Boon Sim Thian

Wireless NUM: Rate and Reliability Tradeoffs in Random Environment

We describe Wireless Network Utility Maximization, WNUM, and compare its performance to NUM for wireless networks of interfering links under random time varying channel conditions. WNUM is shown to simultaneously offer greater rate and reliability performance in simulations operating under Rayleigh fading. A general method for finding adaptive network control policies is presented that is samplebased and converges to the optimal control policies for the network.

A Reduced-Complexity MIMO Receiver via Channel Ordering

We consider the problem of maximum likelihood (ML) signal detection in multiple-input multiple-output (MIMO) wireless communication systems. We propose a new preprocessing algorithm in the form of channel ordering for sphere decoders. Numerical results show that this new channel ordering leads to significantly lower complexity (in the form of the number of nodes visited by the search algorithm); for MPSK modulation where M ≥ 8 and a moderate SNR range of 15 - 24 dB, our channel ordering results in a two-fold to four-fold decrease in the number of nodes visited by the search algorithm. We also present a brief review of the SDR-ML detector, formulated using semidefinite programming and relaxation techniques. Finally, we propose a combined SDR-ML-sphere decoder and demonstrate that it further reduces the number of nodes visited by the search algorithm; for a 20×20 BPSK-modulated MIMO system and SNR of 8 dB, the SDR-ML-sphere decoder has an average complexity that is approximately 5 times less than the sphere decoder.

Reduced-Complexity Robust MIMO Decoders

We propose a robust near maximum-likelihood (ML) decoding metric that is robust to channel estimation errors and is near optimal with respect to symbol error rate (SER). The solution involves an exhaustive search through all possible transmitted signal vectors; this search has exponential complexity, which is undesirable in practical systems. Hence, we also propose a robust sphere decoder to implement the decoding with substantially lower computational complexity. For a real 4 x 4 MIMO system with 256-QAM modulation and at SER of 10^{-3}, our proposed robust sphere decoder has a coding loss of only 0.5 dB while searching through 2360 nodes (or less) compared to a 65536 node search using the exact ML metric. This translates to up to 228 times fewer real multiplications and additions in the implementation. We derive analytical upper bounds on the pairwise codeword error rate and symbol error rate of our robust sphere decoder and validate these bounds via simulation.

Decoding for MIMO systems with correlated channel estimation errors

We consider receiver design in uncoded multiple-input multiple-output (MIMO) wireless communication systems. Practical MIMO systems assume an accurate estimate of the channel state information (CSI) at the receiver; failure to estimate the channel accurately or to account for CSI errors in the receiver leads to poor performance in terms of high symbol error rate (SER) in data detection. Since CSI estimation at the receiver is often imperfect due to measurement errors, quantization errors and other sources of error, it is imperative that MIMO receivers account for CSI errors. In this paper, we design a MIMO receiver that considers channel estimation error; the only assumption we make about the error is its Gaussianity. We allow correlation to exist between channel estimation errors and propose a generalized robust maximum-likelihood (ML) decoder that is robust to CSI errors and is near optimal in the SER (i.e probability of symbol error) performance metric. Our proposed decoder has exponential complexity which is undesirable in practical systems. Hence, we also propose a recursive search algorithm to implement our generalized robust ML decoder with substantially lower computational complexity. For a 4×4 MIMO system with 256-QAM modulation and at SER of 10−3, our proposed generalized robust ML decoder has a coding loss of only 0.5 dB while searching through 2360 nodes (or less) compared to 65536 using the exact ML metric. This translates to up to 228 times fewer real multiplications and additions in the implementation.

Statistical Precoding for MIMO Systems With Channel Estimation Errors

Obtaining accurate instantaneous channel state information (CSI) is challenging for multiple-input-multiple-output (MIMO) systems, particularly if the channel fluctuates rapidly. A more practical assumption is statistical CSI as the channel statistics are likely to remain unchanged for a longer period. In this letter, we propose a precoder design, using only statistical CSI, to minimize error probability for practical MIMO systems with channel estimation errors. Our proposed precoder design is shown to achieve a significant improvement in error performance when compared with other precoding schemes in literature. For example, for a real 4 × 4 MIMO system with BPSK modulation and at a codeword error rate of 10-3, coding gains of up to 12 dB can be achieved.

A New Receiver Structure for DFT Spread OFDM (DFT-SOFDM) in Time-Selective Fading Channel

The transmission of a Discrete Fourier Transform Spread Orthogonal Frequency Division Multiplexing (DFT-SOFDM) signal through a time-selective fading channel suffers from severe performance degradation due to the Doppler shifting of the transmitted spectrum. In this paper, we propose a multiple-input multiple-output (MIMO) DFT-SOFDM scheme and a new technique to overcome the adverse effects caused by Doppler shift. By appropriately interleaving the transmitted signals in space and time, our scheme allows us to use linear equalization techniques such as the zero-forcing (ZF) and minimum mean-squared error (MMSE) equalization. In addition, the use of sphere decoding algorithm (SDA) provides superior BER performance compared to the ZF or MMSE solution. Simulation results show that at a BER of 10 3, SDA provides a 13.5 dB gain over ZF solution, and a 13 dB gain over MMSE solution. The system with SDA shows negligible performance degradation when the system load in the uplink is increased: at Eb/No = 21 dB, a BER of 1.88 times 10-5 is achieved when there are 2 users in the system, but degrades only to 2.19 times 10-5 for a 8 user system. In addition, SDA used with our proposed signal model offers significantly lower worst case complexity as compared to the conventional DFT-SOFDM with SDA.

A transceiver scheme for localized DFT spread OFDM (DFT-SOFDM) in time-selective channel

The transmission of Discrete Fourier Transform Spread Orthogonal Frequency Division Multiplexing (DFT-SOFDM) [4] through a time-selective fading channel with a significant amount of Doppler spread suffers from severe performance degradation. A shift in frequency caused by such channel leads to a loss of orthogonality between users. In this paper, we propose a DFT-SOFDM scheme augmented by MIMO and a new technique to overcome the adverse effects caused by Doppler shift. Repeated Alamouti orthogonal space time block codes are used for transmission of localized MIMO DFT-SOFDM signal. We derive the Minimum Mean-Squared Error (MMSE) combining and estimation scheme that ensures superior BER performance compared to the conventional Maximal-Ratio Receive Combining (MRRC) scheme. The proposed receiver provides a performance gain of 8.6 dB for a 4 users system at BER= 10-3. This gain improves with increased number of users. MRRC gives an error floor due to multiple access interference, which increases with system load.

A Hybrid Receiver Scheme for Multiuser Multicode CDMA Systems in Multipath Fading Channels

In this paper, we present a system model for multiuser multicode code-division multiple access (CDMA) in a multipath fading channel and propose a hybrid receiver scheme for the system. Conventional receivers for CDMA systems utilized interference cancellation (IC) schemes, with the RAKE receiver as an initial data estimator. However, the RAKE receiver generates inaccurate data estimates due the interference that is caused by the cross correlation between the spreading codes. This inaccurate data estimate leads to significant error propagation to the subsequent stages and thus degrades the bit error rate (BER) performance. Our proposed scheme overcomes the problem by using a more accurate initial data estimator. It consists of an equalizer for obtaining initial data estimation, followed by several stages of parallel IC (PIC). Computer simulation results show that the BER curves of our proposed scheme do not encounter an error floor under all channel conditions; in contrast, the BER curves of the conventional RAKE-PIC receiver are constrained by an irreducible error floor. In addition, in an uplink four-path channel and at a BER of 10-3, our simulation results show that a one-stage PIC achieves a 2.5-dB gain over the first stage equalization receiver.

Minimizing Transmit Power in a Virtual-Cell Downlink with Distributed Antennas

We consider the problem of allocating transmit power in the downlink of a distributed wireless communication system. We account for the power used in both channel estimation and data transmission, with the objective of minimizing the overall transmitted power while satisfying specified Quality of Service (QoS) constraints to the mobile users. We consider both single user and multi-user power control optimization; the problem formulation for both cases lead to a nonconvex program. We proposed solution strategies for both scenarios: For the single user case, a simple intuitive solution, where power is allocated to the antennas sequentially until the QoS constraint is satisfied, is presented. For the multi-user case, we use successive convex approximation (based on the single condensation method) to find a provably convergent solution. We also demonstrate, via numerical simulation, the convergence of the proposed multi-user power allocation strategy. Our numerical results indicate that the proposed single and multi-user power allocation lead to an overall savings of up to 45% when compared to the baseline method of equal power allocation.

DFT-spread OFDM for uplink flexible high data rate communications

In this paper, we develop and present a DFT-SOFDM system (operating in both distributed and localized FDMA modes) for transmission and reception through a frequency-selective, slow fading channel. This system allows us to use well-known linear receiver techniques such as the zero-forcing (ZF) and minimum mean-squared error (MMSE) equalization. More importantly, we proposed using a sphere decoding algorithm (SDA) on DFT-SOFDM to obtain a maximum-likelihood (ML) estimate on the received signal, hence achieving superior bit error rate (BER) performance without the complexity of an exhaustive search. Simulation results show that SDA gives superior BER performance for both distributed and localized DFT-SOFDM compared to suboptimal ZF or MMSE receivers.