Dragan Samardzija

Demand responsive pricing and competitive spectrum allocation via a spectrum server

In this paper we develop a framework for competition of future operators likely to operate in a mixed commons/property-rights regime under the regulation of a spectrum policy server (SPS). The operators dynamically compete for customers as well as portions of available spectrum. The operators are charged by the SPS for the amount of bandwidth they use in their services. Through demand responsive pricing, the operators try to come up with convincing service offers for the customers, while trying to maximize their profits. We first consider a single-user system as an illustrative example. We formulate the competition between the operators as a non-cooperative game and propose an SPS-based iterative bidding scheme that results in a Nash equilibrium of the game. Numerical results suggest that, competition increases the users (customers) acceptance probability of the offered service, while reducing the profits achieved by the operators. It is also observed that as the cost of unit bandwidth increases relative to the cost of unit infrastructure (fixed cost), the operator with superior technology (higher fixed cost) becomes more competitive. We then extend the framework to a multiuser setting where the operators are competing for a number of users at once. We propose an SPS-based bandwidth allocation scheme in which the SPS optimally allocates bandwidth portions for each user-operator session to maximize its overall expected revenue resulting from the operator payments. Comparison of the performance of this scheme to one in which the bandwidth is equally shared between the user-operator pairs reveals that such an SPS-based scheme improves the user acceptance probabilities and the bandwidth utilization in multiuser systems

Prototype experience for MIMO BLAST over third-generation wireless system

In this paper, a multiple-input-multiple-output (MIMO) extension for a third-generation (3G) wireless system is described. The integration of MIMO concepts within the existing UMTS standard and the associated space-time RAKE receiver are explained. An analysis is followed by a description of an actual experimental MIMO transmitter and receiver architecture, both realized on digital signal processors (DSPs) and FPGAs within a precommercial OneBTS base station. It uses four transmit and four receive antennas to achieve downlink data rates up to 1 Mb/s per user with a spreading factor of 32 and the UMTS chip rate of 3.84 MHz. Furthermore, different MIMO detectors are evaluated, comparing their performance and complexity. System performance is evaluated through simulations and indoor over-the-air measurements. Capacity and bit-error rate measurement results are presented.

Pilot-assisted estimation of MIMO fading channel response and achievable data rates

We analyze the effects of pilot-assisted channel estimation on achievable data rates (lower bound on information capacity) over a frequency flat time-varying channel. Under a block-fading channel model, the effects of the estimation error are evaluated in the case of the estimates being available at the receiver only (open loop) and in the case when the estimates are fed back to the transmitter allowing water pouring transmitter optimization (closed loop). Using a characterization of the effective noise due to estimation error, we analyze the achievable rates as a function of the power allocated to the pilot, the channel coherence time, the background noise level, as well as the number of transmit and receive antennas. The analysis presented here can be used to optimally allocate pilot power for various system and channel operating conditions, and to also determine the effectiveness of closed loop feedback.

Compressed Transport of Baseband Signals in Radio Access Networks

In current wireless base station solutions it is becoming common to physically separate baseband units and radio subsystems. In many wireless technologies this architecture requires allocation of significant transport network resources. In this paper a low-latency baseband signal compression scheme is presented. The compression scheme significantly lowers the transport data rate while maintaining low levels of signal distortion, thus resulting in a lower-cost transport network. Considering the importance of packet-based networks, a number of additional novel compression schemes are proposed. They are optimized for transport networks that implement a quality-of-service (QoS) mechanism and/or multi-link transmission. The compression schemes are parameterized such that a smooth trade-off between the required signal quality and compression performance can be achieved through operator choice of the suitable parameter values. An attractive feature of these schemes is that they can be applied to different wireless technologies, with appropriate parameter settings, without disrupting the present architecture. The proposed solutions will lead to a cost-effective implementation of collocated and distributed network-centric baseband processing, coordinated multi-point (CoMP) and/or distributed antenna system (DAS) which are critical topics for the entire wireless telecommunications industry and infrastructure.

LTE/LTE-A signal compression on the CPRI interface

The Centralized, Cooperative, Cloud Radio Access Network (C-RAN) is a next-generation wireless access network architecture based on centralized processing, collaborative radio, and real time cloud infrastructure. In this architecture, different access technologies (Global System for Mobile Communications (GSM)/Time Division Synchronous Code Division Multiple Access (TD-SCDMA)/Wideband Code Division Multiple Access (WCDMA)/Long Term Evolution (LTE)) can be supported on the same hardware platform in a baseband pool system, which can largely reduce system costs. Long Term Evolution (LTE) and Long Term Evolution-Advanced (LTE-A), which are based on Orthogonal Frequency Division Multiplexing (OFDM) and multiple input multiple output (MIMO) technologies, are regarded as the main wireless access technologies in the evolution from 3G to 4G. A variety of novel technologies such as multi-antenna MIMO, carrier aggregation (CA), and coordinated multipoint have been introduced in LTE/LTE-A to improve system performance, especially in the C-RAN architecture. However, one of the technical challenges for the C-RAN architecture is the fiber bandwidth required for data transmission between the remote radio unit (RRU) and the baseband unit (BBU). We propose using a low-latency baseband signal compression algorithm to solve this problem by reducing the fiber data rate. Using the characteristics of the LTE signal data, we remove the redundancy in the spectral domain. We also leverage block scaling in conjunction with using a linear or nonlinear (non-uniform) quantizer to minimize quantization error. This algorithm effectively reduces the amount of data transmitted between the BBU and RRU, and facilitates the deployment of LTE in the C-RAN architecture. We verified the robustness of the algorithm via simulations and lab tests. The proposed algorithm yields good system performance at a 1/2 compression rate and at a 1/3 compression rate in a practical propagation environment.

Unquantized and uncoded channel state information feedback in multiple-antenna multiuser systems

We propose a channel state information (CSI) feedback scheme based on unquantized and uncoded (UQ-UC) transmission. We consider a system where a mobile terminal obtains the downlink CSI and feeds it back to the base station using an uplink feedback channel. If the downlink channel is an independent Rayleigh fading channel, then the CSI may be viewed as an output of a complex independent identically distributed Gaussian source. Further, if the uplink feedback channel is an additive white Gaussian noise channel, and the downlink CSI is perfectly known at the mobile terminal, it can be shown that UQ-UC CSI transmission (that incurs zero delay) is optimal in that it achieves the same minimum mean-squared error distortion as a scheme that optimally (in the Shannon sense) quantizes and encodes the CSI, while theoretically incurring infinite delay. Since the UQ-UC transmission is suboptimal on correlated wireless channels, we propose a simple linear CSI feedback receiver that can be used to improve the performance of UQ-UC transmission while still retaining the attractive zero-delay feature. We provide bounds on the performance of such UQ-UC CSI feedback and study its impact on the achievable information rates. Furthermore, we explore its application and performance in multiple-antenna multiuser wireless systems, and also propose a corresponding pilot-assisted channel-state estimation scheme

Doppler radar sensing of multiple subjects in single and multiple antenna systems

Doppler radar life sensing has shown promise in medical and security applications, however the problems of motion artifacts and presence of multiple subjects limit the usefulness of this technique. By leveraging recent advances in signal processing and wireless communications technologies, the Doppler radar technique has the potential to overcome these limitations. We explore the single and multiple antenna systems and SIMO/MIMO signal processing to isolate desired radar return signals from multiple subjects. It has been experimentally demonstrated that up to two subjects can be separated in a single antenna systems. Simulations have also shown that in case two subjects have identical cardiovascular behavior, it is possible to distinguish them using MIMO techniques.

Performance evaluation of the VBLAST algorithm in W-CDMA systems

We evaluate the performance of the VBLAST (vertical Bell Labs layered space-time) receiver algorithm in multiple-transmitter/multiple-receiver (MTMR) cellular W-CDMA systems. We assume that the VBLAST algorithm is executed on a symbol level (i.e., on the despread received signal), following a conventional bank of matched filters (correlators). Also, we introduce the concept of virtual antennas. Performance of the algorithm in the presence of intra- and inter-cell multiple-access interference (MAI) is evaluated. System capacity is also studied. The observed system is defined based on the UMTS physical layer and corresponding channel models.

Multiple antenna transmitter optimization schemes for multiuser systems

We present multiple antenna transmitter optimization (i.e., spatial prefiltering) schemes that are based on linear transformations and transmit power optimization (keeping average transmit power conserved). We consider the downlink of a wireless system with multiple transmit antennas at the base station and a number of mobile terminals (i.e., users) each with a single receive antenna. We consider the maximum achievable data rates in the case of the zero-forcing and triangularization spatial prefiltering coupled with a dirty paper coding transmission scheme. We also present the effects of channel mismatch.

Increasing throughput in cellular networks with higher-order sectorization

We study the impact of higher-order sectorization (up to 12 sectors per cell site) in cellular networks with low angle spread and a high density of users. Under ideal sector patterns (with no intersector interference), the mean throughput per site scales directly with S, the number of sectors per site. Fixing the number of antennas per site to be 12, higher-order sectorization with S = 12 and single-antenna transmission per sector is shown to achieve higher average throughput compared to a conventionally sectorized system with S = 3 and capacity-achieving multiuser MIMO transmission with M = 4 antennas per sector. A circular antenna array architecture is proposed for generating S = 12 sectors using fixed beamforming. Beams generated using an array prototype were measured in an anechoic chamber were shown to achieve a similar response as the one used in simulations, and the wind load improvement is a factor of 8 compared to the S = 3, M = 4 configuration.