Multi-cell coordination is a technique for interference mitigation in cellular systems. For joint-transmission (JT), the received signal power is boosted by diversity combining of signals from multiple transmission points. This however results in reduced frequency-reuse ratio and cell-splitting order, which may subsequently degrade the network-level throughput. In order to strike a balance between the diversity combining gain and frequency-reuse ratio, in this paper we propose a dynamic scheduling algorithm that adaptively schedules users in single-cell or multi-cell transmission mode to maximize the system sum throughput. Furthermore, basestation association for each user is meticulously addressed to avoid negatively impacting the frequency-reuse gain. The proposed algorithm is evaluated with system-level evaluation tools fully compliant with 3GPP LTE specification, thereby providing a realistic assessment on the gain of multi-cell coordination in terms of system capacity and coverage.

Long Term Evolution (LTE) technology aims at addressing the increasing demand for mobile multimedia services in high user density areas. Channel aware scheduling across wide system bandwidth is one of the key techniques enabling this goal. To this end, the LTE scheduler heavily relies on an accurate and robust Link Adaptation (LA) function for predicting the best modulation and coding scheme (MCS) of a user. In this paper, we complement the popular block error rate (BLER) based LA with a scheme maximizing the throughput without BLER constraint and show that it indeed optimizes the spectral efficiency performance. We also describe a sub-optimal UL scheduler providing a good performance/complexity trade-off between a low-complexity basic scheduler and the optimal, but impractical complexity-wise.

The benefits of multiuser diversity for fading chanels are well established in the literature. What is not well documented is the effort required to obtain this CSI information at the scheduler for a frequency division duplex (FDD) system. This paper investigates the practical aspects of the feedback transfer process for a discrete rate-adaptive multiuser system including multi-access, feedback delay and feedback channel imperfections due to fading and additive noise. We compute the optimal power and bandwidth allocated for channel estimation and show that tradeoffs exist between these resources and the number of users depending on the feedback delay. It is also shown that quantization and feedback errors may increase the outage region as the number of users increases. This in effect reduces the multiuser diversity gain expected in ideal feedback channels.

This letter analyzes the performance of an adaptive modulation system, taking into account additive noise and fading on the feedback channel. It is shown that these feedback channel imperfections could significantly degrade the throughput gains of adaptive modulation over nonadaptive transmission. Specifically, feedback errors can result in an outage region in the low signal-to-noise ratio region. Two feedback receivers are proposed: one is based on the finite-state Markov channel model; and the other is a generalized Bayesian receiver. These receivers reduce the outage region due to feedback errors, and they can complement or be used as alternatives to error-control coding schemes.

The paper considers adaptive transmission systems with imperfect feedback channels. It is shown that if the average SNR for the forward channel is known to the transmitter, the feedback detection can be modeled as a classical multiple hypotheses testing problem. Though maximum a posteriori detection is optimal compared to maximum likelihood (in the sense of minimum probability of error) from a feedback communication link viewpoint, the overall effect on adaptive system performance shows that ML detection could be better in the high SNR range. The MAP scheme is generalized to Bayesian detection by defining a cost function matrix, which assigns (unequal) weights to the feedback decision error probabilities. The result is close to ideal bit error rate (BER) performance with only a small drop in spectral efficiency.

In adaptive modulation systems, it is widely assumed that the feedback channel is error-free by employing sophisticated error-control codes and ARQ signaling. However, since feedback is sent over a wireless channel, a heavy price may be paid to justify this assumption. In this paper, we first analyze system performance, given additive noise and fading on the feedback channel. Then, by utilizing the finite-state Markov channel model for a slowly fading Rayleigh channel, we design differential and full-state feedback schemes to correct most of the errors caused by an AWGN channel. For a fading feedback channel, a Markov-based scheme is designed with a threshold level, below which feedback decisions are deemed unreliable. The resulting system performance in terms of the spectral efficiency and bit error rate (BER) is comparable to the ideal case of an error-free feedback channel.

This paper describes a location system using an asynchronous distributed sensor network. The sensors' clocks operate independently and are not explicitly synchronized. The motion of the source, or the object, between two emitted pulses will cause the inter-arrival time of these two pulses at each sensor to vary. This inter-arrival time is a function of the source location and motion and is independent of the clock offsets among sensors. Thus, the independently calculated time-difference-of-arrival (TDOA) of successive pulses at each sensor provides a reliable source of information to estimate the source position as well as its motion. The Cramer-Rao lower bound (CRLB) is derived to assess the performance of the proposed method and to show that its performance can approach that of a synchronous network given a sufficient number of sensors and moderate source movement. Some sub-optimal but effective source trajectory tracking methods are proposed which further relax the assumption of source motion between consecutive pulses. The simulation results show that the proposed estimation and tracking methods are quite good.