Ayman Fawzy Naguib

Propagation Modeling for Accurate Indoor WLAN RSS-Based Localization

WLAN RSS-based localization has been a hot research topic for the last years. To obtain high accuracy in the noisy wireless channel, WLAN location determination systems usually use a calibration phase, where a radio map, capturing the signal strength signatures at different locations in the area of interest, is built. The radio map construction process takes a lot of time and effort, reducing the value of WLAN localization systems. In this paper, we propose 3D ray tracing as a way for automatically generating a highly accurate radiomap. We compare this method to previously used propagation modeling-based methods like the Wall Attenuation Factor and 2D ray tracing models. We evaluate the performance of each method and its computational cost in a typical residential environment. We also examine the sensitivity of the localization accuracy to inaccurate material parameters. Our results quantify the accuracy- complexity trade-off of the different proposed techniques with 3D ray tracing giving the best localization accuracy compared to measurements with acceptable computational requirements on a typical PC.

Combined interference suppression and frequency domain equalization for space-time block coded transmission

We present a transmission scheme that combines space-time block coding over frequency selective channels with single carrier frequency domain interference suppression and equalization. The equalization and interference suppression exploits the structure of the space-time block coding. It is shown that this scheme will provide the diversity benefit of both the frequency selective channel and the space-time block code while completely suppressing the interference from another co-channel transmitter that occupies exactly the same channel (time & frequency) as the desired transmitter.

Field Results on MIMO Performance in UMB Systems

The paper presents MIMO field performance results observed using a ultra mobile broadband (UMB) testbed network. We evaluate metrics such as antenna correlations and channel condition number to characterize the MIMO channel. Results show that low condition numbers, which are beneficial to MIMO, are prevalent for a majority of the coverage area in our network. We demonstrate that the use of MIMO provides gains of the order of 20-40% over SIMO transmissions. These gains are made possible by the use of cross-polarized transmit antennas and advanced UMB features that allow dynamic MIMO vs. SIMO transmission selection based on channel conditions. These results are obtained in a truly mobile, wireless wide-area deployment, which makes them unique. Our results point to the viability and value of MIMO in future mobile wireless networks.

Scalable and accurate indoor positioning on mobile devices

Location-based services (LBS) are an integral part of the mobile ecosystem today, relying on the Global Positioning System (GPS) and other technologies. However, while these technologies have been highly successful at positioning outdoors, they either fail to obtain a fix or do not provide the necessary accuracy indoors. In this paper, we will describe a low-cost high-accuracy indoor positioning system that can run on mobile devices. The system has high-accuracy because it combines several sources of information, thus improving accuracy over using any one of them alone. The cost is low because the sources of information used by the system such as WiFi measurements, inertial sensor data and building maps are readily available for use on a mobile device.

Receiver based PAPR reduction in OFDMA

High peak-to-average power ratio is one of the major drawbacks of orthogonal frequency division multiplexing (OFDM). Clipping is the simplest peak reduction scheme, however, it requires clipping mitigation at the receiver. Recently compressed sensing has been used for clipping mitigation (by exploiting the sparse nature of clipping signal). However, clipping estimation in multi-user scenario (i.e., OFDMA) is not straightforward as clipping distortions overlap in frequency domain and one cannot distinguish between distortions from different users. In this work, a collaborative clipping removal strategy is proposed based on joint estimation of the clipping distortions from all users. Further, an effective data aided channel estimation strategy for clipped OFDM is also outlined. Simulation results are presented to justify the effectiveness of the proposed schemes.

Introduction to the Issue on Managing Complexity in Multiuser MIMO Systems

A DECADE has passed since the pioneering works in which multiple-input multiple-output (MIMO) wireless systems have been introduced. By using multiple antennas at both link ends, MIMO in theory offers tremendous rate and reliability gains. These promises have spurred an extraordinary amount of research activities. By now, MIMO has become a well-established research topic, with thousands of papers published on the topic each year (a search for “MIMO” on IEEEXplore reports 264 hits for the year 2000 and 2880 hits for 2008), addressing signal processing topics like data detection, space-time code design, precoding, beamforming, channel estimation, and synchronization (list not complete). So far, the largest part of MIMO research has been devoted to point-to-point (single-user) channels. It is only fairly recently that MIMO started to be considered in the context of multiuser (multipoint) systems, where additional opportunities like spatial multiple access, interference suppression, and improved resource allocation exist. In this context, the recent survey “Shifting the MIMO paradigm” by Gesbert et al. in the Sept. 2007 issue of the IEEE Signal Processing Magazine is recommended reading. Soon after its introduction, MIMO technology also started to attract the attention of standardization bodies. By now, MIMO techniques have been incorporated into the mainstream of wireless standards like IEEE 802.11n (high-throughput WiFi), IEEE 802.16x (802.16e, a.k.a. mobile WiMAX, and upcoming 802. 16m), and 3GPP’s Long Term Evolution (LTE). While WiFi and 802.16e build on single-user MIMO techniques like spatial multiplexing and space-time coding, LTE Advanced and 802.16m also add multiuser MIMO features. In spite of the plethora of MIMO research and the fact that MIMO is now part of several standards, industry still faces problems with integrating MIMO into their products. The principal barrier to widespread industry adoption is implementation complexity and the sensitivity of receiver signal processing to departures from the standard propagation assumption of Rayleigh scattering. Management of signal processing complexity is thus essential to realizing the theoretical promise of MIMO technology. Here, the goal is to cleverly design tunable algorithms for the terminal and infrastructure side that entail a graceful trade-off between performance and implementation complexity. Substantial advances in this area would certainly have a big practical impact, e.g., with chip manufacturers and terminal and infrastructure vendors. There are 17 papers in this special issue that deal with various aspects of this challenging new thread in MIMO research. We have grouped these papers according to the following three major research themes: efficiently decodable space–time codes,

On the utility of primary side information in cognitive sensing

In this paper, we study the impact of the knowledge of primary side information on the efficiency of spectrum sensing for cognitive radio networks. In particular, assuming that the secondary transmitter knows the modulation and/or coding scheme used in the primary transmissions, we evaluate the efficiency of spectrum sensing in terms of maximizing the overall achievable throughput of the system. We present the results for both block-based and sequential detection techniques. We show that in sequential detection, and when the cognitive transmitter has knowledge of the primary codebook, the detection threshold should be adaptive based on the previous observations. Our results show the gains achieved over energy based techniques.