Dennis Hui

Physical-layer issues for deploying transmit diversity in GPRS/EGPRS networks

Lindskog and Paulraj (see ICC-2000, June, 2000) proposed a transmit diversity scheme for dispersive channels which by utilizing two transmit antennas and only one receive antenna achieves the same diversity benefit (except for the 3 dB array gain) as can be achieved by using one transmit antenna and two receive antennas. This scheme generalizes Alamoutis (see IEEE JSAC, vol.16, no.8, p.1451-58, 1998) transmit diversity scheme (which works best for flat channels) to dispersive channels. We show how the transmit diversity (TXD) scheme of Lindskog et al. can be deployed in GPRS/FGPRS networks. A low-complexity receiver structure for demodulating Lindskog and Paulraj (LP) encoded signals is presented based on a combination of a novel pre-filter and a delayed decision feedback sequence estimation (DFSE) equalizer. This pre-filter is designed to simultaneously achieve three desired effects: (1) the effective baseband channel seen by the equalizer has half the number of taps of the original baseband channel; (2) the effective response of the baseband channel becomes minimum-phase; and (3) the effective baseband noise is whitened. An information-theoretic analysis is also presented to demonstrate the advantage of the LP scheme over other TXD schemes (e.g. over delay diversity). A burst format for transmitting LP encoded signals which is compatible with the existing GPRS/EGPRS burst format is also presented. Finally, simulations results are presented to verify the benefit of using the LP scheme in the typical urban channel of GSM/EDGE.

Prefilter design for low-complexity equalization of MIMO systems

We focus on the problem of reduced complexity equalization of multi-input, multi-output (MIMO) systems. In particular, we look at a prefilter design that enables the use of methods such as decision feedback sequence estimation (DFSE) while minimizing the effects of error propagation. We show that a well-known spectral factorization approach can be used to obtain a minimum-phase MIMO prefilter that performs energy compaction well, and thus provides a suitable prefilter. Through simulations on a MIMO system, we compare the performance of the minimum-phase MIMO prefilter with other prefilter approaches that have been published in literature, such as the minimum-mean-square (MMSE) and channel shortening prefilters. The minimum-phase MIMO prefilter outperforms the published approaches. In addition, the minimum-phase MIMO prefilter is less complex to compute.

Classical Channel Estimation for OFDM based on Delay-Doppler Response

In an Orthogonal Frequency Division Multiplexing (OFDM) system, the channel is often modeled as a two-dimensional zero-mean Gaussian random process in time and frequency with known second order statistics. With pilot symbols placed across the time-frequency plane, the channels response at a particular time-frequency point can be derived from its correlation with the nearby pilot locations. However, this a priori channel statistics may not always be available or the channel may not even be stationary to be adequately characterized by a correlation function. In this paper, we introduce a model of time-varying channel based on its delay-Doppler response. We show that a widely adopted time-frequency correlation model, upon which popular channel estimators for OFDM are often based, can be viewed as a special case of such a model with separable statistical profiles imposed on the delay-Doppler plane. Without using any statistical assumption on the channel, we derive a classical estimator based on the two-dimensional delay- Doppler correlator, which can be implemented using Discrete Fourier Transforms (DFT) of the pilot symbol measurements. Simulation results show promising performance even when the pilot symbols insertion rate is at the channels maximum delay-Doppler spread.

Impact of Transmit Array Geometry on Downlink System-Level Performance of MIMO Systems

For a cellular system with a fixed number of transmit antennas at each base station, we investigate how the system-level performance varies as a function of the geometry of the transmit array used at each base station. Our results show that the system-level performance of a cellular system can be significantly improved by using transmit antenna geometries other than the uniform linear arrays that have been investigated extensively in the literature so far. For example with 4 transmit antennas at each base station, we show that the spectral efficiency for achieving a 5 percentile user data rate of 2 Mbps (in a 5 MHz bandwidth) is improved by 58% when a non-uniform, linear array is used instead of a traditional uniform linear array.

Interference mitigation for MIMO systems employing user-specific, linear precoding

User-specific, linear precoding is used extensively by almost all existing and emerging wireless MIMO standards [1], [2], [3], [4]. With user-specific, linear precoding, the data symbols to be transmitted to each user are passed through a linear transformation before being sent to the transmit antennas, and a different precoder is used for each user depending on his/her channel. For example, with 4 transmit antennas at the BS, 2 receive antennas at the mobile, and instant channel quality indicator (CQI), the cell capacity of a 4times2 2-clustered system with user-specific, linear precoding is more than 80% higher than the cell capacity of a system with one transmit antenna [10]. But such schemes are vulnerable to delayed CQI due to fast variations of interference, leading in some cases to performance that is worse than a SISO system. In this paper, we will present a method that mitigates the degradation due to fast-varying interference in MIMO systems that use linear precoding. We will show that the temporal variation of other-cell interference is almost eliminated with this method. Our results indicate that for a 4times2 2-Clustered transmit array with the proposed method, the performance loss due to delayed CQI is reduced from 35% to 5%.

Millimeter wave communications

Certain 5G METIS scenarios [1] such as Amazingly Fast, Best Experience Follows You , and Service in a Crowd create extreme requirements on data rate, traffic handling capability, and availability of high capacity transport respectively. These scenarios map to corresponding requirements that will entail support of over 10 Gbps, 10–100 times the number of connected devices, 1000 times the traffic, and 5 times lower end-to-end latency than possible through IMT-Advanced. The peak data rate requirements of these scenarios will entail acquisition of several hundreds of MHz of spectrum. These requirements do not encompass 5G, but instead offer one avenue of stressing system capabilities along a limited set of dimensions. Several traffic forecasts [2][3] also predict a tenfold increase in traffic volume from 2015 to 2020. The 5G requirements of interest to this chapter relate mainly to data rates and traffic volumes and can be met using techniques that are tried and tested in past generations of mobile networks. These are to (1) gain access to new spectrum, (2) improve spectral efficiency, and (3) densify the networks using small cells. In the case of 5G, these techniques are given new life using two means: the use of millimeter Wave (mmW) spectrum for the availability of large blocks of contiguous spectrum, and the subsequent adoption of beamforming as an enabler for high spectrum efficiency. The propagation of millimeter waves is naturally affected by physics to reduce coverage to shorter ranges. Ultra-Dense Network (UDN) deployments are therefore a consequence of the choice of frequency band, and will lead to a tremendous increase in capacity over the covered area. The increase in spectral efficiency arises out of the drastic reduction of interference in relation to signal power due to the high gain beamforming. Spectrum and regulations The primary motivation for using millimeter waves is the promise of abundant spectrum above 30 GHz. While mmW spectrum spans the range from 30 GHz–300 GHz, it is widely believed that the reach of mass market semiconductor technology extends up to around 100 GHz and will inevitably surpass that limit with time. Microwave bands from 3 GHz–30 GHz are just as relevant to meeting extreme requirements for 5G, and much of the discussion in this chapter is relevant to those parts of the centimeter Wave (cmW) band outside of the reach of existing systems as well, namely the region 10 GHz–30 GHz (see Figure 6.1).

Single Antenna Interference Cancellation for 8PSK Signals in EGPRS

In this paper, we explore a method for interference suppression in EGPRS (also commonly known as EDGE) systems, wherein 8PSK is used as the modulation for the desired signal and the interferer is modulated using GMSK. Previous methods for single antenna interference cancellation (SAIC) have concentrated on the case when both the desired and interfering signals are GMSK modulated, or have relied on highly complex methods such as joint demodulation. We derive a simple method that exploits the redundancy inherent in the interferer signal to suppress it. The interference suppression method causes a well- modeled nonlinear distortion to the 8PSK signal. This non-linear distortion is handled using a modified equalizer that deals with a time-varying input symbol constellation applied to a matrix channel. Simulation results using the method show great promise.

Blind DC Estimation in the Presence of Non-Gaussian Signal

A method of estimating DC offset based solely on the received signal, without using any training information, is presented. This method takes into account the non-Gaussian statistical distribution of the modulated desired signal in order to produce a DC estimate that is more accurate than the conventional sample average of the received signal. Specifically, two iterative algorithms are derived based on the generalized expectation-maximization algorithms for jointly estimating the DC offset, the noise variance, and the parameters that characterize the signal distribution. As an application, we consider the special case where the modulated signal has a constant-envelope characteristic. Using the GSM/EDGE air interface, we demonstrate that the proposed method yields significant reduction in the DC-offset estimation error, which translates into performance gains in receiver sensitivity when used in direct-conversion receivers.

Turing complexity of fixed-rate quantization

The rate of increase of quantization complexity, as the rate of quantization increases, is investigated under a Turing machine framework. It is shown that the problem of asymptotically optimal scalar quantization has polynomial encoding complexity if the distribution function corresponding to the one-third power of the source density is polynomially computable with high probability.