Position estimation (geolocation) of a direct-sequence, spread-spectrum radio emitter is particularly challenging because of low signal-to-noise ratio at the radio sensors. In this letter, we develop a maximum-likelihood approach to geolocation that utilizes knowledge of the spreading sequence. Simulation results are used to show that spreading sequence knowledge can provide significant gains in position accuracy.

Coordinated multi-point (CoMP) transmission is a general method for mitigating the inter-cell interference in a cellular network through the use of multi-user precoding across neighboring base stations. In this paper, we investigate the system performance of MMSE-based multi-user precoding in a cellular network with CoMP transmission. An iterative algorithm that exploits the duality between the downlink broadcast channel and the uplink multi-access channel is used to compute the multi-user precoding matrices. The algorithm uses the knowledge of the channel error covariance during the precoder computation to alleviate the impact of channel uncertainty at the network. We simulate the system performance of various MMSE-based precoders under the CoMP setting using a realistic MIMO channel model and compare them with those of the zero-forcing precoders. We show that the error-compensated MMSE precoder is more robust towards channel uncertainty and can significantly outperform zero-forcing precoding at high loads.

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%.

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.

This paper provides a high-level overview of some technology components currently considered for the evolution of LTE including complete fulfillment of the IMT-advanced requirements. These technology components include extended spectrum flexibility, multi-antenna solutions, coordinated multipoint transmission/reception, and the use of advanced repeaters/relaying. A simple performance assessment is also included, indicating potential for significantly increased performance.

For a cellular system with a fixed number of transmit antennas at each base station, we investigate how the data rate on the downlink varies as a joint function of the geometry of the transmit array and the linear precoding that precedes the transmit array. The maximum average data rate that can be reliably transmitted over the downlink channel (i.e. the ergodic capacity of the downlink channel) is used in this paper to compare various configurations of transmit antennas at the base stations. Using the 3GPP Spatial Channel Models [4] for a macro-cellular environment, we find the optimum configuration of transmit antennas with a total of 2 or a total of 4 transmit antennas at various SNRs. We offer guidelines for choosing the best transmit antenna geometry for different SNR regions.

In this paper, we focus on a cellular system with M transmit antennas at the base station (BTS) and one receive antenna at the mobile (i.e. an M-input/single-output (MISO) channel), where the BTS commands each mobile to transmit its channel state information back to the BTS. Our main result is a specific method for each mobile to use the uplink channel to inform the BTS of the state of its M downlink channels. This feedback method is particularly well-suited for wireless packet data cellular systems on the downlink where the entire downlink channel is allocated to one downlink user at a time (e.g. a cellular packet data system employing proportional fairness type scheduling on the downlink). We show that with a small portion of uplink channel resources devoted to feedback of channel state information per site, our feedback method results in a performance very close (within 1dB) to the performance that can be obtained with perfect channel knowledge at the BTS.

We focus on data transmission over continuous-time, dispersive M-input/single-output (MISO) channels where the transmitter knows all M channels. The biorthogonal Karhunen-Loeve (KL) expansion in the continuous-time domain is proposed as a unifying analytical framework for studying dispersive MISO channels. Using this KL expansion, we rigorously derive an expression for the capacity of the continuous-time dispersive MISO channel and show that a dispersive MISO channel is equivalent, in terms of channel capacity, to a dispersive single-input/multiple-output (SIMO) channel. Our derivations based on the KL expansion avoid the well-known problems associated with the "frequency splitting" approach. We show that the capacity-achieving transmitter for a dispersive MISO channel can be broken into two parts: (1) an optimal encoder for a dispersive single-input/single-output (SISO) channel and (2) an M-dimensional (M-D) matched filter (or a broadband beamformer). The M-D matched filter turns the original dispersive MISO channel into an equivalent SISO channel with exactly the same capacity as the capacity of the original MISO channel, and the one-dimensional encoder is just the well-known optimal encoder of Gallager for this equivalent SISO channel created by the M-D matched filter. As the number of transmit antennas increases, we show that the channel seen by the receiver approaches a flat-fading SISO channel (even when the individual forward channels are dispersive); hence, water filling in the transmitter can be dropped without much degradation. Second, this shows that with a large number of transmit antennas, the achievable data rate using a pre-RAKE at the transmitter and a very simple symbol-by-symbol detector at the receiver is quite close to the actual capacity of the dispersive MISO channel. With a large number of transmit antennas, this implies that the receiver for a capacity-achieving dispersive MISO system can be considerably less complex than the receiver for a dispersive SISO channel.

We focus on transmit diversity schemes for a communication system with M transmit antennas and one receive antenna (i.e. an M-input/single-output (MISO) system) where the transmitter knows all these M channels, and we derive a transmission scheme that maximizes the data rate, in an information-theoretic sense, that can be reliably transmitted over this MISO channel. An important example of the type of system we consider is a cellular wireless system on the downlink with M transmit antennas at the base station and one receive antenna at the mobile station. Our main result is the identification of the structure of the capacity-achieving transmitter. The capacity-achieving transmitter can be broken into two parts: (I) an optimal encoder for a single-input/single-output (SISO) channel, and (II) an M-dimensional matched filter. We show that the M-dimensional matched filter turns the original MISO channel into a SISO channel with exactly the same capacity as the capacity of the original MISO channel, and the 1-dimensional encoder is just the well known optimal encoder of Gallager (1966) for the SISO channel created by the M-dimensional matched filter. We also derive a closed-form expression for the channel capacity of MISO channels which is valid under a rather general set of assumptions: (1) each channel can be dispersive or flat, and (2) the additive noise at the receiver can be a Gaussian process with arbitrary power spectrum. In a typical urban environment, to achieve 1% block error rate at 4 Mbits/second, the MISO system with our transmission scheme requires 10 dB less SNR than today's SISO system.

A receiver that adapts to the second-order statistics of the disturbance (interference or noise) is presented. By adapting to the statistics of the disturbance, this receiver produces the maximum-likelihood (ML) estimate of the transmitted sequence for any type of disturbance, in contrast to a conventional receiver that only produces the ML estimate when the discrete-time disturbance is white. This disturbance signal could result from (1) cochannel interference, (2) adjacent-channel interference or (3) thermal noise. The proposed receiver consists of a Nyquist analog receive filter and an adaptive maximum-likelihood sequence estimator for colored noise. We show that the samples of the output of this analog receive filter, at one sample per symbol, are sufficient statistics for finding the most likely transmitted sequence regardless of the type of disturbance present at the input to the receiver. An important feature of this adaptive receiver is that the analog part of the this receiver is fixed, i.e. adaption to the statistics of the disturbance is accomplished by processing in the digital domain only (at one sample per symbol). Using the EGPRS air interface as an example, we show that this adaptive receiver performs substantially better than a conventional non-adaptive receiver: (1) cochannel dominated case: 4.0 dB of gain, (2) adjacent-channel dominated case: 3.5 dB of gain, (3) thermal-noise dominated case: 1.2 dB of gain.

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 Alamouti's (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.

The use of the "software radio" concept in cellular applications is a topic of widespread interest. Two key issues in the implementation of software radios are the development of optimal receivers that require the minimum number of bits in the wide-band analog-to-digital converter (ADC) and efficient channelizers that extract individual channels from the digitized wide-band signal. In this paper, both of these issues are studied in detail for cellular base stations. A computationally efficient wide-band channelizer is presented. This channelizer is closely related to the discrete Fourier transform filter bank used in transmultiplexers. It is shown that the complexity of the proposed channelizer is significantly less (2-50/spl times/) than the complexity of conventional channelizers. An optimal receiver that explicitly takes into account the effect of the quantization noise of the wide-band ADC is also derived. The analysis of the ADC noise provides guidelines for specifying wide-band ADC for use in cellular applications. The development of the channelizer and the optimal receiver yield important insights into the implementation of cellular software radios. All of the key results of this paper are applied to a detailed example based on the Digital Advanced Mobile Phone System (D-AMPS, IS-54/IS-136) cellular standard. The bit-error rate (BER) performance simulations of a D-AMPS wide band receiver is presented as a part of this example.

For cellular software radio receivers, this paper presents a computationally efficient algorithm for extracting individual radio channels from the output of the wideband A/D converter. In a software radio, the extraction of individual channels from the output of the wideband A/D converter is by far the most computationally demanding task; hence, it is very important to devise computationally efficient algorithms for this task. Our algorithm is obtained by modifying the DFT filter bank structure that is well known in the multi-rate signal processing literature. We show that the complexity of the proposed algorithm is significantly less (2X-50X) than the complexity of the conventional channelizers.

For cellular software radio receivers, this paper presents a computationally efficient algorithm for extracting individual radio channels from the output of the wideband A/D converter. In a software radio, the extraction of individual channels from the output of the wide band A/D converter is by far the most computationally demanding task; hence, it is very important to devise computationally efficient algorithms for this task. Our algorithm is obtained by modifying the DFT filter bank structure that is well known in the multi-rate signal processing literature (Scheuermann and Gockler, 1981; Vaidyanathan, 1990). We show that the complexity of the proposed algorithm is significantly less (2/spl times/-50/spl times/) than the complexity of the conventional channelizers.

Active noise cancellation is an approach to noise reduction in which a secondary noise source that destructively interferes with the unwanted noise is introduced. In general, active noise cancellation systems rely on multiple sensors to measure the unwanted noise field and the effect of the cancellation. This paper develops an approach that utilizes a single sensor. The noise field is modeled as a stochastic process, and a time-adaptive algorithm is used to adaptively estimate the parameters of the process. Based on these parameter estimates, a canceling signal is generated. In general, the transfer function characteristics from the canceling source to the error sensor need to be accounted for. If these can be accurately measured in advance and are invertible except for the propagation delay between the source and sensor, then the essential problem becomes one of predicting future values of the noise field. The algorithm developed is evaluated with both artificially generated noise and with recordings of aircraft noise.>

The authors develop an approach to active noise cancellation using a single microphone. The noise field is modelled as a stochastic process, and a time-adaptive algorithm based on a modification of the block-estimate-maximize (EM) algorithm is used to adaptively estimate the parameters of this process. Based on these parameter estimates a canceling signal is generated. The algorithm developed is evaluated with recordings of aircraft noise, and has been implemented in real time with a single AT&T DSP32C chip.>