and requirement analysis for selected frequency band(s). Initial link budget calculations have been done for 5G system design. Based on these RF architecture for massive-MIMO and beamforming has been drafted.

Wireless Medical Communications

Wireless Medical Communications (WiMeC) team is investigating the concept and the problematic resulting from this requirement focusing on short range communication (up to tens of meters), wideband communication (in all the forms), channel modelling (crucial for system development), knowledge on antennas, and physical layer and medium access control (MAC). The wireless body area network (WBAN) is a key element of the research approach. In 2014, the central research topics included channel models for WBAN, performance evaluation of ultra wideband receivers, low-power MAC protocols for WBANs, on-body antennas, as well as environmental challenges in medical WBANs. The team had also a major role in contributing to the ETSI SmartBAN standardization work. The results were presented in 1 Doctoral Thesis, one book, 5 international journal papers, and 13 international conference papers. International relations were further developed in through the advisory Board membership of the Research Centre in the area of wireless medical technologies and applications in Macquarie University (Australia). Furthermore, Horizon2020 project proposal was prepared with new partners. WiMeC also contributed to the scientific community by organising UWBAN 2014 (in conjunction with Bodynets 2014) in London, serving as ISMICT2014 general co-chair and board members (International Steering Committee and Technical Program Committee), and co-chairing the IEEE PIMRC 2014 Technical Programme Committee. In 2015, the WiMeC team is focusing its research essentially on solutions of dual use in homes and institutions; receiver performance evaluation and new MAC protocols; dependable WSN networks (robustness, security and secrecy); close to body signal propagation; interference modelling; nanoscale communications; mobile clouds for medical ICT; and visible light communication for medical ICT.

Figure 9. Body area network measurement.

 

Nanoscale Communications and Networks

We have considered nanoscale wireless communication in both the Terahertz and VHF bands. For the Terahertz band, we have developed accurate analytical channel models taking into account multiple scattering. Both frequency and time domain channels have been derived. In time domain, we can notice the tail in response due to multiple scattering and also due to the frequency selective molecular absorption. For the VHF band, we have performed accurate analysis of the bit-error-rates possible with nanoscale carbon nanotube based mechanically oscillating receivers. For high accuracy, linear response has been considered in addition to the square-law response previously considered. More accurate noise correlation models have been used than in previous works, leading to significantly more accurate results. 

Figure 10. Nanoscale communication model in the VHF band.

 

Exploitation of Results

The CSP RG has proposed novel scientific information and results which are of interest to the global scientific community in general and our project partners in particular. Much of the work is done on simulator level but the ability to verify the usability of proposed algorithms with hardware implementations adds significant value to the results and helps the research community and the project partners to evaluate and further develop the ideas. Several invention reports and patent applications have been generated based on the research results. The cooperating companies also use the research results in wireless system standardization.

 

Future Goals

The major focus in the current research is to develop the basic enabling technologies and building blocks for the evolving IoT. The next major targets include optimized interplay of baseband and RF processing, which becomes increasingly critical with increasing carrier frequencies when cm and mm wave frequencies are introduced to practical use in the 5G system development.

 

Personnel

professors

4

senior research fellows

4

postdoctoral researchers

10

doctoral students

25

other research staff

3

total

46

person years for research

36

 

External Funding

Source

EUR

Academy of Finland

664 000

Tekes

779 000

domestic private

188 000

international

350 000

total

 1 981 000

 

Doctoral Theses

Tuovinen, T (2014) Operation of IR-UWB WBAN antennas close to human tissues. Acta Universitatis Ouluensis, Technica C 505.

Höyhtyä, M (2014) Adaptive power and frequency allocation strategies in cognitive radio systems. VTT Science 61.

 

Selected Publications

[1] J. Lehtomäki, A. O. Bicen & I. F. Akyildiz, “On the nanoscale electromechanical wireless communication in the VHF band”. IEEE Transactions on Communications, to appear 2015

[2] Z. Khan, J. Lehtomäki, L. A. DaSilva, E. Hossain &  M. Latva-aho, "Opportunistic Channel Selection by Cognitive Wireless Nodes Under Imperfect Observations and Limited Memory: A Repeated Game Model".  IEEE Transactions on Mobile Computing, under minor revision, January 2015

[3] Hämäläinen M., Iinatti J. (2014), Wireless UWB Body Area Networks - Using the IEEE802.15.4-2011. Mucchi L. (Editor), Academic Press Library in Biomedical Applications of Mobile and Wireless communications. 48 p. ISBN: 978-0-128-00931-4.

[4] H. Karvonen, C. Pomalaza-Raez, M. Hämäläinen, ”A Cross-Layer Optimization Approach for Lower Layers of the Protocol Stack in Sensor Networks“, ACM Transactions on Sensor Networks, Volume 11 Issue 1, Article No. 16,  August 2014. DOI: http://dx.doi.org/10.1145/2590810.

 [5] T. Tuovinen, M. Berg, “Impedance Dependency on Planar Broadband Dipole Dimensions: An Examination with Antenna Equivalent Circuits”, Progress in Electromagnetics Research. 144: 249-260.

[6] H. Karvonen, J. Iinatti, M. Hämäläinen,”A Cross-Layer Energy-Efficiency Optimization Model for WBAN Using IR-UWB Transceivers“, Springer Telecommunications Systems - Modelling, Analysis, Design and Management, Special Issue on Research Advances in Energy-Efficient MAC Protocols for WBANs, November 2014, pp. 1–13.

[7] T. Tuovinen, M. Berg, E. Salonen, “Antenna Close to Tissue: Avoiding Radiation Pattern Minima with Anisotropic Substrate”, IEEE Antennas and Wireless Propagation Letters. (In press)

[8] T. Tuovinen, M. Berg, E. Salonen, “The Effect of Antenna Pattern and Polarization for Launching Creeping Waves on a Skin Surface”. The 8th European Conference on Antennas and Propagation (EUCAP 2014), 6.-11.4.2014, The Hague, The Netherlands.

[9] M. Särestöniemi, V. Niemelä, M. Hämäläinen, J. Iinatti, N. Keränen, J. Partala, T. Jämsä, T. Seppänen, J. Reponen, ”Performance Evaluation of IEEE 802.15.6 Based WBAN System for Monitoring Parkinson’s Disease”, The 8th International Symposium on Medical Information & Communication Technology (ISMICT2014), 2.-4.4.2014, Florence, Italy.

[10] Tuovinen T., Berg M., Salonen E., Hämäläinen M., and Iinatti J., “Conductive Layer under a Wearable UWB Antenna: Trade-off between Absorption and Mismatch Losses,” The 8th International Symposium on Medical Information & Communication Technology (ISMICT2014), 2.-4.4.2014, Florence, Italy.

[11] Niemelä V., Paso T., Tuovinen T., Haapola J., Hämäläinen M. and Iinatti J. “Propagation Effects and Antenna Properties and Their Impact on ED Receivers’ Performance in Body Sensor Network”. The 8th International Symposium on Medical Information & Communication Technology (ISMICT2014), 2.-4.4.2014, Florence, Italy.

[12] Petäjäjärvi J., Karvonen K., Vuohtoniemi R., Hämäläinen M., Huttunen H., ”Preliminary Study of Superregenerative Wake-up Receiver with Addressing Capability”. The 8th International Symposium on Medical Information & Communication Technology (ISMICT2014), 2.-4.4.2014, Florence, Italy.

[13] Kumpuniemi T., Hämäläinen M., Tuovinen T., Yekeh Yazdandoost K., Iinatti J., “Radio Channel Modelling for Pseudo-Dynamic WBAN On-Body UWB Links”. The 8th International Symposium on Medical Information & Communication Technology (ISMICT2014), 2.-4.4.2014, Florence, Italy.

[14] Darooei Zadeh A., Bagheri H., Katz M., “Using Mobile Clouds in Medical ICT scenarios: A Preliminary Study”. The 8th International Symposium on Medical Information & Communication Technology (ISMICT2014), 2.-4.4.2014, Florence, Italy.

[15] Hämäläinen M., Kumpuniemi T., Iinatti J., “Observations from Ultra Wideband On-body Radio Channel Measurements”. 31th URSI General Assembly and Scientific Symposium (31th URSI GASS), 16.-23.8.2014, Beijing, China.

[16] Karvonen H., Petäjäjärvi J., Iinatti J., Hämäläinen M., Pomalaza-Raez C., “A Generic Wake-up Radio based MAC Protocol for Energy Efficient Short Range Communication”. Workshop on "The Convergence of Wireless Technologies for Personalized Healthcare" in Conjuction with  IEEE 25th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC2014), 2.–5.9.2014, Washington, DC, USA.

[17] Virk M. H., Vuohtoniemi R., Hämäläinen M., Mäkelä J.-P., Iinatti J., “Spectrum Occupancy Evaluations at 2.35-2.50 GHz ISM Band in a Hospital Environment”. The 9th International Conference on Body Area Networks (BodyNets-2014), 29.9.–1.10.2013, London, UK.

[18] Mucchi L., Carpini A., Kumpuniemi T., Hämäläinen M., Iinatti J., “Evaluation of the Aggregate Interference in Hospital ISM Band”. The 9th International Conference on Body Area Networks (BodyNets-2014), 29.9.–1.10.2013, London, UK.

[19] Karvonen H., Petäjäjärvi J., Iinatti J., Hämäläinen M., Energy Efficient IR-UWB WBAN using a Generic Wake-up Radio based MAC Protocol. UWBAN-2014 (Ultra Wide Band for Body Area Networking-2014) Workshop Co-located with the 9th International Conference on Body Area Networks (BodyNets-2014), 29.9.–1.10.2014, London, UK.

[20] Kumpuniemi T., Hämäläinen M., Yekeh Yazdandoost K., Iinatti J., Human Body Size and Shape Effect on UWB On-Body WBAN Radio Channels - Preliminary Results. UWBAN-2014 (Ultra Wide Band for Body Area Networking-2014) Workshop Co-located with the 9th International Conference on Body Area Networks (BodyNets-2014), 29.9.–1.10.2014, London, UK.

[21] Berg M., Tuovinen T., Propagation along a Human Body Surface in WBAN: Remarks of Desirable Antenna Characteristics. 4th International Conference on Wireless Mobile Communication and Healthcare (MobiHealth-2014), 3.–5.11.2014, Athens, Greece.

[22] T. Tuovinen, M. Berg, W. Whittow, E. Salonen, Performance of WBAN on Ground Antenna Type with Relation to Analytical Path Loss Model. The 8th International Loughborough Antennas and Propagation Conference (LAPC), Loughborough, United Kingdom, on 10-11th November 2014.

[23] M. Berg, T. Tuovinen, E. Salonen, Low-Profile Antenna with Optimal Polarization for 2.45 GHz On-Body Sensor Nodesl. The 10th International Loughborough Antennas and Propagation Conference (LAPC), Loughborough, United Kingdom, on 10-11th November 2014.

[24] M. F. Hanif, L.-N. Tran, A. Tölli & M. Juntti, “Computationally efficient robust beamforming for SINR balancing in multicell downlink with applications to large antenna array systems”. IEEE Transactions on Communications, vol. 62, no. 6, pp. 1908–1920, June 2014.
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6807782

[25] M. F. Hanif, L.-N. Tran, M. Juntti & S. Glisic, “On Linear precoding strategies for secrecy rate maximization in multiuser multiantenna wireless networks”. IEEE Transactions on Signal Processing, vol. 62, no. 14, pp. 3536–3551, July 15, 2014.
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6820768

[26] L.-N. Tran, M. F. Hanif & M. Juntti, ”A conic quadratic programming approach to physical layer multicasting for large-scale antenna arrays”. IEEE Signal Processing Letters, vol. 21, no. 1, pp. 114–117, January 2014.
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6681898

[27] P. Jayasinghe, L. K. S. Jayasinghe, M. Juntti & M. Latva-aho, “Performance analysis of optimal beamforming in non-coherent AF MIMO relaying over asymmetric fading channels”. IEEE Transactions on Communications, vol. 62, no. 4, pp. 1201–1217, April 2014.
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6750423

[28] E. Suikkanen & M. Juntti, ” Study of adaptive detection and channel estimation for MIMO–OFDM systems”. Wireless Personal Communications, vol. 73, no. 3, December 2014.
http://link.springer.com/article/10.1007/s11277-014-2230-0?sa_campaign=email/event/articleAuthor/onlineFirst#

[29] Q. Sun, L. Li, M. Juntti, A. Tölli & J. Mao, ”Optimal energy efficient bit and power loading for multicarrier systems”. IEEE Communications Letters, vol. 18, no. 7, pp. 1194–1197, July 2014.
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6802448

[30] A. Yadav, M. Juntti & J. Lilleberg, “Linear precoder design for doubly correlated partially coherent fading MIMO channels”, IEEE Transactions on Wireless Communications, vol. 13, no. 7, pp. 3621–3635, July 2014.
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6798756

[31] S. Lin, L. Wang, A. Vosoughi, J. Cavallaro, M. Juntti, J. Boutellier, O. Silven, M. Valkama & S. S. Bhattacharyya, “Dynamic dataflow modelling and design for cognitive radio networks on heterogeneous platforms”. Journal of Signal Processing Systems, to appear.

[32] J. Kokkoniemi, J. Lehtomäki, K. Umebayashi & M. Juntti, ”Frequency and time domain channel models for nanonetworks in Terahertz band”. IEEE Transactions on Antennas and Propagation, to appear 2015.

[33] M. Leinonen, M. Codreanu & M. Juntti “Sequential compressed sensing with progressive signal reconstruction in wireless sensor networks”. IEEE Transactions on Wireless Communications, to appear 2015.

[34] M. F. Hanif, L.-N. Tran & M. Juntti, “Antenna selection with erroneous covariance matrices under secrecy constraints”. IEEE Transactions on Vehicular Technology, submitted September 2014, revised December 2014.

[35] J. Lehtomäki, M. Lopez-Benitez, K. Umebayashi & M. Juntti, ”Improved channel occupancy rate estimation”. IEEE Transactions on Communications, to appear 2015.

[36] Q.-D. Vu, L.-N. Tran, M. Juntti & E.-K. Hong, ”Energy-efficient bandwidth and power allocation for multi-homing networks”. IEEE Transactions on Signal Processing, submitted September 2014, revised November 2014.

[37] R. Asvadi, T. Matsumoto & M. Juntti, ”LDPC code optimization with joint source-channel decoding of quantized Gauss-Markov signals”. Proceedings of IEEE International Conference on Communications (ICC 2014), Sydney, Australia, June 10–14, 2014, pp. 5233–5238.
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6884152

[38] A. Ghazi, J. Boutellier, M. Abdelaziz, X. Lu, L. Anttila, J. R. Cavallaro, S. S. Bhattacharyya, M. Valkama & M. Juntti, “Low power implementation of digital predistortion filter on a heterogeneous application specific multiprocessor”. Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2014), Florence, Italy, May 4–9, 2014, pp. 8336–8340.
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6855227

[39] G. Destino, D. Macagnano, M. Juntti & S. Nagaraj, ”Sparsity-aware channel estimation with contaminated pilot sequence”. Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2014), Florence, Italy, May 4–9, 2014, pp. 6469–6473.
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6854850

[40] J. Kaleva, R. Berry, M. Honig, A. Tölli & M. Juntti, “Decentralized sum MSE minimization for coordinated multi-point transmission”. Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2014), Florence, Italy, May 4–9, 2014, pp. 469–473.
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6853640

[41] Z. Khan, J. J. Lehtomäki, L. A. DaSilva, M. Latva-aho & M. Juntti, “Adaptation in a channel access game with private monitoring”. Proceedings of IEEE Global Telecommunications Conference (GLOBECOM 2013), Atlanta, Georgia, USA, December 9–13, 2013, pp. 3157–3163.
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6831557

[42] M. Leinonen, M. Codreanu & M. Juntti, “Compressed acquisition and progressive reconstruction of multi-dimensional correlated data in wireless sensor networks”. Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2014), Florence, Italy, May 4–9, 2014, pp. 6449–6453.
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6854846

[43] X. Lu, A. Tölli, L. Anttila, M. Juntti & M. Valkama, “Multiuser frequency allocation with wideband power amplifier models”. Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2014), Florence, Italy, May 4–9, 2014, pp. 3913–3917.
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6854335

[44] T. Tuovinen, M. Berg, “Impedance dependency on planar broadband dipole dimensions: an examination with antenna equivalent circuits”. Progress in Electromagnetics Research 144, pp. 249-260.
http://www.jpier.org/PIER/pier.php?paper=13112202.

[45] T. Tuovinen, M. Berg, J. Iinatti, “Analysis of the impedance behaviour for broadband dipoles in proximity of a body tissue: approach by using antenna equivalent circuits”. Progress in electromagnetics research B 59, pp. 135-150.
http://www.jpier.org/PIERB/pier.php?paper=14021902.                    

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Last updated: 10.3.2015