An adaptive rate optimization solution is presented to utilize the benefits of multiuser multiple-input multiple-output (MU-MIMO) communications in a wireless network with distributed and decentralized control that adapts to dynamic channel, interference, and traffic conditions. First, the ergodic sum rates of MIMO multiple access channel (MAC) and interference channel (IC) configurations are determined by jointly integrating the error and overhead effects due to channel estimation (training) and feedback into the rate optimization. Then, a distributed channel access protocol that leverages local information without any centralized scheduler is developed to select and activate MU-MIMO configurations with the maximum achievable sum rates depending on channel, interference, and traffic conditions. In a mobile ad hoc network (MANET), MU-MIMO is shown to provide major gains in network throughput (after accounting for the control message overhead) compared with single antenna and point-to-point (P2P) MIMO communications.

Distributed interference cancellation is considered for a single source and multiple collaborative receivers in the presence of multiple unknown interferers. Receivers observe interference in a distributed setting and collaborate to mitigate the common interference from multiple unknown interferers. Under Rayleigh frequency-flat fading conditions, the ergodic capacity is shown to improve with collaboration surpassing the communication overhead due to collaboration. In particular at SINR of -15 dB, the performance improvement relative to the case without collaboration is a factor of 15. Numerical results are also provided for constrained alphabet signaling, along with simulation results based on DVB-S2#x002F;T2 standard. Finally, results from hardware-in-the-loop tests using USRPs are presented to show the feasibility of practical implementation. Both simulation and radio tests demonstrate the benefit of collaboration for distributed cancellation of unknown interference.

We study the performance of cooperative relaying using orthogonal frequency division multiplexing (OFDM) in the presence of frequency offsets due to Doppler shifts and oscillator instabilities. Through this study, several aspects of transmitter and receiver design, including channel coding, subcarrier mapping and channel estimation are brought to light. We develop two linear front-end receiver architectures based on practical single-user OFDM receivers, and demonstrate the performance using simulations under quasi-static multipath fading channel conditions.

We consider the impact of carrier frequency offsets arising naturally when multiple relay terminals transmit simultaneously using a space-time code in a cooperative relaying scenario. In such a scenario, we design an adaptive, low-complexity receiver that attempts to eliminate the effect of frequency offsets. The adaptive receiver allows for decoupling of the decisionmaking of transmitted symbols utilizing the orthogonality of the underlying space-time code. In a quasi-static Rayleigh fading channel, we demonstrate the performance of the adaptive receiver over a range of frequency offsets by considering two transmitting relays. We prove that the adaptive receiver achieves full diversity, and using simulation results for two relays we show that the performance greatly improves over a conventional differential receiver that ignores the presence of frequency offsets.

We address the issue of sum-capacity in an overloaded, uplink, synchronous CDMA system in a quasi-static fading environment. Part of each fading block is reserved for channel training and the remainder of the block is used for data transmission. We evaluate bounds on sum-capacity using the estimates from channel estimation, and consider the effects on the lower bound caused by the spreading-coding-training tradeoff.

The focus of this paper is on training and signature sequence design in an overloaded synchronous CDMA system. The channel fading gains are assumed to be unknown and are estimated using training sequences. We derive a maximum-likelihood (ML) estimator and design sequences to minimize the mean-squared error (MSE) of the estimate. Two design scenarios are considered. One case assumes that the spreading sequences are fixed due to existing system constraints and optimal training sequences are designed using an iterative algorithm in order to minimize the MSE of the estimate. Performance of the iterative algorithm is examined using Welch-bound equality (WBE) sequences as the pre-designed spreading sequences. In the other scenario, spreading sequences and training sequences are designed jointly to minimize the MSE of the estimate. The jointly designed training and spreading sequences achieve optimum performance in the sense of minimizing the MSE. It is observed that when WBE sequences are used as spreading sequences the performance of the iterative algorithm is close to optimum, or even optimum, in certain situations

This work addresses the issue of sum-capacity in an overloaded, uplink, synchronous code-division multiple access (CDMA) system in a quasi-static Rayleigh-fading environment when the receiver does not have a priori knowledge of the fading gains. Part of each fading block is reserved for channel training and the remainder of the block is used for data transmission. Two modes of operation are considered: one in which the users are allowed to update their spreading sequences based on the channel estimates, and one in which their sequences cannot be modified. For both schemes we derive the optimal training scheme and then evaluate a lower bound on sum-capacity. When all the users have the same average received power, we consider the effects on this bound caused by the training-spreading-coding tradeoff.