Jointly Optimal Channel and Power Assignment for Dual-Hop Multi-channel Multi-user Relaying

We consider the problem of jointly optimizing channel pairing, channel-user assignment, and power allocation, to maximize the weighted sum-rate, in a single-relay cooperative system with multiple channels and multiple users. Common relaying strategies are considered, and transmission power constraints are imposed on both individual transmitters and the aggregate over all transmitters. The joint optimization problem naturally leads to a mixed-integer program. Despite the general expectation that such problems are intractable, we construct an efficient algorithm to find an optimal solution, which incurs computational complexity that is polynomial in the number of channels and the number of users. We further demonstrate through numerical experiments that the jointly optimal solution can significantly improve system performance over its suboptimal alternatives.Comment: This is the full version of a paper to appear in the IEEE Journal on Selected Areas in Communications, Special Issue on Cooperative Networking - Challenges and Applications (Part II), October 201

Jointly Optimal Channel Pairing and Power Allocation for Multichannel Multihop Relaying

We study the problem of channel pairing and power allocation in a multichannel multihop relay network to enhance the end-to-end data rate. Both amplify-and-forward (AF) and decode-and-forward (DF) relaying strategies are considered. Given fixed power allocation to the channels, we show that channel pairing over multiple hops can be decomposed into independent pairing problems at each relay, and a sorted-SNR channel pairing strategy is sum-rate optimal, where each relay pairs its incoming and outgoing channels by their SNR order. For the joint optimization of channel pairing and power allocation under both total and individual power constraints, we show that the problem can be decoupled into two subproblems solved separately. This separation principle is established by observing the equivalence between sorting SNRs and sorting channel gains in the jointly optimal solution. It significantly reduces the computational complexity in finding the jointly optimal solution. It follows that the channel pairing problem in joint optimization can be again decomposed into independent pairing problems at each relay based on sorted channel gains. The solution for optimizing power allocation for DF relaying is also provided, as well as an asymptotically optimal solution for AF relaying. Numerical results are provided to demonstrate substantial performance gain of the jointly optimal solution over some suboptimal alternatives. It is also observed that more gain is obtained from optimal channel pairing than optimal power allocation through judiciously exploiting the variation among multiple channels. Impact of the variation of channel gain, the number of channels, and the number of hops on the performance gain is also studied through numerical examples.Comment: 15 pages. IEEE Transactions on Signal Processin

Resource Management in Multi-channel Relaying

Resource management –particularly power and spectrum management– is becoming increasingly important owing to the fast growing market of smart-phones and other power-hungry wireless devices. While WiFi and cellular communication accounts for a significant portion of the smart-phone power expenditure, spectrum is equally paramount and scarce as well. This demands for an efficient and judicious resource management schemes that is also viable in terms of the practical implementation and complexity. This thesis focuses on the various setups of multi-channel relaying system as an emerging wireless technology, and provides rate optimal, yet easy-to-implement, resource management solutions for them. We exploit the channel pairing (CP) capability of a multi-channel relay node in our design. This capability allows the relay to receive a signal from one channel and transmit a processed version of the signal on a different channel. CP jointly optimized with power allocation (PA), which determines each channel’s power, can lead to significant improvement in spectral efficiency. For two setups, namely multi-hop and multi-user setups, we present the total achievable rates through optimizing CP, PA and channel-user assignment which incurs multi-user diversity. While the achievable rates provide theoretical insight for the performance of such systems, we next incorporate the integer nature of bit loading and rate adaptation, and via an innovative optimization technique, we present the jointly optimal solution to the problem of bit loading, PA and CP.Ph

MDS Codes with Progressive Engagement Property for Cloud Storage Systems

Fast and efficient failure recovery is a new challenge for cloud storage systems with a large number of storage nodes. A pivotal recovery metric upon the failure of a storage node is repair bandwidth cost which refers to the amount of data that must be downloaded for regenerating the lost data. Since all the surviving nodes are not always accessible, we intend to introduce a class of maximum distance separable (MDS) codes that can be re-used when the number of selected nodes varies yet yields close to optimal repair bandwidth. Such codes provide flexibility in engaging more surviving nodes in favor of reducing the repair bandwidth without redesigning the code structure and changing the content of the existing nodes. We call this property of MDS codes progressive engagement. This name comes from the fact that if a failure occurs, it is shown that the best strategy is to incrementally engage the surviving nodes according to their accessing cost (delay, number of hops, traffic load or availability in general) until the repair-bandwidth or accessing cost constraints are met. We argue that the existing MDS codes fail to satisfy the progressive engagement property. We subsequently present a search algorithm to find a new set of codes named rotation codes that has both progressive engagement and MDS properties. Furthermore, we illustrate how the existing permutation codes can provide progressive engagement by modifying the original recovery scheme. Simulation results are presented to compare the repair bandwidth performance of such codes when the number of participating nodes varies as well as their speed of single failure recovery