Abstract-We analyze the ergodic capacity and capacity bound of a multiple-input-multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) system suffering from frequency-selective in-phase and quadrature-phase (IQ) imbalances along with residual carrier frequency offset (CFO). In the literature, capacity analysis of systems with IQ imbalance has been done only for the single antenna case and has considered either frequency-flat IQ imbalances at both transmitter and receiver sides without CFO or only receiver-side IQ imbalances with CFO. Additionally, these works dealt with IQ imbalance by treating the mirror tone interference as an additional source of noise, which is not optimal. In this paper, we consider a generalized system model that includes a multiantenna system with frequencyselective IQ imbalances at both the transmitter and the receiver sides, in addition to the presence of CFO, and perform capacity analysis considering joint detection of the signal and its selfinterference. In addition, for the imperfect channel estimation case, existing works in the literature optimize for pilot spacings and pilot designs. Pilot-data power allocation is an additional degree of freedom that is available to further optimize the system and has not been addressed before. Therefore, we analyze the pilot-data power allocation that maximizes the capacity bound and obtain a closed-form solution for the optimal power allocation at high signal-to-noise ratio (SNR) regime. We then study how the IQ imbalance and residual CFO severity affect capacity, symbol error rate (SER), and capacity bound maximizing power allocation. Finally, we derive the optimal power allocation when the channel is slow varying and remains constant over a block of several OFDM symbols. The derived results are validated through Monte Carlo simulations.Index Terms-Carrier frequency offset (CFO), channel estimation, correlated multiple input-multiple output (MIMO), in-phase and quadrature-phase (IQ) imbalance, orthogonal frequencydivision multiplexing (OFDM), pilot, power allocation.

Abstract-In this paper, we derive optimal pilot power allocation for OFDM systems suffering from in-phase and quadraturephase (IQ) imbalances. Existing works in literature on IQ imbalances optimize for pilot spacings and pilot designs. However, in all these works, optimal power allocation between pilot and data symbols has not been considered. Using a lower bound on the average channel capacity as a metric, we optimize for the pilot and data power allocations. Simulations show that the resulting optimal pilot power allocation increases the channel capacity along with lowering the bit error rate (BER). We further show that the power allocation is flexible in the sense that several power allocation choices exist that improve capacity compared to the equal power allocation scenario.

Abstract-Vehicle to vehicle (V2V) communication has gained renewed interest among research community which is further signified by the allocation of dedicated spectrum and an IEEE standard for their usage in recent years. However, 802.11p, the current IEEE standard for vehicular communications, has a relatively low multiplicity (the number of links that it can simultaneously support). In this work, we propose a new vehicular communication scheme based on sectored antennas in order to improve the multiplicity performance. We first show that a sectored antenna based vehicular communication system has higher multiplicity than 802.11p. To further enable multiple transmit sectors to communicate with a receive node simultaneously in a single receive sector, using an OFDMA system design, we propose a new sector-specific pilot design and corresponding channel estimation over time and frequency domains of the channels corresponding to various sectors. Finally, the performance characteristics of the proposed scheme are shown through simulations.

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Abstract-In this paper, we investigate polynomial expansion approximation to reduce matrix inversion complexity as encountered in the design of the Minimum Mean Squared Error Decision Feedback Equalizer (MMSE-DFE). The scaling factor needed in this polynomial expansion is optimized for a fixed polynomial approximation order so that the received Signal to Interference plus Noise Ratio (SINR) is maximized. The BER performance of the reduced-complexity MMSE-DFE is comparable to that of the direct matrix inversion based MMSE-DFE and outperforms earlier approaches reported in the literature.