Yingwei Yao

Blind carrier frequency offset estimation in SISO, MIMO, and multiuser OFDM systems

Relying on a kurtosis-type criterion, we develop a low-complexity blind carrier frequency offset (CFO) estimator for orthogonal frequency-division multiplexing (OFDM) systems. We demonstrate analytically how identifiability and performance of this blind CFO estimator depend on the channels frequency selectivity and the input distribution. We show that this approach can be applied to blind CFO estimation in multi-input multi-output and multiuser OFDM systems. The issues of channel nulls, multiuser interference, and effects of multiple antennas are addressed analytically, and tested via simulations.

On energy efficiency and optimum resource allocation of relay transmissions in the low-power regime

Relay links are expected to play a critical role in the design of wireless networks. This paper investigates the energy efficiency of relay communications in the low-power regime under two different scenarios: when the relay has unlimited power supply and when it has limited power supply. A system with a source node, a destination node, and a single relay operating in the time division duplex (TDD) mode was considered. Analysis and simulations are used to compare the energy required for transmitting one information bit in three different relay schemes: amplify and forward (AnF), decode and forward (DnF), and block Markov coding (BMC). Relative merits of these relay schemes in comparison with direct transmissions (direct Tx) are discussed. The optimal allocation of power and transmission time between source and relay is also studied.

Energy-efficient scheduling for wireless sensor networks

We consider the problem of minimizing the energy needed for data fusion in a sensor network by varying the transmission times assigned to different sensor nodes. The optimal scheduling protocol is derived, based on which we develop a low-complexity inverse-log scheduling (ILS) algorithm that achieves near-optimal energy efficiency. To eliminate the communication overhead required by centralized scheduling protocols, we further derive a distributed inverse-log protocol that is applicable to networks with a large number of nodes. Focusing on large-scale networks with high total data rates, we analyze the energy consumption of the ILS. Our analysis reveals how its energy gain over traditional time-division multiple access depends on the channel and the data-length variations among different nodes.

Non-coherent distributed space-time processing for multiuser cooperative transmissions

User cooperation can provide spatial transmit diversity gains, enhance coverage and potentially increase capacity. Existing works have focused on two-user cooperative systems with perfect channel state information at the receivers. In this paper, we develop several distributed space-time processing schemes for general N-user cooperative systems, which do not require channel state information at either relays or destination. We prove that full spatial diversity gain can be achieved in such systems. Simulations demonstrate that these cooperative schemes achieve significant performance gain

Achievable rates in low-power relay links over fading channels

Relayed transmissions enable low-power communications among nodes (possibly separated by a large distance) in wireless networks. Since the capacity of general relay channels is unknown, we investigate the achievable rates of relayed transmissions over fading channels for two transmission schemes: the block Markov coded and the time-division multiplexed (TDM) transmissions. The normalized achievable minimum energy per bit required for reliable communications is derived, which also enables optimal power allocation between the source and the relay. The time-sharing factor in TDM transmissions is optimized to improve achievable rates. The region where relayed transmission can provide a lower minimum energy per bit than direct transmission, as well as the optimal relay placement for these two transmission schemes, are also investigated. Numerical results delineate the advantages of relayed, relative to direct, transmissions.

Rate-maximizing power allocation in OFDM based on partial channel knowledge

Power loading algorithms improve the data rates of orthogonal frequency division multiplexing (OFDM) systems. However, they require the transmitter to have perfect channel state information, which is impossible in most wireless systems. We investigate the effects of imperfect (and thus partial) channel feedback on the throughput of OFDM systems. Two channel uncertainty models are studied: 1) the ergodic model, where average rate is the figure of merit and 2) the quasi-static model, where outage rate is relevant. Rate-power allocation algorithms are developed. The throughput achieved by these algorithms and the effects of channel multipath are investigated analytically and with simulations.Power loading algorithms improve the data rates of OFDM systems. However, they require the transmitter to have perfect channel state information, which is impossible in most wireless systems. We investigate the effects of imperfect (and thus partial) channel feedback on the achievable rates of OFDM systems. Two cases are studied: i) ergodic channels, where average rate is the figure of merit; and ii) quasistatic channels, where the outage rate is relevant. Power loading algorithms and the effects of channel multipath are investigated analytically and with simulations.

Eavesdropping in the synchronous CDMA channel: an EM-based approach

The problem of blind detection in a synchronous code division multiple access (CDMA) system when there is no knowledge of the users spreading sequences is considered. An expectation maximization (EM)-based algorithm that exploits the finite alphabet (FA) property of the digital communications source is proposed. Simulations indicate that this approach, which makes use of knowledge of the subspace spanned by the signaling multiplex, achieves the Cramer-Rao lower bound (CRB). The issues of subspace estimation and timing acquisition are also considered.

Blind detection of synchronous CDMA in non-Gaussian channels

Most blind source separation algorithms assume the channel noise to be Gaussian. This paper considers the problem of noncooperative blind detection of synchronous direct-sequence code-division multiple-access communications (no knowledge of the spreading sequences or training data) in non-Gaussian channels. Three iterative algorithms with different performance and complexity tradeoffs are proposed. Simulation results show that they significantly outperform Gaussian-optimal blind source separation algorithms in non-Gaussian channels. The Cramer-Rao lower bound for this problem is computed, and the performance of the proposed algorithms is shown to approach this bound for moderate signal-to-noise ratios.

On regularity and identifiability of blind source separation under constant-modulus constraints

We investigate the information regularity and identifiability of the blind source separation (BSS) problem with constant modulus (CM) constraints on the sources. We establish for this problem the connection between the information regularity [existence of a finite Crame/spl acute/r-Rao bound (CRB)] and local identifiability. Sufficient and necessary conditions for local identifiability are derived. We also study the conditions under which unique (global) identifiability is guaranteed within the inherently unresolvable ambiguities on phase rotation and source permutation. Both sufficient and necessary conditions are obtained.

User capacity for synchronous multirate CDMA systems with linear MMSE receivers

The performance of linear minimum mean-square error (MMSE) multiuser receivers in a dual-rate synchronous direct-sequence code-division multiple-access (DS-CDMA) system is investigated using the random spreading sequence analysis. Multicode (MC) systems and different variants of variable spreading length (VSL) systems are studied. User capacity regions are obtained for these systems.