This paper addresses the joint design of transmit and receive beamforming or linear processing (commonly termed linear precoding at the transmitter and equalization at the receiver) for multicarrier multiple-input multiple-output (MIMO) channels under a variety of design criteria. Instead of considering each design criterion in a separate way, we generalize the existing results by developing a unified framework based on considering two families of objective functions that embrace most reasonable criteria to design a communication system: Schur-concave and Schur-convex functions. Once the optimal structure of the transmit-receive processing is known, the design problem simplifies and can be formulated within the powerful framework of convex optimization theory, in which a great number of interesting design criteria can be easily accommodated and efficiently solved, even though closed-form expressions may not exist. From this perspective, we analyze a variety of design criteria, and in particular, we derive optimal beamvectors in the sense of having minimum average bit error rate (BER). Additional constraints on the peak-to-average ratio (PAR) or on the signal dynamic range are easily included in the design. We propose two multilevel water-filling practical solutions that perform very close to the optimal in terms of average BER with a low implementation complexity. If cooperation among the processing operating at different carriers is allowed, the performance improves significantly. Interestingly, with carrier cooperation, it turns out that the exact optimal solution in terms of average BER can be obtained in closed form.

Orthogonal Frequency Division Multiplexing (OFDM) converts a dispersive channel into parallel subchannels and thus facilitates equalization. But when the channel has nulls close to or on the FFT grid, OFDM faces serious symbol recovery problems. As an alternative to various error-control coding techniques that have been proposed to ameliorate the problem, we linearly precode (LP) symbols before they are multiplexed. We identify the maximum achievable diversity order for i.i.d. or correlated Rayleigh fading channels and also provide design rules for achieving maximum diversity gains with LP-OFDM. Simulated performance comparisons of LP-OFDM with existing block and convolutionally coded OFDM alternatives favor LP-OFDM in a HiperLan2 experiment.

A novel approach of blind channel estimation for OFDM systems is proposed. A linear transformation is applied on each block before it enters the OFDM system. The transform imposes a correlation structure on the transmitted blocks, which is exploited at the receiver to recover the channel via simple cross-correlation operations. The proposed approach is computationally simple and converges fast, which makes it a good candidate for estimation of fast-varying channels. Its performance is tested analytically, through a mean-square error analysis, and also via simulations. Results show that it compares favorably to the training based scheme used in the IEEE 802.11a wireless standard.

This paper considers vector communication through a multi-input multi-output (MIMO) channel with a set of Quality of Service (QoS) requirements for the simultaneously established substreams. Linear transmit-receive processing (also termed linear precoder at the transmitter and linear equalizer at the receiver) is designed to satisfy the QoS constraints with minimum transmitted power. Although the original problem is a complicated nonconvex problem with matrix-valued variables, with the aid of majorization theory, we reformulate it as a simple convex optimization problem with scalar variables. We then propose a practical and e#cient multi-level water-filling algorithm to optimally solve the problem for the general case of different QoS requirements. The optimal transmit-receive processing is shown to diagonalize the channel matrix only after a very specific pre-rotation of the data symbols. For situations in which the resulting transmit power is too large, we give the precise way to relax the QoS constraints in order to reduce the required power based on a perturbation analysis. We also propose a robust design under channel estimation errors which has a great interest in real implementations.

In a multicarrier modulation system, a time domain equalizer (TEQ) traditionally shortens the transmission channel impulse response (CIR) to mitigate intersymbol interference (ISI). In this paper, we propose a data-rate optimal TEQ filter bank whose data rates at the equalizer output are significantly better than those of the Maximum Bit Rate and Minimum ISI methods and similar to those of the least-squares per-tone equalizer method for ADSL CIRs, transmit filters, and receive filters. The contributions of this paper are: (1) a new model for multicarrier demodulator output SNR that includes ISI, near-end crosstalk, white Gaussian noise, and the digital noise floor; (2) data rate optimal time domain per-tone TEQ filter bank, and (3) a new achievable upper bound on achievable bit rate.

The location, number, and power of pilot symbols embedded in multicarrier block transmissions over rapidly fading channels, are important design parameters affecting not only channel estimation performance, but also channel capacity. Considering OFDM systems with decoupled information-bearing symbols from pilot symbols transmitted over wireless frequencyselective Rayleigh fading channels, we show that equi-spaced and equi-powered pilot symbols are optimal in terms of minimizing the mean-square channel estimation error. We also design the number of pilots, and the power distributed between information bearing and pilot symbols, using as criterion a lower bound on the average capacity. Numerical results corroborate our theoretical findings.

In our software-defined radio project we aim at combining two standards: Bluetooth and HiperLAN/2. The HiperLAN /2 receiver requires the most computation power in comparison with Bluetooth. We choose to use this computational power also for Bluetooth and look for more advanced demodulation algorithms such as a Maximum A posteriori Probability (MAP) receiver. This paper discusses a simplified MAP receiver for Bluetooth GFSK signals. The Laurent decomposition provides an orthogonal vector space for the MAP receiver. As the first Laurent waveform contains the most energy we have used only this waveform for our (simplified) MAP receiver. This receiver requires a of about 11 dB for a BER of 10 -3 , required by the Bluetooth standard. This value is about 6 dB better than single bit demodulators. This performance will only be met if the receiver has exact knowledge of the modulation index.

Abstract—High performance frequency estimation is an important issue in orthogonal frequency division multiplexing (OFDM) systems since OFDM systems are very sensitive to carrier frequency offsets. Recently, Morelli & Mengali (M&M) [12] presented a near optimal frequency estimator based on the best linear unbiased estimation (BLUE) principle. In this paper, we have presented three frequency estimation methods based on the BLUE principle. The third method has the same frequency estimation mean square error (MSE) performance as the M&M method. The first two methods give better MSE performance than the M&M method especially at low SNR values. The first two methods ’ MSE performances are essentially the same and quite close to the Cramer-Rao lower bound for all SNR values, hence, these proposed methods are very attractive for OFDM applications. Index Terms—OFDM, Frequency offset, Frequency synchronization, BLUE.

A time domain equalizer (TEQ) is a finite impulse response filter that shortens the channel impulse response (CIR) to mitigate inter-symbol interference (ISI). Melsa, Younce, and Rohrs minimized ISI in the time domain by maximizing the shortening signal-tonoise ratio (SSNR) of the energy in a target window to the energy outside the target window in the shortened CIR. Infinite SSNR means zero ISI. Melsa, Younce, and Rohrs also developed a joint channel shortening method to design a single TEQ to shorten a channel and a near-end echo impulse response. In this paper, we extend the joint SSNR method to design a single TEQ to shorten multiple channels by maximizing the composite SSNR. The composite SSNR is a weighted sum of normalized channel SSNRs. The normalized SSNR is the ratio of the energy in the target window samples to the energy of all samples in the shortened CIR and has a range of [0, 1] so that it is better suited for numerical stability and fixed-point implementation. Our proposed method outperforms the joint channel shortening method. because it achieves higher weighted sum of SSNRs of the used channels.

A Software Defined Radio (SDR) is a radio receiver and/or transmitter, whose characteristics can to a large extent be defined by software. Thus, an SDR can receive and/or transmit a wide variety of signals, supporting many different standards.