Transceiver design for wireless downlink channels with multiple antennas

Jianqi Wang, Purdue University

Abstract

We propose a generalized greedy (G-greedy) algorithm based on zero-forcing beamforming (ZFBF) for the multiple-input multiple-output (MIMO) broadcast channel. This algorithm serves as a general mathematical framework that includes a number of existing greedy user selection methods as its realizations. As previous results only give the scaling law of the sum rate of dirty paper coding (DPC), with the help of the G-greedy structure, we are able to obtain the exact limit of the DPC sum rate for a large number of users. We also prove that the difference between the sum rates obtained by G-greedy user selection and by DPC goes to zero as the number number of users increases. In addition to this, we investigate one particular greedy user selection scheme called sequential water-filling (SWF). For this algorithm, a complexity reduction is achieved by an iterative procedure based on an LQ decomposition, which converts the calculation of the Moore-Penrose matrix inverse to one vector-matrix multiplication. A sufficient condition is given to prune the search space of this algorithm that results in further complexity reduction. With the help of the G-greedy algorithm, we prove that SWF achieves the full DPC sum rate for a large number of users. For a moderate number of users, simulation demonstrates that, compared with other user selection algorithms, SWF achieves a higher sum rate that is close to the maximal sum rate achievable by ZFBF with the same order of complexity. For common information broadcast, we present a hybrid automatic repeat request (ARQ) scheme with incremental redundancy channel coding and the packet retransmission. With this scheme, we can reliably deliver the same copy of information to different users with mild delay. In addition, the design of the feedback channel for this scheme can be greatly simplified as no efforts must be expended to combat the cross user interference. Three specific schemes are studied, including the generalized slotted ALOHA (GSA), the repetition time diversity (RTD), and the general incremental redundancy (INR). Specifically, let K be the number of users. When the rate per packet is finite, the average delay scales as Θ(log K) for all three schemes where only a finite number of previously received packets are used for decoding. As a consequence, the average throughput scales as Θ( K/log K). In addition, when we increase the rate per packet linearly with K, we can obtain a linear scaling for both the throughput and the delay with respect to K. Since every user can achieve no more than the ergodic capacity, we actually achieve the optimal scaling law at this case.

Degree

Ph.D.

Advisors

Love, Purdue University.

Subject Area

Electrical engineering

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