This paper describes a direct conversion receiver applying compressed sensing with the objective to relax the analog filtering requirements seen in the traditional architecture. The analog filter is cumbersome in an Integrated Circuit (IC) design and relaxing its requirements is an advantage in terms of die area, performance and robustness of the receiver. The objective is met by a selection of sampling pattern matched to the prior knowledge of the frequency placement of the desired and interfering signals. A simple numerical example demonstrates the principle. The work is part of an ongoing research effort and the different project phases are explained.

Reconstruction of an undersampled signal is at the root of compressive sensing: when is an algorithm capable of reconstructing the signal? what quality is achievable? and how much time does reconstruction require? We have considered the worst-case performance of the smoothed ℓ0norm reconstruction algorithm in a noiseless setup. Through an empirical tuning of its parameters, we have improved the phase transition (capabilities) of the algorithm for fixed quality and required time. In this paper, we present simulation results that show a phase transition surpassing that of the theoretical ℓ1approach: the proposed modified algorithm obtains 1-norm phase transition with greatly reduced required computation time.

The source coding problem with action-dependent side information at the decoder has recently been introduced to model data acquisition in resource-constrained systems. In this paper, an efficient Blahut-Arimoto-type algorithm for the numerical computation of the rate-distortion-cost function for this problem is proposed. Moreover, a simplified two-stage code structure based on multiplexing is put forth, whereby the first stage encodes the actions and the second stage is composed of an array of classical Wyner-Ziv codes, one for each action. Leveraging this structure, specific coding/decoding strategies are designed based on LDGM codes and message passing. Through numerical examples, the proposed code design is shown to achieve performance close to the rate-distortion-cost function.

The modulation accuracy described by an error vector magnitude is a critical parameter in modern communication systems - defined originally as a performance metric for transmitters but now also used in receiver design and for more general signal analysis. The modulation accuracy is a measure of how far a test signal is from a reference signal at the symbol values when some parameters in a reconstruction model are optimized for best agreement. This paper provides an approach to computation of error vector magnitude as described in several standards from measured or simulated data. It is shown that the error vector magnitude optimization problem is generally non-convex. Robust estimation of the initial conditions for the optimizer is suggested, which is particularly important for a non-convex problem. A Bender decomposition approach is used to separate convex and non-convex parts of the problem to make the optimization procedure simpler and robust. A two step global optimization method is suggested where the global step is the grid method and the local method is the Newton method. A number of test cases are shown to illustrate the concepts.

With the advent of ubiquitous computing there are two design parameters of wireless communication devices that become very important: power efficiency and production cost. Compressive sensing enables the receiver in such devices to sample below the Shannon-Nyquist sampling rate, which may lead to a decrease in the two design parameters. This paper investigates the use of Compressive Sensing (CS) in a general Code Division Multiple Access (CDMA) receiver. We show that when using spread spectrum codes in the signal domain, the CS measurement matrix may be simplified. This measurement scheme, named Compressive Spread Spectrum (CSS), allows for a simple, effective receiver design. Furthermore, we numerically evaluate the proposed receiver in terms of bit error rate under different signal to noise ratio conditions and compare it with other receiver structures. These numerical experiments show that though the bit error rate performance is degraded by the subsampling in the CS-enabled receivers, this may be remedied by including quantization in the receiver model. We also study the computational complexity of the proposed receiver design under different sparsity and measurement ratios. Our work shows that it is possible to subsample a CDMA signal using CSS and that in one example the CSS receiver outperforms the classical receiver.

In compressed sensing it is generally assumed that the dictionary matrix constitutes a (possibly overcomplete) basis of the signal space. In this paper we consider dictionaries that do not span the signal space, i.e. rank deficient dictionaries. We show that in this case the signal-to-noise ratio (SNR) in the compressed samples can be increased by selecting the rows of the measurement matrix from the column space of the dictionary. As an example application of compressed sensing with a rank deficient dictionary, we present a case study of compressed sensing applied to the Coarse Acquisition (C/A) step in a GPS receiver. Simulations show that for this application the proposed choice of measurement matrix yields an increase in SNR performance of up to 5-10 dB, compared to the conventional choice of a fully random measurement matrix. Furthermore, the compressed sensing based C/A step is compared to a conventional method for GPS C/A.

The technology of Radio Frequency IDentification (RFID) enables many applications that rely on passive, battery-less wireless devices. If a RFID reader needs to gather the ID from multiple tags in its range, then it needs to run an anticollision protocol. Due to errors on the wireless link, a single reader session, which contains one full execution of the anticollision protocol, may not be sufficient to retrieve the ID of all tags. This problem can be mitigated by running multiple, redundant reader sessions and use the statistical relationship between these sessions. On the other hand, each session is time consuming and therefore the number of sessions should be kept minimal. We optimize the process of running multiple reader sessions, by allowing only some of the tags already discovered to reply in subsequent reader sessions. The estimation procedure is integrated with an actual tree-based anticollision protocol, and numerical results show that the reliable tag resolution algorithm attain high speed of protocol execution, while not sacrificing the reliability of the estimators used to assess the probability of missing tags.

We propose a new multiple description spherical quantization with repetitively coded amplitudes (MDSQRA) scheme suited for quantization of sinusoidal parameters. The quantization scheme is constituted by a set of spherical quantizers inspired by the multiple description spherical trellis-coded quantization (MDSTCQ) scheme. In this scheme, we apply repetitive coding on the amplitudes, while multiple description coding are applied on the phases and frequencies. Thereby, MDSQRA becomes directly implementable, as opposed to MDSTCQ, since the phase and frequency quantizers depend on the amplitudes which have dissimilar descriptions in MDSTCQ. Furthermore, we implement MDSQRA into a perceptual matching pursuit based sinusoidal audio coder. Finally, we evaluate MDSQRA through perceptual distortion measurements and MUSHRA listening tests. The tests show that MDSQRA outperforms MDSTCQ with respect to a expected perceptual distortion measure. The same results are obtained through the MUSHRA tests performed on sound clips coded using MDSQRA and MDSTCQ.

Media content distribution constitutes a growing share of the services on the Internet. Two distinct distribution approaches used today are layered coding (LC) and multiple description coding (MDC). Current wireless connection technologies, e.g. Wimax, have properties which make them unsuitable for media distribution using traditional approaches. In particular, the asymmetric relationship between the uplink and the downlink bandwidth makes the cooperative distribution difficult. A promising concept, termed MDC with Conditional Compression (MDC-CC), has been proposed [11], which essentially acts as an adaptive hybrid between LC and MDC. In order to facilitate the use of MDC-CC, a new overlay network approach is proposed, using tree of meshes. A control system for managing description distribution and compression in a small mesh is implemented in the discrete event simulator NS-2. The two traditional approaches, MDC and LC, are used as references for the performance evaluation of the proposed scheme. The system is simulated in a heterogeneous network environment, where packet errors are introduced. Moreover, a test is performed at different network loads. Performance gain is shown over both LC and MDC.

This paper proposes a physical-layer security scheme for wireless networks, aiming to achieve communication secrecy by making the eavesdropper incapable of decoding the secret wireless message. The considered scenario features one user within the range of two access points, API and AP2. The APs are assumed to be connected through an alternative secure (e.g. wired) connection. The goal is to secure the wireless link between the user and API. While the user transmits to API, AP2 simultaneously transmits an interfering signal, which is a priori provided to API, such that API is likely the only node capable of decoding the user's entire transmission. Evaluation is done through simulation by measuring the upper bound of the information-theoretic secrecy and error performance. In the latter case it is shown that the eavesdropper experiences significantly higher error rates than the intended receiver, thus providing evidence of practical security.

In this paper we investigate the effect of modelled RF transmitter impairments on UTRA Long Term Evolution (LTE) uplink link performance. Nonlinear power amplifier, gain imbalance, phase imbalance, and phase noise are considered. The main contributions of this work is assessment of the relation between Error Vector Magnitude (EVM) and link performance loss due to each impairment and the investigation of a white Gaussian noise source in the transmitter as an equivalent model of the impairment. The results obtained are based on the UTRA LTE uplink parameter settings. Results show that the EVM is a good measure to estimate the link level performance loss for numerous impairments. The performance degradation in AWGN and a frequency selective fading when using a white noise source as an equivalent transmitter RF impairment model, fits well with the other impairments in the anticipated range of EVM. An analytical formulation describing the effect of the white noise source in the SNR loss fits similarly with the simulation results. With 16 QAM rate 3/4, an EVM value of 8% corresponds to an SNR loss of approximately 0.5 dB.

Cellular multihop networks has the potential to decrease power consumption, increase coverage and/or enable higher data rates. We propose using in-band transmissions for the connection between a fixed repeating device and the cellular base station. A user connected via the repeater use one frequency band (fq2) for the communication to the repeater and the repeater uses an adjacent frequency band (fql) for the communication to the base station. There is strong interference in the repeater due to transmitting and receiving on adjacent frequency bands, and strong interference from users connected directly to the base station on fq2. We demonstrate that the method can be used to introduce multihop functionality into a WCDMA FDD cellular system with only small changes. In a pessimistic scenario repeated users can lower their transmit power, but others have to increase their power. The multihop system requires no extra frequency spectrum but it has a small capacity penalty, and it requires a high adjacent channel leakage ratio in the repeaters. The results are reasonable for this pessimistic study and suggest further studies of alternative scenarios to improve the performance.