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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]

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]

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]

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]