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For rate optimization in interference limited networks, improper Gaussian signaling has shown its ability to outperform conventional proper Gaussian signaling. In this paper, we study a weighted sum-rate maximization problem with improper Gaussian signaling for the multiple-input multiple-output interference broadcast channel. To solve this nonconvex and NP-hard problem, we propose an effective separate covariance and pseudo-covariance matrices optimization algorithm. In the covariance optimization, a weighted minimum mean square error algorithm is adopted, and in the pseudo-covariance optimization, an alternating optimization (AO) algorithm is proposed, which guarantees convergence to a stationary solution and ensures a sum-rate improvement over proper Gaussian signaling. An alternating direction method of multipliers-based multi-agent distributed algorithm is proposed to solve an AO subproblem with the globally optimal solution in a parallel and scalable fashion. The proposed scheme exhibits favorable convergence, optimality, and complexity properties for future large-scale networks. The simulation results demonstrate the superior sum-rate performance of the proposed algorithm as compared with the existing schemes with proper as well as improper Gaussian signaling under various network configurations. [ABSTRACT FROM AUTHOR]

In this paper, system design for a multiple-input–multiple-output (MIMO) relay broadcast channel with individual signal-to-interference-plus-noise ratio (SINR) constraints at mobile stations (MSs) is considered. By exploring the structure of downlink–uplink duality at either the base station (BS) or the relay station (RS), we propose two schemes of joint power allocation and beamforming design at the BS and the RS. The problem of the existence of feasible solutions under practical power constraints at the BS and the RS with given SINR targets is considered first. Then, the problem of sum power minimization is considered. Each design problem can be efficiently solved using optimal joint power allocation and beamforming under the framework of convex optimization. We also show that with subchannel pairing at the RS, the transmission power can be further reduced. Finally, a generalization to the multihop scenario is provided to further improve power efficiency. [ABSTRACT FROM PUBLISHER]

For the multiuser multiple-input multiple-output downlink channel, users feedback their channel state information to help base station schedule users and improve system sum rate. This incurs a large aggregate feedback bandwidth which grows linearly with the number of users. In this paper, we propose a novel scheme to reduce feedback load in a scheduled downlink orthogonal beamforming system by allowing users to opportunistically determine the number of feedback bits to use according to multiple decision thresholds. Through theoretical analysis, we show that, while keeping the aggregate feedback load of the entire system constant regardless of the number of users, the proposed scheme almost achieves the optimal asymptotic sum rate scaling with respect to the number of users (i.e., the multiuser diversity). Specifically, given the number of thresholds, the proposed scheme can achieve a constant portion of the optimal sum rate achievable by the system in which all the users always feedback, and the remaining portion (i.e., the sum rate loss) decreases exponentially to zero as the number of thresholds increases. We further consider feedback design by minimizing the number of thresholds and allocating quantization bits. Simulation shows that the proposed scheme can reduce feedback load and utilize limited feedback bandwidth more effectively than the existing feedback methods. [ABSTRACT FROM PUBLISHER]

In this paper, we analytically study a random access network that uses the request-to-send and clear-to-send (RTS/CTS) handshake for reservation of transmission time. In the network, nodes initiate data transmission to a common base station (BS) by sending an RTS packet according to a transmission probability. The RTS packet of a node specifies the length of the node's requested data transmission interval, and will be successfully received by the BS if its signal to interference plus noise ratio (SINR) is higher than the capture ratio. The BS will then reply with a CTS packet to grant this node the requested data transmission interval and inform the other nodes not to interrupt. The transmission probabilities of RTS packets of all nodes will determine the average throughput and power consumption of each node. The set of all possible throughputs that can be achieved by the network is called the throughput region. We characterize the throughput region and provide an upper bound on the total transmission power consumption over the throughput region at the optimal operating point. Specifically, the upper bound corresponds to one of three points in the throughput region depending on the fraction of time occupied by the RTS packets. [ABSTRACT FROM PUBLISHER]

In this work, we consider an interference-mitigation based cognitive radio system where a secondary transmitter is to communicate with its corresponding receiver without affecting the communication between a primary transmitter-receiver pair. In this case, the secondary transmitter must satisfy a coexistence constraint which requires that no rate degradation occurs at the primary user (PU), even when the latter utilizes only a single-user decoder. To achieve a non-zero rate of the secondary user (SU) under this constraint, Jovicic and Viswanath previously proposed a scheme (referred to as the JV scheme) that utilizes relaying by the secondary transmitter to overcome the interference caused by the simultaneous transmission of the SU's message. In this case, the interference caused by the signals corresponding to PU's message at the secondary receiver (from both the direct and the relay links) is mitigated by employing dirty paper coding (DPC) at the secondary transmitter. However, the interference caused by the SU's message at the primary receiver is not eliminated in this case and, thus, will limit the power (and, hence, the rate) that can be used by the secondary transmitter to transmit its own message. In our work, the use of clean relaying by the secondary transmitter and/or receiver (i.e., relaying without simultaneous transmission of SU's own message) is proposed to improve the quality of the relayed signal and, thereby, increases the rate achievable by the SU. Two improved transmission schemes are proposed: (i) clean relaying by secondary transmitter (CT) and (ii) clean relaying by secondary transmitter and receiver (CTR). The CT scheme utilizes DPC to mitigate interference at the secondary receiver whereas the CTR scheme utilizes coding for multiple access channels with common messages to enable decoding of both PU's and SU's messages at the secondary receiver. The CT scheme can be viewed as a generalization of the JV scheme and, therefore, performs at least as well as the latter. The CTR scheme, on the other hand, is shown to outperform the CT scheme in terms of the multiplexing gain achievable under full channel state information at the transmitter (CSIT) and in terms of the rate achievable with statistical CSIT. Numerical simulations are provided to illustrate these advantages. [ABSTRACT FROM PUBLISHER]

In this paper, we aim to solve the multiuser multi-input multi-output (MIMO) downlink beamforming problem where one multi-antenna base station broadcasts data to many users. Each user is assigned multiple data streams and has multiple antennas at its receiver. Efficient solutions to the joint transmit-receive beamforming and power allocation problem based on iterative methods are proposed. We adopt the group maximum signal-to-interference-plus-noise-ratio (SINR) filter bank (GSINR-FB) as our beamformer which exploits receiver diversity through cooperation between the data streams of a user. The data streams for each user are subject to an average SINR constraint, which has many important applications in wireless communication systems and serves as a good metric to measure the quality of service (QoS). The GSINR-FB also optimizes the average SINR of its output. Based on the GSINR-FB beamformer, we find an SINR balancing structure for optimal power allocation which simplifies the complicated power allocation problem to a linear one. Simulation results verify the superiority of the proposed algorithms over previous works with approximately the same complexity. [ABSTRACT FROM PUBLISHER]

The Nash equilibrium point of the transmission probabilities in a slotted ALOHA system with selfish nodes is analyzed. The system consists of a finite number of heterogeneous nodes, each trying to minimize its average transmission probability (or power investment) selfishly while meeting its average throughput demand over the shared wireless channel to a common base station (BS). We use a game-theoretic approach to analyze the network under two reception models: one is called power capture, the other is called signal-to-interference-plus-noise ratio (SINR) capture. It is shown that, in some situations, Braess-like paradoxes may occur. That is, the performance of the system may become worse instead of better when channel state information (CSI) is available at the selfish nodes. In particular, for homogeneous nodes, we analytically presented that Braess-like paradoxes occur in the power capture model, and in the SINR capture model with the capture ratio larger than one and the noise to signal ratio sufficiently small. [ABSTRACT FROM AUTHOR]